{ "generatedAt": "2026-08-14T00:31:13.796Z", "stats": { "product": 156, "knowledge-base": 142, "gpu-mart-page": 34, "rdp-page": 120, "blog": 17 }, "docs": [ { "type": "product", "title": "NVIDIA GB300 NVL72 Supercluster", "url": "https://rdp.in/gpu-mart/product/nvidia-gb300-nvl72-supercluster/", "sku": "300576", "text": "NVIDIA GB300 NVL72 Supercluster. SKU 300576. 8-rack containerised node · 576× Blackwell Ultra B300 · 288× Grace · ~165.6 TB HBM3e · warm-water DLC . A complete NVIDIA GB300 NVL72 Supercluster in a single, turnkey containerised node. Eight liquid-cooled GB300 NVL72 racks arrive pre-integrated as one production-ready AI factory node — 576 NVIDIA Blackwell Ultra B300 GPUs and 288 Grace CPUs operating as a single coherent accelerator, delivered to your site and commissioned as a plug-and-play unit rather than assembled on the floor over months. Key highlights 8× GB300 NVL72 racks in one containerised node — 576 Blackwell Ultra B300 GPUs + 288 Grace CPUs as one system. ~165.6 TB HBM3e plus ~320 TB fast system memory as node-level unified memory. 1,040 TB/s aggregate NVLink bandwidth — near-zero-bottleneck all-to-all GPU communication. ~11.5 EFLOPS peak (FP4 sparse) and ~8.8 EFLOPS dense per node for trillion-parameter reasoning. Warm-water direct liquid cooling with in-row CDU rated up to 1.8 MW thermal dissipation. Redundant power: 64× 33 kW shelves with integrated busbars and comprehensive BMS/safety. High-speed data spine: ConnectX-8 (800 Gb/s) + BlueField-3 DPUs; Quantum-X800 InfiniBand or Spectrum-X Ethernet options. Complete stack: NVOS , full NVIDIA AI Enterprise (576 GPU subscriptions), Mission Control & DOCA — containerised and plug-and-play. AI workload fit Large-scale / foundation-model pretraining at trillion-parameter scale. Post-training alignment and fine-tuning (SFT / RLHF) on frontier models. Real-time, test-time-scaling inference and serving. Agentic AI and multi-step reasoning workloads. Generative AI (text, image, video), NLP & speech model families. HPC + AI convergence and sovereign / national-scale AI. AI workload positioning This is a rack-scale-to-node building block for an AI factory. The balance of unified HBM3e capacity, 1,040 TB/s NVLink, and a high-speed ConnectX-8 / BlueField-3 data spine lets 576 GPUs train and serve models that will not fit on a single rack, while warm-water DLC and redundant 33 kW power shelves sustain the density in continuous production. It sits at the top of the DRACO tier — above a single GB300 NVL72 rack — and scales out to 16-, 32- and 64-rack superclusters. Industry use cases Sovereign & public sector: data-resident national AI, on-soil foundation-model programs. Neocloud / AI cloud: multi-tenant training-" }, { "type": "product", "title": "DRACO 8× B300 HGX GPU Server", "url": "https://rdp.in/gpu-mart/product/draco-8x-b300-hgx-gpu-server/", "sku": "300008", "text": "DRACO 8× B300 HGX GPU Server. SKU 300008. 2× Intel Xeon 6 6767P (64-core, 2.4 GHz) · 4 TB DDR5-6400 (32× 128 GB RDIMM) · 2× 1.92 TB M.2 + 8× 3.84 TB U.2 NVMe (PCIe 4.0) · 8U rack . The DRACO 8× B300 HGX GPU Server is a factory-built, ready-to-deploy 8-GPU AI server — 8× NVIDIA B300 (HGX, Blackwell Ultra), 2× Intel Xeon 6 6767P (64-core, 2.4 GHz), 4 TB DDR5-6400 (32× 128 GB RDIMM) — assembled and validated for frontier-scale LLM training and high-throughput inference. It is a specific, in-stock configuration RDP delivers turnkey in India: landed, GST-invoiced, installed and supported, so a CIO gets a running AI node, not a procurement project. Built on the NVIDIA HGX B300 8-GPU SXM baseboard with all 8 GPUs tightly coupled over NVLink/NVSwitch, it is the class of machine that trains and serves the largest models on-prem — with data sovereignty and no per-hour cloud meter. Key highlights GPUs: 8× NVIDIA B300 (HGX, Blackwell Ultra) — 2,304 GB HBM3e (8× 288 GB), NVLink/NVSwitch-coupled. CPU: 2× Intel Xeon 6 6767P (64-core, 2.4 GHz) (128 cores) for data pipeline, orchestration and host workloads. Memory: 4 TB DDR5-6400 (32× 128 GB RDIMM). Storage: 2× 1.92 TB M.2 + 8× 3.84 TB U.2 NVMe (PCIe 4.0). Networking: 8× 800G InfiniBand XDR (ConnectX-8 SuperNIC) + 2× 200G (ConnectX-7) — cluster-ready east-west fabric. Form factor: 8U rack, air-cooled · 12× 3000W Titanium PSU (6+6 redundant). Availability: made-to-order (vendor 5-wk + delivery) · lead time 8 weeks (delivered, cleared, installed in India). Make-in-India delivery — INR price, GST tax invoice, pan-India onsite support, GeM-procurable. AI workload fit Frontier LLM training — 2,304 GB HBM3e (8× 288 GB) of coupled HBM holds large models + optimizer state for data/tensor-parallel training. High-throughput inference — serve many concurrent sessions / long-context requests per node. Fine-tuning & RAG — full-parameter and PEFT on 70B–400B-class models on a single node. HPC & scientific AI — mixed-precision simulation and AI-for-science. AI workload positioning An 8× B300 Blackwell-Ultra node carries ~2.3 TB of HBM3e and 800G XDR fabric — next-gen capacity for the largest training and reasoning workloads. A single 8-GPU node is the unit of scale for on-prem AI: cluster several over the 800G InfiniBand XDR fabric to build a pod, or run one as a self-contained training/inference engine. We do not publish fabricated token" }, { "type": "product", "title": "DRACO 8× H200 141GB SXM5 GPU Server", "url": "https://rdp.in/gpu-mart/product/draco-8x-h200-141gb-sxm5-gpu-server/", "sku": "200008", "text": "DRACO 8× H200 141GB SXM5 GPU Server. SKU 200008. 2× Intel Xeon 8558 (48-core, 2.1 GHz) · 2 TB DDR5-5600 ECC (32× 64 GB) · 2× 1.92 TB + 7.68 TB NVMe (PCIe 4.0) · 8U rack . The DRACO 8× H200 141GB SXM5 GPU Server is a factory-built, ready-to-deploy 8-GPU AI server — 8× NVIDIA H200 141 GB SXM5, 2× Intel Xeon 8558 (48-core, 2.1 GHz), 2 TB DDR5-5600 ECC (32× 64 GB) — assembled and validated for frontier-scale LLM training and high-throughput inference. It is a specific, in-stock configuration RDP delivers turnkey in India: landed, GST-invoiced, installed and supported, so a CIO gets a running AI node, not a procurement project. Built on the NVIDIA HGX H200 8-GPU SXM baseboard with all 8 GPUs tightly coupled over NVLink/NVSwitch, it is the class of machine that trains and serves the largest models on-prem — with data sovereignty and no per-hour cloud meter. Key highlights GPUs: 8× NVIDIA H200 141 GB SXM5 — 1,128 GB HBM3e (8× 141 GB), NVLink/NVSwitch-coupled. CPU: 2× Intel Xeon 8558 (48-core, 2.1 GHz) (96 cores) for data pipeline, orchestration and host workloads. Memory: 2 TB DDR5-5600 ECC (32× 64 GB). Storage: 2× 1.92 TB + 7.68 TB NVMe (PCIe 4.0). Networking: 8× 400G InfiniBand (OSFP) — cluster-ready east-west fabric. Form factor: 8U rack, air-cooled · 6× 3000W redundant PSU. Availability: 2 units (end-July batch) · lead time 7 weeks (delivered, cleared, installed in India). Make-in-India delivery — INR price, GST tax invoice, pan-India onsite support, GeM-procurable. AI workload fit Frontier LLM training — 1,128 GB HBM3e (8× 141 GB) of coupled HBM holds large models + optimizer state for data/tensor-parallel training. High-throughput inference — serve many concurrent sessions / long-context requests per node. Fine-tuning & RAG — full-parameter and PEFT on 70B–400B-class models on a single node. HPC & scientific AI — mixed-precision simulation and AI-for-science. AI workload positioning An 8× H200 SXM5 node delivers 1,128 GB of NVLink-coupled HBM3e — enough to train and serve very large models on a single machine. A single 8-GPU node is the unit of scale for on-prem AI: cluster several over the 400G InfiniBand fabric to build a pod, or run one as a self-contained training/inference engine. We do not publish fabricated tokens/sec — request a POC for your model and we will benchmark it. Industry use cases Government & sovereign AI — train national/domain models on-" }, { "type": "product", "title": "DRACO 8× B300 SXM GPU Server", "url": "https://rdp.in/gpu-mart/product/draco-8x-b300-sxm-gpu-server/", "sku": "612968", "text": "DRACO 8× B300 SXM GPU Server. SKU 612968. 2× Intel Xeon 6 · 4 TB DDR5 ECC · 120 TB NVMe · 10U rack . The DRACO 8× B300 SXM GPU Server is RDP’s flagship single-node AI server — an Rack 10U HGX B300 (Blackwell Ultra) platform with eight NVIDIA B300 SXM (HGX B300, Blackwell Ultra) GPUs delivering 2,304 GB HBM3e of HBM3e on one NVLink+NVSwitch baseboard. It is the most GPU memory and the highest single-node training and inference capacity RDP builds, sized for trillion-parameter-class frontier models — on-premises, behind your firewall, in INR, on a GST invoice. Engineered for organisations building national- or enterprise-scale AI capability in-house, it pairs the eight Blackwell Ultra GPUs with a 2× Intel Xeon 6 host, 4 TB DDR5 ECC and 120 TB NVMe, with 8× XDR InfiniBand for scale-out, liquid cooling, redundant power and full BMC/IPMI for lights-out operation. Key highlights 2,304 GB HBM3e of HBM3e across 8× B300 SXM — the largest single-node GPU-memory pool RDP offers, for trillion-parameter-class training and serving. NVLink + NVSwitch fabric — full all-to-all bandwidth across all eight Blackwell Ultra GPUs for the most demanding tensor-parallel models. Blackwell Ultra FP4/FP8 — the current generation’s highest throughput for training and high-efficiency inference. 2× Intel Xeon 6 + 4 TB DDR5 ECC — high core count and memory bandwidth to feed eight flagship GPUs. Rack 10U, liquid-cooled, redundant PSU, BMC/IPMI — sustained clocks under full load, lights-out management. 120 TB NVMe + 8× InfiniBand XDR — very large local storage and the highest-bandwidth scale-out fabric; no egress fees. On-prem data sovereignty — training data and weights stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. AI workload fit (what it actually runs — honestly) Frontier training & fine-tuning: full pre-training and fine-tuning of trillion-parameter-class models, tensor- and pipeline-parallel across the eight NVSwitch-linked Blackwell Ultra GPUs. Inference: highest-efficiency FP4/FP8 serving of the very largest models, or many large models concurrently. RAG, vision, multimodal & agentic: the most demanding production pipelines on the 120 TB NVMe and large multi-agent systems. Engineering note: all eight SXM GPUs share an NVLink+NVSwitch fabric for full all-to-all b" }, { "type": "product", "title": "DRACO NVIDIA AI Enterprise + Mission Control Suite", "url": "https://rdp.in/gpu-mart/product/draco-nvidia-ai-enterprise-mission-control-suite/", "sku": "532246", "text": "DRACO NVIDIA AI Enterprise + Mission Control Suite. SKU 532246. NVIDIA AI Enterprise + Mission Control · On-prem · Per-GPU / cluster-wide · Per-GPU annual subscription (NVIDIA AI Enterprise) . The DRACO NVIDIA AI Enterprise + Mission Control Suite is the enterprise software layer for an on-prem GPU cluster — NVIDIA AI Enterprise (supported frameworks, libraries and NIM inference microservices) plus Mission Control for cluster operations, licensed and supported through RDP. It gives AI platform teams a production-grade, security-maintained, vendor-supported software stack on their own infrastructure — in INR, on a GST invoice. Engineered to run on RDP’s GPU servers, rack-scale systems and superclusters, it is delivered configured and validated, with RDP as your single point of contact for licensing, deployment and support. Key highlights NVIDIA AI Enterprise — supported, security-maintained frameworks, CUDA-X libraries and NIM inference microservices for production AI. Mission Control — cluster operations and workload management for large GPU clusters. On-prem — runs on your infrastructure; models and data stay in-house. Enterprise support — NVIDIA’s enterprise support, fronted by RDP pan-India. Production-grade — tested, supported releases rather than DIY open-source assembly. Integrations: NVIDIA AI Enterprise, Mission Control, Base Command, NIM microservices. Validated with RDP infrastructure — delivered configured for your cluster. Make-in-India OEM partner — INR pricing, GST tax invoice, pan-India support, GeM-procurable. What it does Supported AI stack (primary): production frameworks, CUDA-X libraries and NIM microservices with enterprise support. Cluster operations: Mission Control for managing and operating large GPU clusters. Inference microservices: NIM for deploying optimised model endpoints. Security & updates: maintained, supported releases with security patching. How it works NVIDIA AI Enterprise is licensed per GPU and installed on your cluster; Mission Control manages cluster operations; RDP configures, integrates and supports the stack on your RDP infrastructure. Honest note: this is NVIDIA’s licensed software, delivered and supported through RDP — entitlements and support terms follow NVIDIA’s program, confirmed at quote. Industry use cases Government & national labs — supported, sovereign AI software. BFSI & enterpr" }, { "type": "product", "title": "DRACO 64× GB300 NVL72 AI SuperCluster", "url": "https://rdp.in/gpu-mart/product/draco-64x-gb300-nvl72-ai-supercluster/", "sku": "118513", "text": "DRACO 64× GB300 NVL72 AI SuperCluster. SKU 118513. 64× GB300 NVL72 · 2,304× NVIDIA Grace (ARM) · Grace LPDDR5X coherent memory · 64 PB parallel NVMe · Multi-Rack data hall · liquid-cooled . The DRACO 64× GB300 NVL72 AI SuperCluster is RDP’s flagship sovereign AI factory — a turnkey, liquid-cooled multi-rack data hall of 4608 Grace-Blackwell Ultra GPUs across 64 unified NVLink-domain racks, joined by a non-blocking spine-leaf InfiniBand fabric, delivering ~1.3 PB HBM3e of aggregate GPU memory. It is the largest system RDP builds, sized to train the largest foundation models a nation or enterprise will run — on-premises, in INR, on a GST invoice. Engineered for sovereign-AI programmes and national-scale operators, it is delivered as a single engagement: RDP designs the reference architecture, integrates and burns it in, and hands over one validated AI factory with one warranty and one support contract — removing multi-vendor integration risk at the largest scale. Key highlights 64× GB300 NVL72 · ~1.3 PB HBM3e aggregate — 4608 Grace-Blackwell Ultra GPUs, RDP’s largest single-engagement AI system. 64 unified NVLink domains + non-blocking InfiniBand spine — each NVL72 rack is one 72-GPU accelerator; 64 racks scale over a full-bisection fabric. 2,304× NVIDIA Grace (ARM) (coherent) + Grace LPDDR5X coherent memory — Grace CPUs coherently attached to the Blackwell Ultra GPUs. 64 PB parallel NVMe parallel filesystem — data-hall-scale training data and checkpoint storage. Multi-Rack data hall, liquid-cooled, turnkey — delivered, integrated and validated; one engagement, one warranty. On-prem data sovereignty — training data and weights stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Scale path — extend the data hall with additional SuperPODs on the same fabric. AI workload fit (what it actually runs — honestly) Frontier training: distributed pre-training of the largest foundation models across 4608 GPUs with 3D parallelism. National-scale fine-tuning & serving: fine-tune and serve many large models in parallel for an entire organisation or nation. RAG, multimodal & agentic platforms: the most demanding production AI platforms at sovereign scale. Engineering note: at this scale the data hall is the computer — 64 unified NVLink domains (72 Blackwell" }, { "type": "product", "title": "QUASAR 192-Core Arm Agentic Inference Server", "url": "https://rdp.in/gpu-mart/product/quasar-192-core-arm-agentic-inference-server/", "sku": "171299", "text": "QUASAR 192-Core Arm Agentic Inference Server. SKU 171299. AmpereOne 192-core Arm · 768 GB DDR5 ECC · 8 TB NVMe · Rack 2U · GPU-ready . The QUASAR 192-Core Arm Agentic Inference Server is a power-efficient Arm server built for high-concurrency agentic inference — a 192-core AmpereOne CPU that runs large fleets of AI agents, orchestration, RAG retrieval and quantised small-model inference at scale, without a GPU for every workload. It brings agent fleets in-house on energy-efficient cores, on-premises, in INR, on a GST invoice — and is GPU-ready when you need acceleration. Engineered for platform teams running many concurrent agents and RAG pipelines, it pairs 192 Arm cores with 768 GB of memory and fast NVMe, delivering high throughput-per-watt for orchestration-heavy and concurrency-bound agentic workloads — with PCIe slots to add GPUs for accelerated inference. Key highlights 192-core AmpereOne Arm CPU — massive concurrency for agent fleets, orchestration and RAG retrieval, with high performance-per-watt. 768 GB DDR5 ECC — large memory for many concurrent agents, vector search and caches. GPU-ready (PCIe) — add NVIDIA L40S / RTX PRO accelerators when a workload needs GPU inference. 8 TB NVMe NVMe + 2× 25 GbE — fast local storage and high-throughput networking; no egress. 2U rack, redundant PSU, BMC/IPMI — production node with lights-out remote management. Energy-efficient — high throughput-per-watt for sustained agentic inference, lowering operating cost. On-prem data sovereignty — prompts and data stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. AI workload fit (what it actually runs — honestly) High-concurrency agents (primary): run large fleets of AI agents, tool-use loops and orchestration on the 192 Arm cores — workloads that are concurrency- and I/O-bound rather than GPU-bound. RAG & retrieval: vector search, embedding lookup and retrieval pipelines at scale. Quantised small-model inference: serve quantised small LLMs on CPU for many concurrent sessions; add GPUs for larger models. Engineering note: this is a CPU-forward Arm server — it runs the Arm software stack and excels at concurrency-bound agentic and retrieval workloads, not GPU-bound large-model inference. It is GPU-ready: add accelerators for GPU inference. We help you place the right" }, { "type": "product", "title": "DRACO 250 kW In-Rack CDU", "url": "https://rdp.in/gpu-mart/product/draco-250-kw-in-rack-cdu/", "sku": "621126", "text": "DRACO 250 kW In-Rack CDU. SKU 621126. 250 kW · Up to 400 L/min · Liquid-to-liquid CDU (in-rack) · PG25 / treated water · In-rack (full-height) . The DRACO 250 kW In-Rack CDU removes the heat that dense GPU racks generate — 250 kW of cooling via liquid-to-liquid cdu (in-rack), so today’s 700 W–1 kW+ GPUs run at full clocks without thermal throttling. It is the thermal layer that makes high-density AI racks possible on-premises, in INR, on a GST invoice. Engineered to match RDP’s GPU servers, rack-scale systems and superclusters, it integrates with your facility water or runs closed-loop, and is delivered sized, plumbed and validated with the compute it cools — with leak detection and monitoring built in. Key highlights 250 kW — rack/row-level coolant distribution. Liquid-to-liquid CDU (in-rack) — distributes treated coolant to cold-plate loops with filtration and control. Up to 400 L/min · PG25 / treated water — controlled flow and coolant chemistry for reliable, corrosion-safe operation. Leak detection & monitoring — sensors and BMS/DCIM integration for safe, observable operation. Supports 1-2 dense racks — sized to the density of RDP GPU racks. Quiet, efficient — liquid moves heat far more efficiently than air, lowering fan power and PUE. Validated with RDP compute — delivered as part of a tested, cooled rack. Make-in-India OEM — predictable INR pricing, GST tax invoice, pan-India onsite support, GeM-procurable. Where it fits Dense GPU racks (primary): feeds direct-to-chip cold-plate loops across a rack or row. Rack-scale & NVL systems: the cooling that keeps NVL72-class racks within thermal limits. Retrofit or new build: design a liquid-cooled hall, or add density to a room. Edge/micro-DC: sealed/compact options for self-contained sites. How it works The unit isolates the rack coolant loop from facility water, controls flow, temperature and pressure, filters the coolant, and distributes it to the cold-plate loops. RDP sizes the loop, flow and coolant to your rack density and facility. Honest note: real cooling capacity depends on inlet water temperature, flow and rack layout — we size and validate it for your room. Industry use cases AI data centres — cool dense GPU and NVL racks at full clocks. Government & national labs — sovereign HPC/AI cooling. Neocloud / AI providers — higher density per rack, lower PUE. Manufacturing & energy — HPC + AI" }, { "type": "product", "title": "DRACO 16 PB Parallel-FS NVMe AI Storage", "url": "https://rdp.in/gpu-mart/product/draco-16-pb-parallel-fs-nvme-ai-storage/", "sku": "269611", "text": "DRACO 16 PB Parallel-FS NVMe AI Storage. SKU 269611. 16 PB usable (NVMe) · 9.6 TB/s read · Parallel FS (Lustre/GPFS-class) · 256× 400G InfiniBand/Ethernet · Multi-rack (64-node) . The DRACO 16 PB Parallel-FS NVMe AI Storage is RDP’s flagship parallel-filesystem NVMe storage system — built to feed the largest GPU superclusters and supercomputers during frontier AI training. It delivers 16 PB usable (NVMe) at 9.6 TB/s read with GPUDirect Storage across a single clustered namespace, so datasets, checkpoints and weights stream to thousands of GPUs in parallel without the storage ever becoming the bottleneck — on-premises, in INR, on a GST invoice. Engineered for the most demanding AI/HPC data pipelines, it presents one parallel namespace over a 400G fabric and scales capacity and bandwidth together by adding nodes — delivered racked, configured and validated as one system with one warranty and one support contract. Key highlights 16 PB usable (NVMe) · 9.6 TB/s read — frontier-scale bandwidth sized to feed thousands of GPUs. Parallel filesystem + GPUDirect Storage — a single namespace; data streams from NVMe straight to GPU memory across the supercluster. Parallel FS (Lustre/GPFS-class) + NFS/S3, GPUDirect Storage — parallel and standard protocols so existing pipelines and schedulers just work. 1,536× 15.36 TB NVMe (64 nodes) — dense enterprise NVMe with end-to-end data integrity across 64 nodes. 256× 400G InfiniBand/Ethernet — very high aggregate bandwidth to the GPU fabric; bandwidth grows with capacity. 640M random read — high aggregate random-read IOPS for metadata- and small-file-heavy datasets. On-prem data sovereignty — datasets and weights stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Where it fits Frontier training data lake (primary): streams datasets to a GPU supercluster in parallel without starving any node. Checkpoints & weights: fast parallel write/read of the largest checkpoints during frontier runs. RAG & vector stores: low-latency storage for the largest embeddings and indexes. HPC scratch: high-throughput scratch for the largest simulations alongside AI. How it works A clustered parallel filesystem stripes data across 64 NVMe nodes and presents one namespace over 256× 400G InfiniBand/Ethernet. With GPUDirect Storage, reads bypa" }, { "type": "product", "title": "DRACO 64-Port 800G InfiniBand Switch", "url": "https://rdp.in/gpu-mart/product/draco-64-port-800g-infiniband-switch/", "sku": "145727", "text": "DRACO 64-Port 800G InfiniBand Switch. SKU 145727. 64× 800G OSFP (XDR) · 102 Tb/s switching · InfiniBand XDR (Quantum-X800 class) · <600 ns port-to-port · 1U . The DRACO 64-Port 800G InfiniBand Switch is the high-bandwidth interconnect that turns a pile of GPU servers into a cluster. It provides 64× 800G OSFP (XDR) at 102 Tb/s of non-blocking switching over InfiniBand XDR (Quantum-X800 class), with <600 ns port-to-port — the low-latency, lossless fabric that lets distributed AI training scale across nodes without the network becoming the bottleneck. On-premises, in INR, on a GST invoice. Engineered as the fabric layer of an RDP AI cluster, it carries the collective (all-reduce) traffic that dominates multi-node training, and is delivered configured, cabled and validated alongside the compute and storage it connects. Key highlights 64× 800G OSFP (XDR) · 102 Tb/s — non-blocking switching to wire a GPU cluster at full bandwidth. InfiniBand XDR (Quantum-X800 class) — RDMA, lossless, in-network compute (SHARP) for fast collectives. <600 ns port-to-port — low latency so distributed training scales with near-linear efficiency. 800G / 400G per port — flexible speeds to match your GPU NICs/DPUs. Spine-leaf ready — combine switches into a non-blocking fabric for hundreds to thousands of GPUs. Validated with RDP compute — delivered as part of a tested cluster, not a loose box. On-prem sovereignty — your fabric, your data path; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8517), pan-India onsite support, GeM-procurable. Where it fits GPU cluster fabric (primary): the interconnect between GPU servers that carries distributed-training collectives. Storage fabric: high-bandwidth path between GPU nodes and the NVMe parallel-FS (GPUDirect). Scale-out spine: a leaf or spine in a non-blocking topology for large clusters. HPC interconnect: tightly-coupled MPI and AI collectives. How it works The switch forms a leaf/spine fabric with RDMA over InfiniBand; GPU NICs/DPUs connect at 800G / 400G. In-network compute (SHARP) offloads reductions, and adaptive routing avoids hotspots — so all-reduce traffic, which dominates multi-node training, completes fast. RDP sizes the topology (oversubscription, spine count) to your cluster. Honest note: real scaling efficiency depends on topology, collective library and model — we validate it on yo" }, { "type": "product", "title": "DRACO 16384× MI300A AI Supercomputer", "url": "https://rdp.in/gpu-mart/product/draco-16384x-mi300a-ai-supercomputer/", "sku": "375905", "text": "DRACO 16384× MI300A AI Supercomputer. SKU 375905. 16384× MI300A · Integrated AMD Zen4 (APU, per node) · Unified APU memory (HBM3) · 256 PB parallel NVMe · Data hall · liquid-cooled . The DRACO 16384× MI300A AI Supercomputer is RDP’s flagship exascale HPC + AI supercomputer — 16384 AMD Instinct MI300A APUs, the same accelerator architecture behind the world’s leadership-class FP64 systems, delivering ~2.1 PB unified HBM3 of unified accelerator memory in a full liquid-cooled data hall on a non-blocking InfiniBand spine. It is the largest converged simulation-and-AI machine RDP builds, engineered for national programmes — on-premises, in INR, on a GST invoice. Delivered as a single national engagement, RDP co-designs the reference architecture, integrates, cools and burns it in, and hands over one validated supercomputer with one warranty and one support contract. Its defining strength: FP64 HPC leadership and AI fused in one APU with unified CPU-GPU memory. Key highlights 16384× MI300A · ~2.1 PB unified HBM3 aggregate — flagship exascale accelerator memory for the largest simulations and frontier AI. Infinity Fabric + non-blocking InfiniBand — Infinity Fabric across the APUs and a full-bisection InfiniBand spine across the data hall. Unified CPU-GPU APU memory — Zen4 CPU and CDNA GPU share one HBM3 pool, eliminating host-device transfers for HPC + AI. FP64 HPC leadership — the architecture of the world’s top FP64 supercomputers, with mixed-precision AI on the same nodes. 256 PB parallel NVMe parallel filesystem — exascale-grade storage for datasets, checkpoints and simulation output. Data hall, liquid-cooled, turnkey — delivered, integrated and validated as one engagement. On-prem data sovereignty — data, models and codes stay in-country; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. AI workload fit (what it actually runs — honestly) HPC + simulation: leadership-class FP64 scientific computing (CFD, climate, molecular dynamics, finite-element) at national scale. Frontier AI training: distributed training of the largest foundation models across 16384 APUs with 3D parallelism. Large-scale inference & fine-tuning: serve and fine-tune many large models in parallel. Engineering note: this is an AMD Instinct system — it runs the open ROCm/HIP software" }, { "type": "product", "title": "NVIDIA GB300 NVL72 Rack-Scale AI Factory", "url": "https://rdp.in/gpu-mart/product/nvidia-gb300-nvl72-rack-scale-ai-factory/", "sku": "300072", "text": "NVIDIA GB300 NVL72 Rack-Scale AI Factory. SKU 300072. 72 Blackwell Ultra GPUs · 36 Grace CPUs · 20 TB GPU memory · liquid-cooled NVL72 rack . The NVIDIA GB300 NVL72 Rack-Scale AI Factory is a liquid-cooled, rack-scale AI infrastructure system built on the NVIDIA Blackwell Ultra platform. It unifies 72 Blackwell Ultra GPUs and 36 Grace CPUs into a single NVLink domain, so an entire rack operates as one accelerator for trillion-parameter training and test-time-scaling inference. Delivered, integrated and supported across India by RDP Technologies Limited — predictable INR pricing, GST invoice and pan-India onsite support. Key highlights 72 NVIDIA Blackwell Ultra GPUs and 36 NVIDIA Grace CPUs unified as a single NVLink domain — the rack behaves as one accelerator. 130 TB/s NVLink scale-up bandwidth across all 72 GPUs. 20 TB GPU memory, 37 TB fast memory and 17 TB LPDDR5X CPU memory for trillion-parameter models and long-context inference. 2,592 Arm Neoverse V2 cores (36 Grace CPUs) for data orchestration and CPU-side pipelines. Fully liquid-cooled rack-scale architecture for sustained high-density performance and energy efficiency. Engineered for AI factories: training, fine-tuning, high-throughput inference, test-time scaling and agentic / reasoning systems. Delivered as a validated reference-architecture rack — onsite integration, deployment and pan-India support by RDP. Make-in-India delivery; GST invoice; available on GeM for government and PSU procurement. AI workload positioning The GB300 NVL72 is built to be an AI factory, not a single server. With 20 TB of GPU memory, a 130 TB/s NVLink scale-up fabric and 54 TB of total fast and CPU memory across 72 Blackwell Ultra GPUs and 36 Grace CPUs, one rack can train and serve trillion-parameter models, run test-time-scaling (reasoning) inference and host large agentic systems that would otherwise require a room of disaggregated servers. Because the whole rack is one NVLink domain, parallelism scales up rather than out, removing network bottlenecks at frontier scale. Built for AI factories — who it is for Enterprise AI labs and frontier-model teams Cloud, neocloud and hosting providers building AI capacity Government and sovereign AI programmes Research organisations and national HPC / AI centres Large IT and infrastructure teams standing up AI factories System integrators and hyperscale AI operations Why it matt" }, { "type": "product", "title": "DRACO Managed Operations and SLA", "url": "https://rdp.in/gpu-mart/product/draco-managed-operations-and-sla/", "sku": "953029", "text": "DRACO Managed Operations and SLA. SKU 953029. Managed datacentre operations (NOC, SLA-backed) · 24×7 NOC with SLA-backed uptime · Pan-India, remote plus onsite · 1–5 years . The DRACO Managed Operations and SLA is a fully managed datacentre operations service from RDP — Managed datacentre operations (NOC, SLA-backed), delivered pan-india, remote plus onsite on a GST tax invoice in INR. It wraps your RDP GPU Mart infrastructure in the people, process and SLA that keep it running, so your team focuses on the AI, not the operations. RDP runs your infrastructure for you — monitoring, patching, capacity, incident and change management against an agreed SLA — so you consume outcomes, not operations. Key highlights Service: Managed datacentre operations (NOC, SLA-backed). SLA: 24×7 NOC with SLA-backed uptime. Coverage: Pan-India, remote plus onsite. Engagement: Monthly / annual managed service (OpEx). Term: 1–5 years. Single point of contact — RDP owns the outcome end-to-end. Made-in-India OEM-direct — no third-party reseller layer between you and the people who built the hardware. GST invoice, INR billing, GeM-procurable. Scope of work 24×7 NOC — monitoring, alerting, incident and problem management. Patch & firmware management — scheduled, tested updates across the fleet. Capacity & performance — utilisation reporting and growth planning. Change & reporting — governed changes with monthly SLA reports. How it works RDP operates your estate to an agreed SLA — monitoring, patching, capacity and change — and reports against it monthly, while you retain ownership and control. Honest note: exact scope, response times and pricing are confirmed in the service agreement at quote — we do not quote SLAs we cannot staff for in your location. Industry use cases Government & PSU — SLA-backed operations and GeM-procurable contracts. BFSI — mission-critical uptime with audit-ready documentation. Healthcare — supported infrastructure under data-residency and continuity rules. Manufacturing & ITES — multi-site coverage and predictable OpEx. Neocloud & research — run-and-grow operations and flexible financing. SLA and how to be sure The commitment is 24×7 NOC with SLA-backed uptime. Want certainty? Ask for a reference customer and a sample SLA report before you sign — we will show you how response, resolution and uptime are measured and reported. We do not promise SLAs we cannot me" }, { "type": "product", "title": "DRACO 24×7 Mission-Critical AMC", "url": "https://rdp.in/gpu-mart/product/draco-24x7-mission-critical-amc/", "sku": "241282", "text": "DRACO 24×7 Mission-Critical AMC. SKU 241282. Premium mission-critical support (24×7 AMC) · 24×7, 4-hour onsite, proactive monitoring · Pan-India with a dedicated technical account manager · 1–5 years . The DRACO 24×7 Mission-Critical AMC is a premium round-the-clock support contract from RDP — Premium mission-critical support (24×7 AMC), delivered pan-india with a dedicated technical account manager on a GST tax invoice in INR. It wraps your RDP GPU Mart infrastructure in the people, process and SLA that keep it running, so your team focuses on the AI, not the operations. It is the highest support tier: round-the-clock coverage, four-hour onsite, proactive monitoring and a dedicated technical account manager — for infrastructure that simply cannot go down. Key highlights Service: Premium mission-critical support (24×7 AMC). SLA: 24×7, 4-hour onsite, proactive monitoring. Coverage: Pan-India with a dedicated technical account manager. Engagement: Annual subscription (premium AMC). Term: 1–5 years. Single point of contact — RDP owns the outcome end-to-end. Made-in-India OEM-direct — no third-party reseller layer between you and the people who built the hardware. GST invoice, INR billing, GeM-procurable. Scope of work 24×7 break-fix — any hour, every day, with 4-hour onsite response. Proactive monitoring — RDP watches health and opens tickets before you notice. Dedicated TAM — a named technical account manager and quarterly reviews. Pre-positioned spares — critical parts staged for fastest recovery. How it works RDP monitors your estate 24×7, responds onsite within four hours at any hour, and a dedicated TAM owns the relationship and reporting. Honest note: exact scope, response times and pricing are confirmed in the service agreement at quote — we do not quote SLAs we cannot staff for in your location. Industry use cases Government & PSU — SLA-backed operations and GeM-procurable contracts. BFSI — mission-critical uptime with audit-ready documentation. Healthcare — supported infrastructure under data-residency and continuity rules. Manufacturing & ITES — multi-site coverage and predictable OpEx. Neocloud & research — run-and-grow operations and flexible financing. SLA and how to be sure The commitment is 24×7, 4-hour onsite, proactive monitoring. Want certainty? Ask for a reference customer and a sample SLA report before you sign — we will show you how respons" }, { "type": "product", "title": "QUASAR Mission-Ready AMC (4-Hour)", "url": "https://rdp.in/gpu-mart/product/quasar-mission-ready-amc-4-hour/", "sku": "673911", "text": "QUASAR Mission-Ready AMC (4-Hour). SKU 673911. Priority hardware support and maintenance (AMC) · 4-hour onsite response (business hours) · Pan-India metro and tier-2 cities · 1–5 years . The QUASAR Mission-Ready AMC (4-Hour) is a priority support contract with a 4-hour response from RDP — Priority hardware support and maintenance (AMC), delivered pan-india metro and tier-2 cities on a GST tax invoice in INR. It wraps your RDP GPU Mart infrastructure in the people, process and SLA that keep it running, so your team focuses on the AI, not the operations. It guarantees a four-hour onsite response with pre-positioned spares for production systems where downtime is measured in money, not days. Key highlights Service: Priority hardware support and maintenance (AMC). SLA: 4-hour onsite response (business hours). Coverage: Pan-India metro and tier-2 cities. Engagement: Annual subscription (AMC). Term: 1–5 years. Single point of contact — RDP owns the outcome end-to-end. Made-in-India OEM-direct — no third-party reseller layer between you and the people who built the hardware. GST invoice, INR billing, GeM-procurable. Scope of work 4-hour onsite break-fix — guaranteed response in covered cities. Pre-positioned spares — critical parts staged near your site. Proactive monitoring option — alerting tied to the priority queue. Named escalation — direct line to senior engineers. How it works You log a critical ticket; RDP responds onsite within four business hours with pre-positioned spares and a named escalation path. Honest note: exact scope, response times and pricing are confirmed in the service agreement at quote — we do not quote SLAs we cannot staff for in your location. Industry use cases Government & PSU — SLA-backed support and GeM-procurable service contracts. BFSI — mission-critical uptime with audit-ready documentation. Healthcare — supported infrastructure under data-residency and continuity rules. Manufacturing & ITES — multi-site coverage and predictable OpEx. Research & higher-ed — long-life support for shared clusters on tight budgets. SLA and how to be sure The commitment is 4-hour onsite response (business hours). Want certainty? Ask for a reference customer and a sample SLA report before you sign — we will show you how response, resolution and uptime are measured and reported. We do not promise SLAs we cannot meet in your region. Service tiers and upgr" }, { "type": "product", "title": "CARINA Remote-Site and Edge AMC", "url": "https://rdp.in/gpu-mart/product/carina-remote-site-and-edge-amc/", "sku": "779025", "text": "CARINA Remote-Site and Edge AMC. SKU 779025. Edge and remote-site hardware support (AMC) · Next-business-day at remote and edge locations · Pan-India including remote and edge sites · 1–3 years . The CARINA Remote-Site and Edge AMC is an annual support contract for remote and edge sites from RDP — Edge and remote-site hardware support (AMC), delivered pan-india including remote and edge sites on a GST tax invoice in INR. It wraps your RDP GPU Mart infrastructure in the people, process and SLA that keep it running, so your team focuses on the AI, not the operations. It extends genuine onsite support to branches, factories, retail and telco-edge locations that sit outside metro coverage — so distributed infrastructure is not left unsupported. Key highlights Service: Edge and remote-site hardware support (AMC). SLA: Next-business-day at remote and edge locations. Coverage: Pan-India including remote and edge sites. Engagement: Annual subscription (AMC). Term: 1–3 years. Single point of contact — RDP owns the outcome end-to-end. Made-in-India OEM-direct — no third-party reseller layer between you and the people who built the hardware. GST invoice, INR billing, GeM-procurable. Scope of work Remote-site break-fix — next-business-day engineer dispatch to edge locations. Genuine spares — OEM parts forwarded to remote sites. Remote diagnostics — triage before dispatch to cut truck rolls. Multi-site case management — one contract across all your locations. How it works You register your remote/edge sites; RDP provides remote diagnostics plus next-business-day onsite dispatch across those locations under one AMC. Honest note: exact scope, response times and pricing are confirmed in the service agreement at quote — we do not quote SLAs we cannot staff for in your location. Industry use cases Government & PSU — SLA-backed support and GeM-procurable service contracts. BFSI — mission-critical uptime with audit-ready documentation. Healthcare — supported infrastructure under data-residency and continuity rules. Manufacturing & ITES — multi-site coverage and predictable OpEx. Research & higher-ed — long-life support for shared clusters on tight budgets. SLA and how to be sure The commitment is Next-business-day at remote and edge locations. Want certainty? Ask for a reference customer and a sample SLA report before you sign — we will show you how response, resolution and upt" }, { "type": "product", "title": "QUASAR Onsite Support AMC", "url": "https://rdp.in/gpu-mart/product/quasar-onsite-support-amc/", "sku": "930534", "text": "QUASAR Onsite Support AMC. SKU 930534. Priority hardware support and annual maintenance (AMC) · Same-day / 8-business-hour onsite response · Pan-India · 1–5 years . The QUASAR Onsite Support AMC is a professional-tier annual support contract (AMC) from RDP — Priority hardware support and annual maintenance (AMC), delivered pan-india on a GST tax invoice in INR. It wraps your RDP GPU Mart infrastructure in the people, process and SLA that keep it running, so your team focuses on the AI, not the operations. It adds faster response and proactive firmware/health management to standard AMC — for production systems that cannot wait until tomorrow. Key highlights Service: Priority hardware support and annual maintenance (AMC). SLA: Same-day / 8-business-hour onsite response. Coverage: Pan-India. Engagement: Annual subscription (AMC). Term: 1–5 years. Single point of contact — RDP owns the outcome end-to-end. Made-in-India OEM-direct — no third-party reseller layer between you and the people who built the hardware. GST invoice, INR billing, GeM-procurable. Scope of work Priority onsite break-fix — same-day / 8-business-hour engineer dispatch. Genuine spares — OEM parts, with optional onsite spares kit. Proactive firmware & health — scheduled updates and periodic health reviews. Named case management — priority queue and single point of contact. How it works You log a priority ticket; RDP dispatches an engineer same-day / within 8 business hours, supported by proactive firmware and health reviews. Honest note: exact scope, response times and pricing are confirmed in the service agreement at quote — we do not quote SLAs we cannot staff for in your location. Industry use cases Government & PSU — SLA-backed support and GeM-procurable service contracts. BFSI — mission-critical uptime with audit-ready documentation. Healthcare — supported infrastructure under data-residency and continuity rules. Manufacturing & ITES — multi-site coverage and predictable OpEx. Research & higher-ed — long-life support for shared clusters on tight budgets. SLA and how to be sure The commitment is Same-day / 8-business-hour onsite response. Want certainty? Ask for a reference customer and a sample SLA report before you sign — we will show you how response, resolution and uptime are measured and reported. We do not promise SLAs we cannot meet in your region. Service tiers and upgrade path CARI" }, { "type": "product", "title": "CARINA Onsite Support AMC", "url": "https://rdp.in/gpu-mart/product/carina-onsite-support-amc/", "sku": "991969", "text": "CARINA Onsite Support AMC. SKU 991969. Hardware support and annual maintenance (AMC) · Next-business-day onsite response · Pan-India · 1–3 years . The CARINA Onsite Support AMC is an annual hardware support contract (AMC) from RDP — Hardware support and annual maintenance (AMC), delivered pan-india on a GST tax invoice in INR. It wraps your RDP GPU Mart infrastructure in the people, process and SLA that keep it running, so your team focuses on the AI, not the operations. It keeps your RDP infrastructure covered with onsite engineers, genuine spares and a single escalation path — predictable support without per-incident surprises. Key highlights Service: Hardware support and annual maintenance (AMC). SLA: Next-business-day onsite response. Coverage: Pan-India. Engagement: Annual subscription (AMC). Term: 1–3 years. Single point of contact — RDP owns the outcome end-to-end. Made-in-India OEM-direct — no third-party reseller layer between you and the people who built the hardware. GST invoice, INR billing, GeM-procurable. Scope of work Onsite break-fix — next-business-day engineer dispatch for hardware faults. Genuine spares — OEM parts from pan-India depots. Firmware & advisories — guided updates and security advisories. Case management — logged tickets with a single point of contact. How it works You log a ticket; RDP dispatches an engineer and parts to your site on a next-business-day basis and manages the case to closure. Honest note: exact scope, response times and pricing are confirmed in the service agreement at quote — we do not quote SLAs we cannot staff for in your location. Industry use cases Government & PSU — SLA-backed support and GeM-procurable service contracts. BFSI — mission-critical uptime with audit-ready documentation. Healthcare — supported infrastructure under data-residency and continuity rules. Manufacturing & ITES — multi-site coverage and predictable OpEx. Research & higher-ed — long-life support for shared clusters on tight budgets. SLA and how to be sure The commitment is Next-business-day onsite response. Want certainty? Ask for a reference customer and a sample SLA report before you sign — we will show you how response, resolution and uptime are measured and reported. We do not promise SLAs we cannot meet in your region. Service tiers and upgrade path CARINA — essential support: next-business-day onsite, core coverage. QUASAR — pr" }, { "type": "product", "title": "DRACO DCIM Monitoring — Multi-DC", "url": "https://rdp.in/gpu-mart/product/draco-dcim-monitoring-multi-dc/", "sku": "767186", "text": "DRACO DCIM Monitoring — Multi-DC. SKU 767186. DCIM & cluster monitoring · On-prem (multi-site) · Multi-DC / unlimited nodes · Enterprise annual subscription . The DRACO DCIM Monitoring — Multi-DC gives operators a single pane of glass over the AI cluster — health, power, thermal and utilisation telemetry from servers, PDUs and CDUs, with alerting. It runs on-premises behind your firewall, in INR, on a GST invoice, and is delivered configured and validated with the RDP infrastructure it manages. Engineered for AI operations teams, it turns raw infrastructure telemetry into actionable operations, integrated with the rest of the RDP stack. Key highlights DCIM & cluster monitoring — unified health, power, thermal and utilisation monitoring across the cluster. On-prem (multi-site) — runs on-prem; telemetry never leaves the site. Multi-DC / unlimited nodes — sized for clusters of this scale, licensed per node. Proactive alerting — thresholds and anomaly alerts catch issues before downtime. Role-based dashboards — per-team views and historical analytics. Integrations: Redfish/IPMI, PDU, CDU, Prometheus/Grafana. Validated with RDP infrastructure — delivered configured for your cluster. Make-in-India OEM — predictable INR pricing, GST tax invoice, pan-India support, GeM-procurable. What it does Monitoring (primary): collect health, power, thermal and utilisation telemetry. Alerting: thresholds, anomaly detection and notifications. Capacity planning: trends and reports for capacity and energy planning. Dashboards: role-based dashboards and historical analytics. How it works Agents and standard protocols (Redfish/IPMI, SNMP, PDU/CDU APIs) feed a time-series database and dashboards; a rules engine raises alerts and analytics report trends. RDP configures it for your cluster and integrates it with the RDP stack. Honest note: real observability depends on configuration — we tune it for your cluster. Industry use cases Neocloud / AI providers — operations visibility across a GPU cloud. Government & national labs — sovereign, maintained AI monitoring. BFSI & enterprise — governed, supported AI platforms. Research & higher-ed — a ready AI environment for teams. Manufacturing & energy — managed HPC + AI operations. Telecom — large-scale cluster operations. Outcomes — and how to be sure The outcome is fewer outages and clear operations visibility. Want certainty? Request a pil" }, { "type": "product", "title": "DRACO DCIM Monitoring — up to 4,096 Nodes", "url": "https://rdp.in/gpu-mart/product/draco-dcim-monitoring-up-to-4-096-nodes/", "sku": "236445", "text": "DRACO DCIM Monitoring — up to 4,096 Nodes. SKU 236445. DCIM & cluster monitoring · On-prem · Up to 4,096 nodes · Per-node annual subscription . The DRACO DCIM Monitoring — up to 4,096 Nodes gives operators a single pane of glass over the AI cluster — health, power, thermal and utilisation telemetry from servers, PDUs and CDUs, with alerting. It runs on-premises behind your firewall, in INR, on a GST invoice, and is delivered configured and validated with the RDP infrastructure it manages. Engineered for AI operations teams, it turns raw infrastructure telemetry into actionable operations, integrated with the rest of the RDP stack. Key highlights DCIM & cluster monitoring — unified health, power, thermal and utilisation monitoring across the cluster. On-prem — runs on-prem; telemetry never leaves the site. Up to 4,096 nodes — sized for clusters of this scale, licensed per node. Proactive alerting — thresholds and anomaly alerts catch issues before downtime. Role-based dashboards — per-team views and historical analytics. Integrations: Redfish/IPMI, PDU, CDU, Prometheus/Grafana. Validated with RDP infrastructure — delivered configured for your cluster. Make-in-India OEM — predictable INR pricing, GST tax invoice, pan-India support, GeM-procurable. What it does Monitoring (primary): collect health, power, thermal and utilisation telemetry. Alerting: thresholds, anomaly detection and notifications. Capacity planning: trends and reports for capacity and energy planning. Dashboards: role-based dashboards and historical analytics. How it works Agents and standard protocols (Redfish/IPMI, SNMP, PDU/CDU APIs) feed a time-series database and dashboards; a rules engine raises alerts and analytics report trends. RDP configures it for your cluster and integrates it with the RDP stack. Honest note: real observability depends on configuration — we tune it for your cluster. Industry use cases Neocloud / AI providers — operations visibility across a GPU cloud. Government & national labs — sovereign, maintained AI monitoring. BFSI & enterprise — governed, supported AI platforms. Research & higher-ed — a ready AI environment for teams. Manufacturing & energy — managed HPC + AI operations. Telecom — large-scale cluster operations. Outcomes — and how to be sure The outcome is fewer outages and clear operations visibility. Want certainty? Request a pilot on your cluster before yo" }, { "type": "product", "title": "DRACO DCIM Monitoring — up to 1,024 Nodes", "url": "https://rdp.in/gpu-mart/product/draco-dcim-monitoring-up-to-1-024-nodes/", "sku": "979186", "text": "DRACO DCIM Monitoring — up to 1,024 Nodes. SKU 979186. DCIM & cluster monitoring · On-prem · Up to 1,024 nodes · Per-node annual subscription . The DRACO DCIM Monitoring — up to 1,024 Nodes gives operators a single pane of glass over the AI cluster — health, power, thermal and utilisation telemetry from servers, PDUs and CDUs, with alerting. It runs on-premises behind your firewall, in INR, on a GST invoice, and is delivered configured and validated with the RDP infrastructure it manages. Engineered for AI operations teams, it turns raw infrastructure telemetry into actionable operations, integrated with the rest of the RDP stack. Key highlights DCIM & cluster monitoring — unified health, power, thermal and utilisation monitoring across the cluster. On-prem — runs on-prem; telemetry never leaves the site. Up to 1,024 nodes — sized for clusters of this scale, licensed per node. Proactive alerting — thresholds and anomaly alerts catch power/thermal issues before downtime. Role-based dashboards — per-team views and historical analytics. Integrations: Redfish/IPMI, PDU, CDU, Prometheus/Grafana. Validated with RDP infrastructure — delivered configured for your cluster. Make-in-India OEM — predictable INR pricing, GST tax invoice, pan-India support, GeM-procurable. What it does Monitoring (primary): collect health, power, thermal and utilisation telemetry across servers, PDUs and CDUs. Alerting: thresholds, anomaly detection and notifications. Capacity planning: trends and reports for capacity and energy planning. Dashboards: role-based dashboards and historical analytics. How it works Agents and standard protocols (Redfish/IPMI, SNMP, PDU/CDU APIs) feed a time-series database and dashboards; a rules engine raises alerts and the analytics layer reports trends. RDP configures it for your topology and integrates it with the RDP stack. Honest note: real observability depends on configuration — we tune it for your cluster. Industry use cases Neocloud / AI providers — operations visibility across a GPU cloud. Government & national labs — sovereign cluster monitoring. BFSI & enterprise — governed AI operations. Research & higher-ed — shared cluster observability. Manufacturing & energy — managed HPC + AI operations. Colocation — multi-tenant operations visibility. Outcomes — and how to be sure The outcome is fewer outages and clear operations visibility. Want certainty?" }, { "type": "product", "title": "QUASAR Edge DCIM Monitoring", "url": "https://rdp.in/gpu-mart/product/quasar-edge-dcim-monitoring/", "sku": "346616", "text": "QUASAR Edge DCIM Monitoring. SKU 346616. DCIM & cluster monitoring · On-prem · Edge / distributed sites · Per-node annual subscription . The QUASAR Edge DCIM Monitoring gives operators a single pane of glass over the AI cluster — health, power, thermal and utilisation telemetry from servers, PDUs and CDUs, with alerting, across distributed edge sites. It runs on-premises behind your firewall, in INR, on a GST invoice, and is delivered configured and validated with the RDP infrastructure it manages. Engineered for AI operations teams, it turns raw infrastructure telemetry into actionable operations, integrated with the rest of the RDP stack and fleet-managed across sites. Key highlights DCIM & cluster monitoring — unified health, power, thermal and utilisation monitoring across the cluster and edge fleet. On-prem — runs on-prem; telemetry never leaves the site. Edge / distributed sites — sized for distributed edge estates, licensed per node. Proactive alerting — thresholds and anomaly alerts catch power/thermal issues before downtime. Role-based dashboards — per-team views and historical analytics. Integrations: Redfish/IPMI, PDU, CDU, Prometheus/Grafana. Validated with RDP infrastructure — delivered configured for your cluster. Make-in-India OEM — predictable INR pricing, GST tax invoice, pan-India support, GeM-procurable. What it does Monitoring (primary): collect health, power, thermal and utilisation telemetry across servers, PDUs and CDUs at every site. Alerting: thresholds, anomaly detection and notifications. Capacity planning: trends and reports for capacity and energy planning. Dashboards: role-based dashboards and historical analytics, with a fleet view across sites. How it works Agents and standard protocols (Redfish/IPMI, SNMP, PDU/CDU APIs) feed a time-series database and dashboards; a rules engine raises alerts and the analytics layer reports trends; edge sites roll up to a central fleet view. RDP configures it for your topology and integrates it with the RDP stack. Honest note: real observability depends on configuration — we tune it for your cluster. Industry use cases Neocloud / AI providers — operations visibility across a GPU cloud. Government & national labs — sovereign cluster monitoring. BFSI & enterprise — governed AI operations. Research & higher-ed — shared cluster observability. Telecom & edge — distributed edge fleet monitoring. Col" }, { "type": "product", "title": "QUASAR DCIM Monitoring — up to 256 Nodes", "url": "https://rdp.in/gpu-mart/product/quasar-dcim-monitoring-up-to-256-nodes/", "sku": "774244", "text": "QUASAR DCIM Monitoring — up to 256 Nodes. SKU 774244. DCIM & cluster monitoring · On-prem · Up to 256 nodes · Per-node annual subscription . The QUASAR DCIM Monitoring — up to 256 Nodes gives operators a single pane of glass over the AI cluster — health, power, thermal and utilisation telemetry from servers, PDUs and CDUs, with alerting. It runs on-premises behind your firewall, in INR, on a GST invoice, and is delivered configured and validated with the RDP infrastructure it manages. Engineered for AI operations teams, it turns raw infrastructure telemetry into actionable operations, integrated with the rest of the RDP stack. Key highlights DCIM & cluster monitoring — unified health, power, thermal and utilisation monitoring across the cluster. On-prem — runs on-prem; telemetry never leaves the site. Up to 256 nodes — sized for clusters of this scale, licensed per node. Proactive alerting — thresholds and anomaly alerts catch power/thermal issues before downtime. Role-based dashboards — per-team views and historical analytics. Integrations: Redfish/IPMI, PDU, CDU, Prometheus/Grafana. Validated with RDP infrastructure — delivered configured for your cluster. Make-in-India OEM — predictable INR pricing, GST tax invoice, pan-India support, GeM-procurable. What it does Monitoring (primary): collect health, power, thermal and utilisation telemetry across servers, PDUs and CDUs. Alerting: thresholds, anomaly detection and notifications. Capacity planning: trends and reports for capacity and energy planning. Dashboards: role-based dashboards and historical analytics. How it works Agents and standard protocols (Redfish/IPMI, SNMP, PDU/CDU APIs) feed a time-series database and dashboards; a rules engine raises alerts and the analytics layer reports trends. RDP configures it for your topology and integrates it with the RDP stack. Honest note: real observability depends on configuration — we tune it for your cluster. Industry use cases Neocloud / AI providers — operations visibility across a GPU cloud. Government & national labs — sovereign cluster monitoring. BFSI & enterprise — governed AI operations. Research & higher-ed — shared cluster observability. Manufacturing & energy — managed HPC + AI operations. Colocation — multi-tenant operations visibility. Outcomes — and how to be sure The outcome is fewer outages and clear operations visibility. Want certainty? Reque" }, { "type": "product", "title": "QUASAR DCIM Monitoring — up to 64 Nodes", "url": "https://rdp.in/gpu-mart/product/quasar-dcim-monitoring-up-to-64-nodes/", "sku": "671932", "text": "QUASAR DCIM Monitoring — up to 64 Nodes. SKU 671932. DCIM & cluster monitoring · On-prem · Up to 64 nodes · Per-node annual subscription . The QUASAR DCIM Monitoring — up to 64 Nodes gives operators a single pane of glass over the AI cluster — health, power, thermal and utilisation telemetry from servers, PDUs and CDUs, with alerting. It runs on-premises behind your firewall, in INR, on a GST invoice, and is delivered configured and validated with the RDP infrastructure it manages. Engineered for AI platform and operations teams, it turns raw infrastructure telemetry into actionable operations, integrated with the rest of the RDP stack. Key highlights DCIM & cluster monitoring — unified health, power, thermal and utilisation monitoring across the cluster. On-prem — runs on-prem; your data and telemetry never leave the site. Up to 64 nodes — sized for clusters of this scale, licensed per node. Proactive alerting — thresholds and anomaly alerts catch power/thermal issues before they cause downtime. Multi-tenant — role-based dashboards per team. Integrations: Redfish/IPMI, PDU, CDU, Prometheus/Grafana. Validated with RDP infrastructure — delivered configured for your cluster. Make-in-India OEM — predictable INR pricing, GST tax invoice, pan-India support, GeM-procurable. What it does Monitoring (primary): collect health, power, thermal and utilisation telemetry across servers, PDUs and CDUs. Alerting: thresholds, anomaly detection and notifications. Capacity planning: trends and reports for capacity and energy planning. Dashboards: role-based dashboards and historical analytics. How it works Agents and standard protocols (Redfish/IPMI, SNMP, PDU/CDU APIs) feed a time-series database and dashboards; rules engine raises alerts and the analytics layer reports trends. RDP configures it for your cluster topology and integrates it with the RDP stack. Honest note: real utilisation/observability depends on workload mix and configuration — we tune it for your cluster. Industry use cases Neocloud / AI providers — operations visibility across a GPU cloud. Government & national labs — sovereign cluster monitoring. BFSI & enterprise — shared AI platforms with governance. Research & higher-ed — fair-share access to shared clusters. Manufacturing & energy — managed HPC + AI operations. Telecom — large-scale cluster operations. Outcomes — and how to be sure The outcome is fewe" }, { "type": "product", "title": "DRACO 128× H200 Modular Data Center", "url": "https://rdp.in/gpu-mart/product/draco-128x-h200-modular-data-center/", "sku": "615353", "text": "DRACO 128× H200 Modular Data Center. SKU 615353. 128× H200 · 64× Intel Xeon 6 · 16 TB DDR5 ECC · 2 PB NVMe · Modular multi-container data center · Integrated liquid (CDU) cooling + UPS . The DRACO 128× H200 Modular Data Center is a turnkey, modular AI data centre — 128× NVIDIA H200 SXM5 (18,048 GB HBM3e) across coupled containerized modules, pre-integrated with liquid cooling, UPS, power distribution, physical security and DCIM monitoring on a spine-leaf InfiniBand fabric. It stands up a full GPU data centre on a slab where there is no built facility — for sovereign programmes, neoclouds and large enterprises — and runs on-premises, in INR, on a GST invoice. Engineered to deploy data-centre-scale AI without constructing a building, it couples self-contained modules into one validated system — GPU servers, fabric, liquid cooling, power and monitoring — delivered, integrated and burned-in as a single engagement with one warranty and one support contract. Key highlights 128× H200 · 18,048 GB HBM3e — data-centre-scale AI capacity for training and inference, deployed on a slab. Modular, self-contained — coupled containerized modules with GPU servers, fabric, liquid cooling, UPS, PDU, security and monitoring. No building required — deploy where there is power and connectivity; expand by adding modules. 64× Intel Xeon 6 + 16 TB DDR5 ECC — host compute and memory matched to 128 GPUs. 2 PB NVMe NVMe + Spine-leaf InfiniBand NDR — large parallel storage and a non-blocking fabric for distributed training. DCIM remote monitoring + BMC/IPMI — full remote management of power, cooling, environment and compute. On-prem data sovereignty — data and models stay on site; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. AI workload fit (what it actually runs — honestly) Training & inference at scale: distributed training and high-throughput serving across the 128 H200 GPUs over the InfiniBand fabric. Large-model serving: serve 70B–180B-class models, or host many large models concurrently. Vision, multimodal & agentic: organisation-wide production AI co-located with operations. Engineering note: this is a data centre, not a single system — modular construction lets you stand up 128 GPUs of liquid-cooled, battery-backed capacity on a slab in months, not years. We validate real scaling on" }, { "type": "product", "title": "DRACO 64× H200 Containerized Micro Data Center", "url": "https://rdp.in/gpu-mart/product/draco-64x-h200-containerized-micro-data-center/", "sku": "411269", "text": "DRACO 64× H200 Containerized Micro Data Center. SKU 411269. 64× H200 · 32× Intel Xeon 6 · 8 TB DDR5 ECC · 960 TB NVMe · ISO-container (containerized) · Integrated liquid (CDU) cooling + UPS . The DRACO 64× H200 Containerized Micro Data Center is a turnkey, self-contained AI data centre — 64× NVIDIA H200 SXM5 (9,024 GB HBM3e) pre-integrated with integrated liquid (cdu) cooling, UPS, power distribution, physical security and remote monitoring in an ISO shipping container. It places real AI capacity where there is no built data centre — a campus, remote site — and runs private AI on-premises, in INR, on a GST invoice. Engineered to remove the need to build a server room, it bundles the GPU servers, networking, integrated liquid (cdu) cooling, battery backup and DCIM monitoring into one validated unit — delivered, integrated and burned-in as a single SKU with one warranty and one support contract. Key highlights 64× H200 · 9,024 GB HBM3e — real AI capacity for training and inference, anywhere. Self-contained container — GPU servers, networking, integrated liquid (cdu) cooling, UPS, PDU, fire suppression and security in one unit. No server room required — deploy with just site power and network. 32× Intel Xeon 6 + 8 TB DDR5 ECC — host compute and memory matched to 64 GPUs. 960 TB NVMe NVMe + InfiniBand NDR 400G — local storage and a low-latency fabric for distributed jobs. DCIM remote monitoring + BMC/IPMI — full remote management of power, cooling, environment and compute. On-prem data sovereignty — data and models stay at the site; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. AI workload fit (what it actually runs — honestly) Local training & inference (primary): train, fine-tune and serve large models at the site over the InfiniBand fabric. Large-model serving: serve 70B-class models across the enclosure. Vision, multimodal & agentic: production AI services co-located with operations. Engineering note: the H200 (141 GB HBM3e, NVLink) handles training-grade workloads; the enclosure provides liquid cooling and power so a full GPU cluster runs where there is no data centre. AI workload positioning This sits at the deploy-anywhere stage: a complete AI site in a container. With 9,024 GB HBM3e across 64 GPUs plus its own power and cooling, it is sized to sustain real l" }, { "type": "product", "title": "DRACO 32× H200 Micro Data Center Pod", "url": "https://rdp.in/gpu-mart/product/draco-32x-h200-micro-data-center-pod/", "sku": "224128", "text": "DRACO 32× H200 Micro Data Center Pod. SKU 224128. 32× H200 · 16× Intel Xeon 6 · 4 TB DDR5 ECC · 480 TB NVMe · Dual-rack self-contained enclosure · Integrated liquid (CDU) cooling + UPS . The DRACO 32× H200 Micro Data Center Pod is a turnkey, self-contained AI data centre — 32× NVIDIA H200 SXM5 (4,512 GB HBM3e) pre-integrated with integrated liquid (cdu) cooling, UPS, power distribution, physical security and remote monitoring in a sealed enclosure. It places real AI capacity where there is no built data centre — a campus, remote site — and runs private AI on-premises, in INR, on a GST invoice. Engineered to remove the need to build a server room, it bundles the GPU servers, networking, integrated liquid (cdu) cooling, battery backup and DCIM monitoring into one validated unit — delivered, integrated and burned-in as a single SKU with one warranty and one support contract. Key highlights 32× H200 · 4,512 GB HBM3e — real AI capacity for training and inference, anywhere. Self-contained enclosure — GPU servers, networking, integrated liquid (cdu) cooling, UPS, PDU, fire suppression and security in one unit. No server room required — deploy with just site power and network. 16× Intel Xeon 6 + 4 TB DDR5 ECC — host compute and memory matched to 32 GPUs. 480 TB NVMe NVMe + InfiniBand NDR 400G — local storage and a low-latency fabric for distributed jobs. DCIM remote monitoring + BMC/IPMI — full remote management of power, cooling, environment and compute. On-prem data sovereignty — data and models stay at the site; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. AI workload fit (what it actually runs — honestly) Local training & inference (primary): train, fine-tune and serve large models at the site over the InfiniBand fabric. Large-model serving: serve 70B-class models across the enclosure. Vision, multimodal & agentic: production AI services co-located with operations. Engineering note: the H200 (141 GB HBM3e, NVLink) handles training-grade workloads; the enclosure provides liquid cooling and power so a full GPU cluster runs where there is no data centre. AI workload positioning This sits at the deploy-anywhere stage: a complete AI site in a box. With 4,512 GB HBM3e across 32 GPUs plus its own power and cooling, it is sized to sustain real local AI where there is no da" }, { "type": "product", "title": "QUASAR 8× RTX PRO 6000 Blackwell Edge Micro Data Center", "url": "https://rdp.in/gpu-mart/product/quasar-8x-rtx-pro-6000-blackwell-edge-micro-data-center/", "sku": "729618", "text": "QUASAR 8× RTX PRO 6000 Blackwell Edge Micro Data Center. SKU 729618. 8× RTX PRO 6000 Blackwell · 4× Intel Xeon 6 · 1 TB DDR5 ECC · 160 TB NVMe · Ruggedized sealed edge enclosure · Integrated sealed cooling + UPS . The QUASAR 8× RTX PRO 6000 Blackwell Edge Micro Data Center is a turnkey, self-contained AI data centre — 8× RTX PRO 6000 Blackwell Server Edition (768 GB GDDR7) pre-integrated with integrated sealed cooling, UPS, power distribution, physical security and remote monitoring in a sealed enclosure. It places real AI capacity where there is no built data centre — a campus, remote site, or a harsh/outdoor environment — and runs private AI on-premises, in INR, on a GST invoice. Engineered to remove the need to build a server room, it bundles the GPU servers, networking, integrated sealed cooling, battery backup and DCIM monitoring into one validated unit — delivered, integrated and burned-in as a single SKU with one warranty and one support contract. Key highlights 8× RTX PRO 6000 Blackwell · 768 GB GDDR7 — real AI capacity for fine-tuning and inference, anywhere. Self-contained enclosure — GPU servers, networking, integrated sealed cooling, UPS, PDU, fire suppression and security in one unit. No server room required — deploy with just site power and network; sealed and ruggedized for harsh or outdoor sites. 4× Intel Xeon 6 + 1 TB DDR5 ECC — host compute and memory matched to 8 GPUs. 160 TB NVMe NVMe + 2× 25 GbE — local storage and high-throughput networking. DCIM remote monitoring + BMC/IPMI — full remote management of power, cooling, environment and compute. On-prem data sovereignty — data and models stay at the site; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. AI workload fit (what it actually runs — honestly) Local fine-tune & inference (primary): fine-tune and serve up to 70B-class models, and host many models, at the site. RAG & agentic: private on-site RAG and agent back-ends. Vision, multimodal & agentic: production AI services co-located with operations. Engineering note: the RTX PRO 6000 Blackwell Server Edition (96 GB GDDR7, PCIe, no NVLink) is sized for fine-tuning and serving up to 70B-class models data-parallel — not large-scale pre-training; the value is a sealed, self-cooled AI site you can place in harsh environments. AI workload positioni" }, { "type": "product", "title": "QUASAR 16× H200 Micro Data Center Pod", "url": "https://rdp.in/gpu-mart/product/quasar-16x-h200-micro-data-center-pod/", "sku": "639847", "text": "QUASAR 16× H200 Micro Data Center Pod. SKU 639847. 16× H200 · 8× Intel Xeon 6 · 2 TB DDR5 ECC · 240 TB NVMe · Single-rack self-contained enclosure · Integrated liquid-ready cooling + UPS . The QUASAR 16× H200 Micro Data Center Pod is a turnkey, self-contained AI data centre in an enclosure — 16× NVIDIA H200 SXM5 (2,256 GB HBM3e) pre-integrated with integrated liquid-ready cooling, UPS, power distribution, physical security and remote monitoring. It deploys AI compute where there is no built data centre: a factory, warehouse, branch, campus or remote site. You roll it in, connect power and network, and run private AI on-premises, in INR, on a GST invoice. Engineered to remove the need to build a server room, it bundles the GPU servers, networking, integrated liquid-ready cooling, battery backup and DCIM monitoring into one validated, lockable enclosure — delivered, integrated and burned-in as a single SKU with one warranty and one support contract. Key highlights 16× H200 · 2,256 GB HBM3e — real AI capacity for inference, training and fine-tuning, anywhere. Self-contained enclosure — GPU servers, networking, integrated liquid-ready cooling, UPS, PDU, fire suppression and physical security in one lockable unit. No server room required — deploy in a warehouse, campus, branch or remote site with just power and network. 8× Intel Xeon 6 + 2 TB DDR5 ECC — host compute and memory matched to 16 GPUs. 240 TB NVMe NVMe + InfiniBand NDR 400G — local storage and a low-latency fabric for distributed jobs. DCIM remote monitoring + BMC/IPMI — full remote management of power, cooling, environment and compute. On-prem data sovereignty — data and models stay at the site; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. AI workload fit (what it actually runs — honestly) Local training & inference: train, fine-tune and serve large models at the site over the InfiniBand fabric. Large-model serving: serve 70B-class models across the enclosure. Vision, multimodal & agentic: production AI services co-located with operations. Engineering note: this is infrastructure plus compute — the NVIDIA H200 SXM5 (141 GB HBM3e, NVLink) handles training-grade workloads. The value is a complete, self-cooled, battery-backed AI site you can place anywhere, not just the GPUs inside it. AI workload positioni" }, { "type": "product", "title": "QUASAR 16× L40S Micro Data Center Pod", "url": "https://rdp.in/gpu-mart/product/quasar-16x-l40s-micro-data-center-pod/", "sku": "839156", "text": "QUASAR 16× L40S Micro Data Center Pod. SKU 839156. 16× L40S · 8× Intel Xeon 6 · 2 TB DDR5 ECC · 160 TB NVMe · Single-rack self-contained enclosure · Integrated in-row cooling + UPS . The QUASAR 16× L40S Micro Data Center Pod is a turnkey, self-contained AI data centre in an enclosure — 16× NVIDIA L40S (768 GB GDDR6) pre-integrated with integrated in-row cooling, UPS, power distribution, physical security and remote monitoring. It deploys AI compute where there is no built data centre: a factory, warehouse, branch, campus or remote site. You roll it in, connect power and network, and run private AI on-premises, in INR, on a GST invoice. Engineered to remove the need to build a server room, it bundles the GPU servers, networking, integrated in-row cooling, battery backup and DCIM monitoring into one validated, lockable enclosure — delivered, integrated and burned-in as a single SKU with one warranty and one support contract. Key highlights 16× L40S · 768 GB GDDR6 — real AI capacity for inference and fine-tuning, anywhere. Self-contained enclosure — GPU servers, networking, integrated in-row cooling, UPS, PDU, fire suppression and physical security in one lockable unit. No server room required — deploy in a warehouse, campus, branch or remote site with just power and network. 8× Intel Xeon 6 + 2 TB DDR5 ECC — host compute and memory matched to 16 GPUs. 160 TB NVMe NVMe + 2× 25 GbE — local storage and high-throughput networking. DCIM remote monitoring + BMC/IPMI — full remote management of power, cooling, environment and compute. On-prem data sovereignty — data and models stay at the site; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. AI workload fit (what it actually runs — honestly) Local inference (primary): serve many models and run real-time vision at the site with low latency. Fine-tuning & RAG: QLoRA/LoRA fine-tuning and private on-site RAG. Vision, multimodal & agentic: production AI services co-located with operations. Engineering note: this is infrastructure plus compute — the NVIDIA L40S (48 GB, Ada inference) is sized for inference, fine-tuning and visualisation, not large-model pre-training. The value is a complete, self-cooled, battery-backed AI site you can place anywhere, not just the GPUs inside it. AI workload positioning This sits at the deploy-an" }, { "type": "product", "title": "DRACO 48U 100 kW Liquid-Ready AI Rack", "url": "https://rdp.in/gpu-mart/product/draco-48u-100-kw-liquid-ready-ai-rack/", "sku": "943025", "text": "DRACO 48U 100 kW Liquid-Ready AI Rack. SKU 943025. 100 kW per rack · 2N PDU (A/B feeds) · 415V 3-phase, busway · Liquid-ready (DLC manifold) · 48U high-density rack . The DRACO 48U 100 kW Liquid-Ready AI Rack is RDP’s flagship AI-ready rack — 100 kW per rack of capacity, 2N PDU (A/B feeds), busway distribution and direct-liquid-cooling provisioning, sized for the densest NVL-class GPU racks. It is the physical and power foundation the largest GPU deployments sit in, delivered integrated, cabled and validated with the compute it houses — on-premises, in INR, on a GST invoice. Engineered to match RDP’s rack-scale systems and superclusters, it provides the structure, high-current power, cable management and liquid-cooling readiness that the densest AI hardware needs, with metered, monitored A/B power feeds. Key highlights 100 kW per rack — flagship power density for NVL-class GPU racks. 2N PDU (A/B feeds) — 2N redundant, metered PDUs on A/B feeds for resilient power. 415V 3-phase, busway — busway-fed high-current distribution for the densest loads. 48U · 100 kW/rack — usable height and depth with structured cable management. Liquid-ready (DLC manifold) — manifold and rear-door provisioning for direct-liquid cooling. Per-outlet metering — visibility into power draw per server for capacity planning. Validated with RDP compute — delivered as part of a tested, powered rack. Make-in-India OEM — predictable INR pricing, GST tax invoice, pan-India onsite support, GeM-procurable. Where it fits High-density GPU racks (primary): houses and powers liquid-cooled, NVL-class GPU racks. Rack-scale building block: the cabinet and PDU layer of a supercluster. Liquid-cooled halls: pairs with RDP CDUs and direct-liquid cooling. Colocation: the densest AI-ready cabinets in shared halls. How it works The rack provides structure, liquid-cooling provisioning (manifold, rear-door) and cable routing for GPU servers; 2N metered PDUs distribute busway power on A/B feeds with per-outlet metering. RDP sizes the rack, power and cooling readiness to your server density and facility. Honest note: usable power per rack depends on your facility feed and cooling — we size and validate it for your room. Industry use cases AI data centres — house and power the densest GPU servers. Government & national labs — sovereign high-density AI infrastructure. Neocloud / hyperscale — maximum den" }, { "type": "product", "title": "DRACO 48U 80 kW Liquid-Ready AI Rack", "url": "https://rdp.in/gpu-mart/product/draco-48u-80-kw-liquid-ready-ai-rack/", "sku": "921280", "text": "DRACO 48U 80 kW Liquid-Ready AI Rack. SKU 921280. 80 kW per rack · 2N PDU (A/B feeds) · 415V 3-phase, busway · Liquid-ready (DLC manifold) · 48U high-density rack . The DRACO 48U 80 kW Liquid-Ready AI Rack is an AI-ready rack with intelligent power distribution — 80 kW per rack of capacity, 2N PDU (A/B feeds), and metered PDUs sized for the densest, liquid-cooled GPU servers. It is the physical and power foundation a GPU deployment sits in, delivered integrated, cabled and validated with the compute it houses — on-premises, in INR, on a GST invoice. Engineered to match RDP’s GPU servers and rack-scale systems, it provides the structure, power, cable management and liquid-cooling readiness that high-density liquid-cooled AI hardware needs, with metered, monitored power feeds. Key highlights 80 kW per rack — power capacity sized for the densest GPU racks (NVL-class). 2N PDU (A/B feeds) — redundant, metered PDUs on A/B feeds for resilient power. 415V 3-phase, busway — busway-fed high-current distribution for high-density loads. 48U · 80 kW/rack — usable height and depth with proper cable management. Liquid-ready (DLC manifold) — manifold and rear-door provisioning for direct-liquid cooling. Per-outlet metering — visibility into power draw per server for capacity planning. Validated with RDP compute — delivered as part of a tested, powered rack. Make-in-India OEM — predictable INR pricing, GST tax invoice, pan-India onsite support, GeM-procurable. Where it fits High-density GPU racks (primary): houses and powers liquid-cooled, NVL-class GPU racks. Rack-scale building block: the cabinet and PDU layer of a larger deployment. Liquid-cooled halls: pairs with RDP CDUs and direct-liquid cooling. Colocation: AI-ready cabinets in shared halls. How it works The rack provides structure, liquid-cooling provisioning (manifold, rear-door) and cable routing for GPU servers; redundant metered PDUs distribute 415V 3-phase, busway power on A/B feeds with per-outlet metering and monitoring. RDP sizes the rack, power and cooling readiness to your server density and facility. Honest note: usable power per rack depends on your facility feed and cooling — we size and validate it for your room. Industry use cases AI data centres — house and power the densest GPU servers. Government & PSU — sovereign AI infrastructure on GeM-procurable racks. BFSI & healthcare — compliant, metere" }, { "type": "product", "title": "DRACO 48U 60 kW High-Density AI Rack", "url": "https://rdp.in/gpu-mart/product/draco-48u-60-kw-high-density-ai-rack/", "sku": "490097", "text": "DRACO 48U 60 kW High-Density AI Rack. SKU 490097. 60 kW per rack · 2N PDU (A/B feeds) · 415V 3-phase, busway · Liquid-ready (rear-door/DLC) · 48U high-density rack . The DRACO 48U 60 kW High-Density AI Rack is an AI-ready rack with intelligent power distribution — 60 kW per rack of capacity, 2N PDU (A/B feeds), and metered PDUs sized for the densest, liquid-cooled GPU servers. It is the physical and power foundation a GPU deployment sits in, delivered integrated, cabled and validated with the compute it houses — on-premises, in INR, on a GST invoice. Engineered to match RDP’s GPU servers and rack-scale systems, it provides the structure, power, cable management and liquid-cooling readiness that high-density liquid-cooled AI hardware needs, with metered, monitored power feeds. Key highlights 60 kW per rack — power capacity sized for the densest GPU racks (NVL-class). 2N PDU (A/B feeds) — redundant, metered PDUs on A/B feeds for resilient power. 415V 3-phase, busway — busway-fed high-current distribution for high-density loads. 48U · 60 kW/rack — usable height and depth with proper cable management. Liquid-ready (rear-door/DLC) — manifold and rear-door provisioning for direct-liquid cooling. Per-outlet metering — visibility into power draw per server for capacity planning. Validated with RDP compute — delivered as part of a tested, powered rack. Make-in-India OEM — predictable INR pricing, GST tax invoice, pan-India onsite support, GeM-procurable. Where it fits High-density GPU racks (primary): houses and powers liquid-cooled, NVL-class GPU racks. Rack-scale building block: the cabinet and PDU layer of a larger deployment. Liquid-cooled halls: pairs with RDP CDUs and direct-liquid cooling. Colocation: AI-ready cabinets in shared halls. How it works The rack provides structure, liquid-cooling provisioning (manifold, rear-door) and cable routing for GPU servers; redundant metered PDUs distribute 415V 3-phase, busway power on A/B feeds with per-outlet metering and monitoring. RDP sizes the rack, power and cooling readiness to your server density and facility. Honest note: usable power per rack depends on your facility feed and cooling — we size and validate it for your room. Industry use cases AI data centres — house and power the densest GPU servers. Government & PSU — sovereign AI infrastructure on GeM-procurable racks. BFSI & healthcare — compliant, mete" }, { "type": "product", "title": "QUASAR 42U Edge Rack + PDU", "url": "https://rdp.in/gpu-mart/product/quasar-42u-edge-rack-pdu/", "sku": "214628", "text": "QUASAR 42U Edge Rack + PDU. SKU 214628. 15 kW per rack · N+1 PDU · 230/415V · Air (sealed option) · 42U short-depth/edge rack . The QUASAR 42U Edge Rack + PDU is an AI-ready rack with intelligent power distribution — 15 kW per rack of capacity, N+1 PDU, and metered PDUs sized for GPU servers at the edge. It is the physical and power foundation a GPU deployment sits in, delivered integrated, cabled and validated with the compute it houses — on-premises, in INR, on a GST invoice. Engineered to match RDP’s GPU servers and rack-scale systems, it provides the structure, power, cable management and airflow that dense AI hardware needs, with metered, monitored power feeds. Key highlights 15 kW per rack — power capacity sized for dense GPU servers, in a short-depth edge form. N+1 PDU — redundant, metered PDUs on A/B feeds for resilient power. 230/415V — the right distribution for AI rack loads. 42U short-depth · 15 kW/rack — usable height and depth with proper cable management. Air (sealed option) — airflow management, with a sealed option for harsh sites. Per-outlet metering — visibility into power draw per server for capacity planning. Validated with RDP compute — delivered as part of a tested, powered rack. Make-in-India OEM — predictable INR pricing, GST tax invoice, pan-India onsite support, GeM-procurable. Where it fits GPU server homes (primary): the rack and power that house and feed dense GPU servers at the edge. Rack-scale building block: the cabinet and PDU layer of a larger deployment. Retrofit or new build: standardise on AI-ready racks. Edge/micro-DC: the powered enclosure for a self-contained site. How it works The rack provides structure, airflow management and cable routing for GPU servers; redundant metered PDUs distribute 230/415V power on A/B feeds with per-outlet metering and monitoring. RDP sizes the rack, power and cooling readiness to your server density and facility. Honest note: usable power per rack depends on your facility feed and cooling — we size and validate it for your room. Industry use cases AI data centres — house and power dense GPU servers. Government & PSU — sovereign AI infrastructure on GeM-procurable racks. BFSI & healthcare — compliant, metered power for on-prem AI. Manufacturing & energy — well-powered racks near operations, sealed for harsh sites. Research & higher-ed — standardised racks for shared clusters. Neoclo" }, { "type": "product", "title": "QUASAR 42U 45 kW AI Rack + PDU", "url": "https://rdp.in/gpu-mart/product/quasar-42u-45-kw-ai-rack-pdu/", "sku": "589163", "text": "QUASAR 42U 45 kW AI Rack + PDU. SKU 589163. 45 kW per rack · N+1 PDU (A/B feeds) · 415V 3-phase, busway-ready · Air (rear-door ready) · 42U rack . The QUASAR 42U 45 kW AI Rack + PDU is an AI-ready rack with intelligent power distribution — 45 kW per rack of capacity, N+1 PDU (A/B feeds), and metered PDUs sized for dense GPU servers. It is the physical and power foundation a GPU deployment sits in, delivered integrated, cabled and validated with the compute it houses — on-premises, in INR, on a GST invoice. Engineered to match RDP’s GPU servers and rack-scale systems, it provides the structure, power, cable management and airflow that high-density AI hardware needs, with metered, monitored power feeds. Key highlights 45 kW per rack — power capacity sized for dense GPU servers, not a generic IT rack. N+1 PDU (A/B feeds) — redundant, metered PDUs on A/B feeds for resilient power. 415V 3-phase, busway-ready — the right distribution for AI rack loads. 42U · 45 kW/rack — usable height and depth for GPU servers with proper cable management. Air (rear-door ready) — airflow management (blanking, containment) and rear-door-ready for higher density. Per-outlet metering — visibility into power draw per server for capacity planning. Validated with RDP compute — delivered as part of a tested, powered rack. Make-in-India OEM — predictable INR pricing, GST tax invoice, pan-India onsite support, GeM-procurable. Where it fits GPU server homes (primary): the rack and power that house and feed dense GPU servers. Rack-scale building block: the cabinet and PDU layer of a larger deployment. Retrofit or new build: standardise on AI-ready racks across a room. Edge/micro-DC: the powered enclosure for a self-contained site. How it works The rack provides structure, airflow management and cable routing for GPU servers; redundant metered PDUs distribute 415V 3-phase, busway-ready power on A/B feeds with per-outlet metering and monitoring. RDP sizes the rack, power and airflow to your server density and facility. Honest note: usable power per rack depends on your facility feed and cooling — we size and validate it for your room. Industry use cases AI data centres — house and power dense GPU servers. Government & PSU — sovereign AI infrastructure on GeM-procurable racks. BFSI & healthcare — compliant, metered power for on-prem AI. Manufacturing & energy — rugged, well-powered racks" }, { "type": "product", "title": "QUASAR 42U 20 kW AI Rack + PDU", "url": "https://rdp.in/gpu-mart/product/quasar-42u-20-kw-ai-rack-pdu/", "sku": "151586", "text": "QUASAR 42U 20 kW AI Rack + PDU. SKU 151586. 20 kW per rack · N+1 PDU · 230/415V, single/3-phase · Air · 42U rack . The QUASAR 42U 20 kW AI Rack + PDU is an AI-ready rack with intelligent power distribution — 20 kW per rack of capacity, N+1 PDU, and metered PDUs sized for dense GPU servers. It is the physical and power foundation a GPU deployment sits in, delivered integrated, cabled and validated with the compute it houses — on-premises, in INR, on a GST invoice. Engineered to match RDP’s GPU servers and rack-scale systems, it provides the structure, power, cable management and airflow that high-density AI hardware needs, with metered, monitored power feeds. Key highlights 20 kW per rack — power capacity sized for dense GPU servers, not a generic IT rack. N+1 PDU — redundant, metered PDUs on A/B feeds for resilient power. 230/415V, single/3-phase — the right distribution for AI rack loads. 42U · 20 kW/rack — usable height and depth for GPU servers with proper cable management. Air — airflow management (blanking, containment) and rear-door-ready for higher density. Per-outlet metering — visibility into power draw per server for capacity planning. Validated with RDP compute — delivered as part of a tested, powered rack. Make-in-India OEM — predictable INR pricing, GST tax invoice, pan-India onsite support, GeM-procurable. Where it fits GPU server homes (primary): the rack and power that house and feed dense GPU servers. Rack-scale building block: the cabinet and PDU layer of a larger deployment. Retrofit or new build: standardise on AI-ready racks across a room. Edge/micro-DC: the powered enclosure for a self-contained site. How it works The rack provides structure, airflow management and cable routing for GPU servers; redundant metered PDUs distribute 230/415V, single/3-phase power on A/B feeds with per-outlet metering and monitoring. RDP sizes the rack, power and airflow to your server density and facility. Honest note: usable power per rack depends on your facility feed and cooling — we size and validate it for your room. Industry use cases AI data centres — house and power dense GPU servers. Government & PSU — sovereign AI infrastructure on GeM-procurable racks. BFSI & healthcare — compliant, metered power for on-prem AI. Manufacturing & energy — rugged, well-powered racks near operations. Research & higher-ed — standardised racks for shared clusters" }, { "type": "product", "title": "DRACO 128× H200 Multi-Node System", "url": "https://rdp.in/gpu-mart/product/draco-128x-h200-multi-node-system/", "sku": "131941", "text": "DRACO 128× H200 Multi-Node System. SKU 131941. 40-blade chassis · 80× Intel Xeon 6 (40 blades) · 40 TB DDR5 ECC · 640 TB NVMe · Quad Blade Chassis 32U · liquid-cooled . The DRACO 128× H200 Multi-Node System is a dense 40-blade chassis system that packs 128 NVIDIA H200 SXM5 GPUs (18,048 GB HBM3e) into one shared-infrastructure chassis with pooled power and liquid cooling. It consolidates large-scale training and high-throughput inference into one efficient, serviceable footprint on-premises, in INR, on a GST invoice. Engineered for platform teams who want training-grade density, it shares power, cooling and management across the blades, with NVLink inside each blade and a non-blocking InfiniBand fabric between them — delivered racked, cabled and validated as a single SKU with one warranty. Key highlights 128× H200 · 18,048 GB HBM3e — training-grade GPU density for distributed training and high-throughput inference. NVLink in-blade + non-blocking InfiniBand — efficient in-blade tensor parallelism and low-latency collectives across the system. 80× Intel Xeon 6 (40 blades) + 40 TB DDR5 ECC — host compute and memory matched to 128 data-centre GPUs. 640 TB NVMe NVMe + InfiniBand NDR 400G — fast local storage and a high-bandwidth fabric for multi-blade jobs. Liquid-cooled, hot-swap, serviceable — blade-level service, redundant shared PSUs, full BMC/IPMI. On-prem data sovereignty — training data and weights stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Scale path — add blades, or step up to rack-scale systems and SuperClusters. AI workload fit (what it actually runs — honestly) Distributed training (primary): train and fine-tune large models across the NVLink-connected blades, scaling over the InfiniBand fabric. Large-model serving: shard the largest models across blades, or host many large models concurrently at density. RAG, vision, multimodal & agentic: dense production AI services and multi-agent back-ends. Engineering note: each blade’s H200 GPUs are NVLink-connected for efficient in-blade tensor parallelism, and blades scale over a non-blocking InfiniBand fabric — this system trains and serves large models at density. The strength is training-grade GPU density in one serviceable chassis. AI workload positioning This sits at the train-and-serve" }, { "type": "product", "title": "DRACO 32× B200 Multi-Node System", "url": "https://rdp.in/gpu-mart/product/draco-32x-b200-multi-node-system/", "sku": "489466", "text": "DRACO 32× B200 Multi-Node System. SKU 489466. 8-node twin block · 16× Intel Xeon 6 (8 nodes) · 8 TB DDR5 ECC · 160 TB NVMe · Twin Compute Block 8U · liquid-cooled . The DRACO 32× B200 Multi-Node System is a dense 8-node twin block system that packs 32 NVIDIA B200 SXM GPUs (5,760 GB HBM3e) into one shared-infrastructure chassis with pooled power and liquid cooling. It consolidates large-scale training and high-throughput inference into one efficient, serviceable footprint on-premises, in INR, on a GST invoice. Engineered for platform teams who want training-grade density, it shares power, cooling and management across the nodes, with NVLink inside each node and a non-blocking InfiniBand fabric between them — delivered racked, cabled and validated as a single SKU with one warranty. Key highlights 32× B200 · 5,760 GB HBM3e — training-grade GPU density for distributed training and high-throughput inference. NVLink in-node + non-blocking InfiniBand — efficient in-node tensor parallelism and low-latency collectives across the system. 16× Intel Xeon 6 (8 nodes) + 8 TB DDR5 ECC — host compute and memory matched to 32 data-centre GPUs. 160 TB NVMe NVMe + InfiniBand NDR 400G — fast local storage and a high-bandwidth fabric for multi-node jobs. Liquid-cooled, hot-swap, serviceable — node-level service, redundant shared PSUs, full BMC/IPMI. On-prem data sovereignty — training data and weights stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Scale path — add nodes, or step up to rack-scale systems and SuperClusters. AI workload fit (what it actually runs — honestly) Distributed training (primary): train and fine-tune large models across the NVLink-connected nodes, scaling over the InfiniBand fabric. Large-model serving: shard the largest models across nodes, or host many large models concurrently at density. RAG, vision, multimodal & agentic: dense production AI services and multi-agent back-ends. Engineering note: each node’s B200 GPUs are NVLink-connected for efficient in-node tensor parallelism, and nodes scale over a non-blocking InfiniBand fabric — this system trains and serves large models at density. The strength is training-grade GPU density in one serviceable chassis. AI workload positioning This sits at the train-and-serve at density stage: a dens" }, { "type": "product", "title": "DRACO 64× H200 Multi-Node System", "url": "https://rdp.in/gpu-mart/product/draco-64x-h200-multi-node-system/", "sku": "571974", "text": "DRACO 64× H200 Multi-Node System. SKU 571974. 16-blade chassis · 32× Intel Xeon 6 (16 blades) · 16 TB DDR5 ECC · 320 TB NVMe · Dual Blade Chassis 16U · liquid-cooled . The DRACO 64× H200 Multi-Node System is a dense 16-blade chassis system that packs 64 NVIDIA H200 SXM5 GPUs (9,024 GB HBM3e) into one shared-infrastructure chassis with pooled power and liquid cooling. It consolidates large-scale training and high-throughput inference into one efficient, serviceable footprint on-premises, in INR, on a GST invoice. Engineered for platform teams who want training-grade density, it shares power, cooling and management across the blades, with NVLink inside each blade and a non-blocking InfiniBand fabric between them — delivered racked, cabled and validated as a single SKU with one warranty. Key highlights 64× H200 · 9,024 GB HBM3e — training-grade GPU density for distributed training and high-throughput inference. NVLink in-blade + non-blocking InfiniBand — efficient in-blade tensor parallelism and low-latency collectives across the system. 32× Intel Xeon 6 (16 blades) + 16 TB DDR5 ECC — host compute and memory matched to 64 data-centre GPUs. 320 TB NVMe NVMe + InfiniBand NDR 400G — fast local storage and a high-bandwidth fabric for multi-blade jobs. Liquid-cooled, hot-swap, serviceable — blade-level service, redundant shared PSUs, full BMC/IPMI. On-prem data sovereignty — training data and weights stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Scale path — add blades, or step up to rack-scale systems and SuperClusters. AI workload fit (what it actually runs — honestly) Distributed training (primary): train and fine-tune large models across the NVLink-connected blades, scaling over the InfiniBand fabric. Large-model serving: shard the largest models across blades, or host many large models concurrently at density. RAG, vision, multimodal & agentic: dense production AI services and multi-agent back-ends. Engineering note: each blade’s H200 GPUs are NVLink-connected for efficient in-blade tensor parallelism, and blades scale over a non-blocking InfiniBand fabric — this system trains and serves large models at density. The strength is training-grade GPU density in one serviceable chassis. AI workload positioning This sits at the train-and-serve at den" }, { "type": "product", "title": "QUASAR 16× RTX PRO 6000 Blackwell Edge Multi-Node System", "url": "https://rdp.in/gpu-mart/product/quasar-16x-rtx-pro-6000-blackwell-edge-multi-node-system/", "sku": "389260", "text": "QUASAR 16× RTX PRO 6000 Blackwell Edge Multi-Node System. SKU 389260. 4-blade edge chassis · 8× Intel Xeon 6 (4 blades) · 4 TB DDR5 ECC · 64 TB NVMe · Edge Blade Chassis 4U short-depth · shared power & cooling . The QUASAR 16× RTX PRO 6000 Blackwell Edge Multi-Node System is a dense 4-blade edge chassis system that packs 16 RTX PRO 6000 Blackwell Server Edition GPUs (1,536 GB GDDR7) into one shared-infrastructure chassis with pooled power and cooling in a short-depth chassis sized for edge and telco racks. It consolidates many inference and fine-tune workloads into one efficient footprint on-premises, in INR, on a GST invoice. Engineered for platform teams who want density and serviceability, it shares power supplies, cooling and management across the blades, so you deploy more GPUs per rack-U with one management plane — delivered racked, cabled and validated as a single SKU with one warranty. Key highlights 16× RTX PRO 6000 Blackwell · 1,536 GB GDDR7 — high GPU density for consolidated inference, fine-tuning and small-scale training. 4-blade edge chassis, shared power & cooling — more GPUs per rack-U with pooled PSUs and a single management plane; short-depth for edge/telco racks. 8× Intel Xeon 6 (4 blades) + 4 TB DDR5 ECC — host compute and memory matched to 16 GPUs. 64 TB NVMe NVMe + 2× 25 GbE — fast local storage and high-throughput networking. Hot-swap, serviceable — blade-level service, redundant shared PSUs, full BMC/IPMI. On-prem data sovereignty — data and models stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Scale path — add blades, or step up to rack-scale systems and SuperClusters. AI workload fit (what it actually runs — honestly) Consolidated inference (primary): host many models across 16 GPUs for high aggregate throughput with one management plane. Fine-tuning & small-scale training: data-parallel fine-tuning across blades. RAG, vision, multimodal & agentic: dense production AI services and multi-agent back-ends. Engineering note: the RTX PRO 6000 Blackwell Server Edition is a PCIe card with no NVLink ; GPUs excel at data-parallel serving and multi-instance hosting. For tightly-coupled large-model training, choose an SXM/NVLink rack-scale system. AI workload positioning This sits at the consolidate-and-serve stage: a density play th" }, { "type": "product", "title": "DRACO 32× H200 Multi-Node System", "url": "https://rdp.in/gpu-mart/product/draco-32x-h200-multi-node-system/", "sku": "838688", "text": "DRACO 32× H200 Multi-Node System. SKU 838688. 8-blade chassis · 16× Intel Xeon 6 (8 blades) · 8 TB DDR5 ECC · 160 TB NVMe · Blade Chassis 8U · shared power & cooling . The DRACO 32× H200 Multi-Node System is a dense 8-blade chassis system that packs 32 NVIDIA H200 SXM5 GPUs (4,512 GB HBM3e) into one shared-infrastructure chassis with pooled power and cooling. It consolidates many training and inference workloads into one efficient footprint on-premises, in INR, on a GST invoice. Engineered for platform teams who want density and serviceability, it shares power supplies, cooling and management across the blades, so you deploy more GPUs per rack-U with one management plane — delivered racked, cabled and validated as a single SKU with one warranty. Key highlights 32× H200 · 4,512 GB HBM3e — high GPU density for distributed training and high-throughput inference. 8-blade chassis, shared power & cooling — more GPUs per rack-U with pooled PSUs and a single management plane. 16× Intel Xeon 6 (8 blades) + 8 TB DDR5 ECC — host compute and memory matched to 32 GPUs. 160 TB NVMe NVMe + InfiniBand NDR 400G — fast local storage and a low-latency InfiniBand fabric for multi-blade jobs. Hot-swap, serviceable — blade-level service, redundant shared PSUs, full BMC/IPMI. On-prem data sovereignty — data and models stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Scale path — add blades, or step up to rack-scale systems and SuperClusters. AI workload fit (what it actually runs — honestly) Distributed training & inference: train and fine-tune large models across the NVLink-connected blades, and serve them at high throughput. Large-model serving: shard the largest models across blades over the InfiniBand fabric. RAG, vision, multimodal & agentic: dense production AI services and multi-agent back-ends. Engineering note: each blade’s H200 GPUs are NVLink-connected for efficient in-node tensor parallelism, and blades scale over the InfiniBand fabric — this system trains and serves large models at density. AI workload positioning This sits at the train-and-serve at density stage: a density play that puts many GPUs in one serviceable chassis. With 4,512 GB HBM3e across 32 GPUs, it is sized to sustain distributed training and large-scale serving in one footprint — more ef" }, { "type": "product", "title": "DRACO 80× RTX PRO 6000 Blackwell Multi-Node System", "url": "https://rdp.in/gpu-mart/product/draco-80x-rtx-pro-6000-blackwell-multi-node-system/", "sku": "417464", "text": "DRACO 80× RTX PRO 6000 Blackwell Multi-Node System. SKU 417464. 20-blade chassis · 40× Intel Xeon 6 (20 blades) · 20 TB DDR5 ECC · 320 TB NVMe · Dual Blade Chassis 16U · shared power & cooling . The DRACO 80× RTX PRO 6000 Blackwell Multi-Node System is a dense 20-blade chassis system that packs 80 RTX PRO 6000 Blackwell Server Edition GPUs (7,680 GB GDDR7) into one shared-infrastructure chassis with pooled power and cooling. It consolidates many inference and fine-tune workloads into one efficient footprint on-premises, in INR, on a GST invoice. Engineered for platform teams who want density and serviceability, it shares power supplies, cooling and management across the blades, so you deploy more GPUs per rack-U with one management plane — delivered racked, cabled and validated as a single SKU with one warranty. Key highlights 80× RTX PRO 6000 Blackwell · 7,680 GB GDDR7 — high GPU density for consolidated inference, fine-tuning and small-scale training. 20-blade chassis, shared power & cooling — more GPUs per rack-U with pooled PSUs and a single management plane. 40× Intel Xeon 6 (20 blades) + 20 TB DDR5 ECC — host compute and memory matched to 80 GPUs. 320 TB NVMe NVMe + InfiniBand NDR 400G — fast local storage and a low-latency InfiniBand fabric for multi-blade jobs. Hot-swap, serviceable — blade-level service, redundant shared PSUs, full BMC/IPMI. On-prem data sovereignty — data and models stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Scale path — add blades, or step up to rack-scale systems and SuperClusters. AI workload fit (what it actually runs — honestly) Consolidated inference (primary): host many models across 80 GPUs for high aggregate throughput with one management plane. Fine-tuning & small-scale training: data-parallel fine-tuning across blades. RAG, vision, multimodal & agentic: dense production AI services and multi-agent back-ends. Engineering note: the RTX PRO 6000 Blackwell Server Edition is a PCIe card with no NVLink ; GPUs excel at data-parallel serving and multi-instance hosting. Across blades, the InfiniBand fabric carries collective traffic for distributed jobs. AI workload positioning This sits at the consolidate-and-serve stage: a density play that puts many GPUs in one serviceable chassis. With 7,680 GB GDDR7 across 80 G" }, { "type": "product", "title": "DRACO 2.5 MW Facility CDU", "url": "https://rdp.in/gpu-mart/product/draco-2-5-mw-facility-cdu/", "sku": "303576", "text": "DRACO 2.5 MW Facility CDU. SKU 303576. 2.5 MW · Up to 4,000 L/min · Liquid-to-liquid facility CDU · PG25 / treated water · Facility CDU (floor-standing, N+1) . The DRACO 2.5 MW Facility CDU is RDP’s flagship coolant distribution unit — 2.5 MW of heat removal that cools a full row-zone or a data-hall block of dense GPU racks. It is the facility-scale thermal backbone that makes the largest on-premises AI deployments possible, in INR, on a GST invoice. Engineered to match RDP’s rack-scale systems, superclusters and supercomputers, it isolates the rack coolant loops from facility water, controls flow, temperature and pressure, filters the coolant, and distributes it across many racks with N+1 pumping — delivered sized, plumbed and commissioned with the compute it cools, with leak detection and monitoring built in. Key highlights 2.5 MW · Up to 4,000 L/min — facility-scale heat removal for Up to 24 dense racks / a row-zone. Liquid-to-liquid facility CDU — isolates rack coolant from facility water; controls flow, temperature and pressure with filtration at scale. PG25 / treated water — corrosion-safe coolant chemistry for reliable long-term operation. N+1 redundant pumps — continuous cooling during maintenance and failures. Leak detection & monitoring — sensors and BMS/DCIM integration for safe, observable operation at scale. Efficient, low PUE — liquid removes heat far more efficiently than air across the hall. Validated with RDP compute — delivered as part of a tested, cooled data hall. Make-in-India OEM — predictable INR pricing, GST tax invoice, pan-India onsite support, GeM-procurable. Where it fits Data-hall cooling (primary): distributes coolant to direct-to-chip loops across Up to 24 dense racks / a row-zone. Superclusters & supercomputers: the cooling backbone for halls of NVL72-class racks. New liquid-cooled facilities: the facility CDU layer between the racks and the building’s water loop. Scale-up cooling: add CDUs as the data hall grows. How it works The facility CDU forms a closed technology-cooling-system (TCS) loop to many racks, rejecting heat to the building water loop through large heat exchangers. It controls flow, supply temperature and pressure, filters and treats the coolant, and provides N+1 pumping for continuous operation. RDP sizes the CDU, loops and connections to your hall density and facility water conditions. Hones" }, { "type": "product", "title": "DRACO 1.2 MW Row CDU", "url": "https://rdp.in/gpu-mart/product/draco-1-2-mw-row-cdu/", "sku": "533244", "text": "DRACO 1.2 MW Row CDU. SKU 533244. 1.2 MW · Up to 2,000 L/min · Liquid-to-liquid row CDU · PG25 / treated water · Row CDU (floor-standing) . The DRACO 1.2 MW Row CDU is a high-capacity coolant distribution unit that cools a row of dense GPU racks — 1.2 MW of heat removal via liquid-to-liquid row cdu, so racks of 700 W–1 kW+ GPUs run at full clocks. It is the thermal backbone that makes high-density AI deployments possible on-premises, in INR, on a GST invoice. Engineered to match RDP’s rack-scale systems and superclusters, it isolates the rack coolant loop from facility water, controls flow, temperature and pressure, filters the coolant, and distributes it to the cold-plate loops — delivered sized, plumbed and validated with the compute it cools, with leak detection and monitoring built in. Key highlights 1.2 MW · Up to 2,000 L/min — row-scale heat removal for Up to 12 dense racks. Liquid-to-liquid row CDU — isolates rack coolant from facility water; controls flow, temperature and pressure with filtration. PG25 / treated water — corrosion-safe coolant chemistry for reliable long-term operation. Redundant pumps — N+1 pumping for continuous cooling during maintenance. Leak detection & monitoring — sensors and BMS/DCIM integration for safe, observable operation. Efficient, low PUE — liquid moves heat far more efficiently than air, lowering fan power and energy cost. Validated with RDP compute — delivered as part of a tested, cooled deployment. Make-in-India OEM — predictable INR pricing, GST tax invoice, pan-India onsite support, GeM-procurable. Where it fits Dense GPU rows (primary): distributes coolant to direct-to-chip cold-plate loops across Up to 12 dense racks. Rack-scale & NVL systems: the cooling that keeps rows of NVL72-class racks within thermal limits. New liquid-cooled halls: the row/zone CDU layer between racks and facility water. Scale-up cooling: add CDUs as rows and density grow. How it works The CDU forms a closed technology-cooling-system (TCS) loop to the racks, rejecting heat to the facility water loop through a heat exchanger. It controls flow, supply temperature and pressure, filters and treats the coolant, and provides redundant pumping. RDP sizes the CDU, loop and connections to your row density and facility water conditions. Honest note: real cooling capacity depends on inlet water temperature, flow and rack layout — we size and va" }, { "type": "product", "title": "DRACO 700 kW In-Row CDU", "url": "https://rdp.in/gpu-mart/product/draco-700-kw-in-row-cdu/", "sku": "117261", "text": "DRACO 700 kW In-Row CDU. SKU 117261. 700 kW · Up to 1,100 L/min · Liquid-to-liquid CDU (in-row) · PG25 / treated water · In-row (full-height) . The DRACO 700 kW In-Row CDU is a high-capacity coolant distribution unit that cools a row of dense GPU racks — 700 kW of heat removal via liquid-to-liquid cdu (in-row), so racks of 700 W–1 kW+ GPUs run at full clocks. It is the thermal backbone that makes high-density AI deployments possible on-premises, in INR, on a GST invoice. Engineered to match RDP’s rack-scale systems and superclusters, it isolates the rack coolant loop from facility water, controls flow, temperature and pressure, filters the coolant, and distributes it to the cold-plate loops — delivered sized, plumbed and validated with the compute it cools, with leak detection and monitoring built in. Key highlights 700 kW · Up to 1,100 L/min — row-scale heat removal for Up to 6 dense racks. Liquid-to-liquid CDU (in-row) — isolates rack coolant from facility water; controls flow, temperature and pressure with filtration. PG25 / treated water — corrosion-safe coolant chemistry for reliable long-term operation. Redundant pumps — N+1 pumping for continuous cooling during maintenance. Leak detection & monitoring — sensors and BMS/DCIM integration for safe, observable operation. Efficient, low PUE — liquid moves heat far more efficiently than air, lowering fan power and energy cost. Validated with RDP compute — delivered as part of a tested, cooled deployment. Make-in-India OEM — predictable INR pricing, GST tax invoice, pan-India onsite support, GeM-procurable. Where it fits Dense GPU rows (primary): distributes coolant to direct-to-chip cold-plate loops across Up to 6 dense racks. Rack-scale & NVL systems: the cooling that keeps rows of NVL72-class racks within thermal limits. New liquid-cooled halls: the row/zone CDU layer between racks and facility water. Scale-up cooling: add CDUs as rows and density grow. How it works The CDU forms a closed technology-cooling-system (TCS) loop to the racks, rejecting heat to the facility water loop through a heat exchanger. It controls flow, supply temperature and pressure, filters and treats the coolant, and provides redundant pumping. RDP sizes the CDU, loop and connections to your row density and facility water conditions. Honest note: real cooling capacity depends on inlet water temperature, flow and rack layout —" }, { "type": "product", "title": "QUASAR Sealed Edge Liquid Cooling Kit", "url": "https://rdp.in/gpu-mart/product/quasar-sealed-edge-liquid-cooling-kit/", "sku": "215530", "text": "QUASAR Sealed Edge Liquid Cooling Kit. SKU 215530. Up to 40 kW · Closed-loop · Sealed closed-loop (edge) · Dielectric / PG25 · Sealed enclosure . The QUASAR Sealed Edge Liquid Cooling Kit removes the heat that dense GPU racks generate — Up to 40 kW of cooling via sealed closed-loop (edge), so today’s 700 W–1 kW+ GPUs run at full clocks without thermal throttling. It is the thermal layer that makes high-density AI racks possible on-premises, in INR, on a GST invoice. Engineered to match RDP’s GPU servers, rack-scale systems and superclusters, it integrates with your facility water or runs closed-loop, and is delivered sized, plumbed and validated with the compute it cools — with leak detection and monitoring built in. Key highlights Up to 40 kW — direct-to-chip cooling for the hottest GPUs and CPUs. Sealed closed-loop (edge) — cold plates sit directly on the silicon, the most efficient way to cool 1 kW GPUs. Closed-loop · Dielectric / PG25 — controlled flow and coolant chemistry for reliable, corrosion-safe operation. Leak detection & monitoring — sensors and BMS/DCIM integration for safe, observable operation. Supports 1 edge rack — sized to the density of RDP GPU racks. Quiet, efficient — liquid moves heat far more efficiently than air, lowering fan power and PUE. Validated with RDP compute — delivered as part of a tested, cooled rack. Make-in-India OEM — predictable INR pricing, GST tax invoice, pan-India onsite support, GeM-procurable. Where it fits Dense GPU racks (primary): cools the GPUs/CPUs directly in liquid-cooled servers. Rack-scale & NVL systems: the cooling that keeps NVL72-class racks within thermal limits. Retrofit or new build: design a liquid-cooled hall, or add density to a room. Edge/micro-DC: sealed/compact options for self-contained sites. How it works Cold plates mounted on the GPUs and CPUs carry heat into a coolant loop via quick-disconnects and a manifold; the loop rejects heat to a CDU, facility water, or a sealed closed-loop dry-cooler at the edge. RDP sizes the loop, flow and coolant to your rack density and facility. Honest note: real cooling capacity depends on inlet water temperature, flow and rack layout — we size and validate it for your room. Industry use cases AI data centres — cool dense GPU and NVL racks at full clocks. Government & national labs — sovereign HPC/AI cooling. Neocloud / AI providers — higher den" }, { "type": "product", "title": "DRACO 500 kW In-Row CDU", "url": "https://rdp.in/gpu-mart/product/draco-500-kw-in-row-cdu/", "sku": "160225", "text": "DRACO 500 kW In-Row CDU. SKU 160225. 500 kW · Up to 800 L/min · Liquid-to-liquid CDU (in-row) · PG25 / treated water · In-row (full-height) . The DRACO 500 kW In-Row CDU is a high-capacity coolant distribution unit that cools a row of dense GPU racks — 500 kW of heat removal via liquid-to-liquid cdu (in-row), so racks of 700 W–1 kW+ GPUs run at full clocks. It is the thermal backbone that makes high-density AI deployments possible on-premises, in INR, on a GST invoice. Engineered to match RDP’s rack-scale systems and superclusters, it isolates the rack coolant loop from facility water, controls flow, temperature and pressure, filters the coolant, and distributes it to the cold-plate loops — delivered sized, plumbed and validated with the compute it cools, with leak detection and monitoring built in. Key highlights 500 kW · Up to 800 L/min — row-scale heat removal for Up to 4 dense racks. Liquid-to-liquid CDU (in-row) — isolates rack coolant from facility water; controls flow, temperature and pressure with filtration. PG25 / treated water — corrosion-safe coolant chemistry for reliable long-term operation. Redundant pumps — N+1 pumping for continuous cooling during maintenance. Leak detection & monitoring — sensors and BMS/DCIM integration for safe, observable operation. Efficient, low PUE — liquid moves heat far more efficiently than air, lowering fan power and energy cost. Validated with RDP compute — delivered as part of a tested, cooled deployment. Make-in-India OEM — predictable INR pricing, GST tax invoice, pan-India onsite support, GeM-procurable. Where it fits Dense GPU rows (primary): distributes coolant to direct-to-chip cold-plate loops across Up to 4 dense racks. Rack-scale & NVL systems: the cooling that keeps rows of NVL72-class racks within thermal limits. New liquid-cooled halls: the row/zone CDU layer between racks and facility water. Scale-up cooling: add CDUs as rows and density grow. How it works The CDU forms a closed technology-cooling-system (TCS) loop to the racks, rejecting heat to the facility water loop through a heat exchanger. It controls flow, supply temperature and pressure, filters and treats the coolant, and provides redundant pumping. RDP sizes the CDU, loop and connections to your row density and facility water conditions. Honest note: real cooling capacity depends on inlet water temperature, flow and rack layout — we" }, { "type": "product", "title": "QUASAR 50 kW Direct-Liquid Cooling Kit", "url": "https://rdp.in/gpu-mart/product/quasar-50-kw-direct-liquid-cooling-kit/", "sku": "394244", "text": "QUASAR 50 kW Direct-Liquid Cooling Kit. SKU 394244. Up to 50 kW (cold-plate) · Manifold-fed (quick-disconnect) · Direct-to-chip cold plates + manifold · PG25 / treated water · In-rack manifold + cold plates . The QUASAR 50 kW Direct-Liquid Cooling Kit removes the heat that dense GPU racks generate — Up to 50 kW (cold-plate) of cooling via direct-to-chip cold plates + manifold, so today’s 700 W–1 kW+ GPUs run at full clocks without thermal throttling. It is the thermal layer that makes high-density AI racks possible on-premises, in INR, on a GST invoice. Engineered to match RDP’s GPU servers, rack-scale systems and superclusters, it integrates with your facility water or runs closed-loop, and is delivered sized, plumbed and validated with the compute it cools — with leak detection and monitoring built in. Key highlights Up to 50 kW (cold-plate) — direct-to-chip cooling for the hottest GPUs and CPUs. Direct-to-chip cold plates + manifold — cold plates sit directly on the silicon, the most efficient way to cool 1 kW GPUs. Manifold-fed (quick-disconnect) · PG25 / treated water — controlled flow and coolant chemistry for reliable, corrosion-safe operation. Leak detection & monitoring — sensors and BMS/DCIM integration for safe, observable operation. Supports 1 rack — sized to the density of RDP GPU racks. Quiet, efficient — liquid moves heat far more efficiently than air, lowering fan power and PUE. Validated with RDP compute — delivered as part of a tested, cooled rack. Make-in-India OEM — predictable INR pricing, GST tax invoice, pan-India onsite support, GeM-procurable. Where it fits Dense GPU racks (primary): cools the GPUs/CPUs directly in liquid-cooled servers. Rack-scale & NVL systems: the cooling that keeps NVL72-class racks within thermal limits. Retrofit or new build: design a liquid-cooled hall, or add density to a room. Edge/micro-DC: sealed/compact options for self-contained sites. How it works Cold plates mounted on the GPUs and CPUs carry heat into a coolant loop via quick-disconnects and a manifold; the loop rejects heat to a CDU, facility water, or a dry-cooler. RDP sizes the loop, flow and coolant to your rack density and facility. Honest note: real cooling capacity depends on inlet water temperature, flow and rack layout — we size and validate it for your room. Industry use cases AI data centres — cool dense GPU and NVL racks at ful" }, { "type": "product", "title": "DRACO 8 PB Parallel-FS NVMe AI Storage", "url": "https://rdp.in/gpu-mart/product/draco-8-pb-parallel-fs-nvme-ai-storage/", "sku": "522027", "text": "DRACO 8 PB Parallel-FS NVMe AI Storage. SKU 522027. 8 PB usable (NVMe) · 4.8 TB/s read · Parallel FS (Lustre/GPFS-class) · 128× 400G InfiniBand/Ethernet · Multi-rack (32-node) . The DRACO 8 PB Parallel-FS NVMe AI Storage is a large scale-out parallel-filesystem NVMe storage system built to feed entire GPU superclusters during the largest AI training runs. It delivers 8 PB usable (NVMe) at 4.8 TB/s read with GPUDirect Storage across a clustered namespace, so datasets, checkpoints and weights stream to hundreds of GPU nodes in parallel without the storage becoming the bottleneck — on-premises, in INR, on a GST invoice. Engineered for supercluster-scale AI/HPC data pipelines, it presents a single parallel namespace over high-speed networking and scales capacity and bandwidth together by adding nodes — delivered racked, configured and validated as one system with one warranty and one support contract. Key highlights 8 PB usable (NVMe) · 4.8 TB/s read — supercluster-scale bandwidth sized to feed hundreds of GPU nodes. Parallel filesystem + GPUDirect Storage — a single namespace; data streams from NVMe straight to GPU memory across the cluster. Parallel FS (Lustre/GPFS-class) + NFS/S3, GPUDirect Storage — parallel and standard protocols so existing pipelines and schedulers just work. 768× 15.36 TB NVMe (32 nodes) — dense enterprise NVMe with end-to-end data integrity, scaling across nodes. 128× 400G InfiniBand/Ethernet — very high aggregate bandwidth to the GPU fabric; bandwidth grows with capacity. 320M random read — high aggregate random-read IOPS for metadata- and small-file-heavy datasets. On-prem data sovereignty — datasets and weights stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Where it fits Supercluster training data lake (primary): streams datasets to a large GPU cluster in parallel without starving any node. Checkpoints & weights: fast parallel write/read of very large checkpoints during long runs. RAG & vector stores: low-latency storage for very large embeddings and indexes. HPC scratch: high-throughput scratch for large simulation alongside AI. How it works A clustered parallel filesystem stripes data across many NVMe nodes and presents one namespace over 128× 400G InfiniBand/Ethernet. With GPUDirect Storage, reads bypass the CPU and land" }, { "type": "product", "title": "DRACO 4 PB Parallel-FS NVMe AI Storage", "url": "https://rdp.in/gpu-mart/product/draco-4-pb-parallel-fs-nvme-ai-storage/", "sku": "731615", "text": "DRACO 4 PB Parallel-FS NVMe AI Storage. SKU 731615. 4 PB usable (NVMe) · 2.4 TB/s read · Parallel FS (Lustre/GPFS-class) · 64× 400G InfiniBand/Ethernet · 32U (16-node) . The DRACO 4 PB Parallel-FS NVMe AI Storage is a large scale-out parallel-filesystem NVMe storage system built to feed entire GPU superclusters during the largest AI training runs. It delivers 4 PB usable (NVMe) at 2.4 TB/s read with GPUDirect Storage across a clustered namespace, so datasets, checkpoints and weights stream to hundreds of GPU nodes in parallel without the storage becoming the bottleneck — on-premises, in INR, on a GST invoice. Engineered for supercluster-scale AI/HPC data pipelines, it presents a single parallel namespace over high-speed networking and scales capacity and bandwidth together by adding nodes — delivered racked, configured and validated as one system with one warranty and one support contract. Key highlights 4 PB usable (NVMe) · 2.4 TB/s read — supercluster-scale bandwidth sized to feed hundreds of GPU nodes. Parallel filesystem + GPUDirect Storage — a single namespace; data streams from NVMe straight to GPU memory across the cluster. Parallel FS (Lustre/GPFS-class) + NFS/S3, GPUDirect Storage — parallel and standard protocols so existing pipelines and schedulers just work. 384× 15.36 TB NVMe (16 nodes) — dense enterprise NVMe with end-to-end data integrity, scaling across nodes. 64× 400G InfiniBand/Ethernet — very high aggregate bandwidth to the GPU fabric; bandwidth grows with capacity. 160M random read — high aggregate random-read IOPS for metadata- and small-file-heavy datasets. On-prem data sovereignty — datasets and weights stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Where it fits Supercluster training data lake (primary): streams datasets to a large GPU cluster in parallel without starving any node. Checkpoints & weights: fast parallel write/read of very large checkpoints during long runs. RAG & vector stores: low-latency storage for very large embeddings and indexes. HPC scratch: high-throughput scratch for large simulation alongside AI. How it works A clustered parallel filesystem stripes data across many NVMe nodes and presents one namespace over 64× 400G InfiniBand/Ethernet. With GPUDirect Storage, reads bypass the CPU and land directly i" }, { "type": "product", "title": "DRACO 2 PB Parallel-FS NVMe AI Storage", "url": "https://rdp.in/gpu-mart/product/draco-2-pb-parallel-fs-nvme-ai-storage/", "sku": "212196", "text": "DRACO 2 PB Parallel-FS NVMe AI Storage. SKU 212196. 2 PB usable (NVMe) · 1.2 TB/s read · Parallel FS (Lustre/GPFS-class) · 32× 400G InfiniBand/Ethernet · 16U (8-node) . The DRACO 2 PB Parallel-FS NVMe AI Storage is a scale-out parallel-filesystem NVMe storage system built to feed entire GPU clusters during large-scale AI training. It delivers 2 PB usable (NVMe) at 1.2 TB/s read with GPUDirect Storage across a clustered namespace, so datasets, checkpoints and weights stream to many GPU nodes in parallel without the storage becoming the bottleneck — on-premises, in INR, on a GST invoice. Engineered for cluster-scale AI/HPC data pipelines, it presents a single parallel namespace over high-speed networking and scales capacity and bandwidth together by adding nodes — delivered racked, configured and validated as one system with one warranty and one support contract. Key highlights 2 PB usable (NVMe) · 1.2 TB/s read — cluster-scale bandwidth sized to feed many GPU nodes during training. Parallel filesystem + GPUDirect Storage — a single namespace; data streams from NVMe straight to GPU memory across the cluster. Parallel FS (Lustre/GPFS-class) + NFS/S3, GPUDirect Storage — parallel and standard protocols so existing pipelines and schedulers just work. 192× 15.36 TB NVMe (8 nodes) — dense enterprise NVMe with end-to-end data integrity, scaling across nodes. 32× 400G InfiniBand/Ethernet — high-bandwidth networking to the GPU fabric; bandwidth grows with capacity. 80M random read — high aggregate random-read IOPS for metadata- and small-file-heavy AI datasets. On-prem data sovereignty — datasets and weights stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Where it fits Cluster training data lake (primary): the high-bandwidth tier that streams datasets to a GPU cluster in parallel without starving any node. Checkpoints & weights: fast parallel write/read of large checkpoints during long multi-node runs. RAG & vector stores: low-latency storage for large embeddings, indexes and retrieval corpora. HPC scratch: high-throughput scratch for simulation alongside AI. How it works A clustered parallel filesystem stripes data across NVMe nodes and presents one namespace over 32× 400G InfiniBand/Ethernet. With GPUDirect Storage, reads bypass the CPU and land directly in" }, { "type": "product", "title": "QUASAR 50 TB Edge AI Storage", "url": "https://rdp.in/gpu-mart/product/quasar-50-tb-edge-ai-storage/", "sku": "469979", "text": "QUASAR 50 TB Edge AI Storage. SKU 469979. 50 TB usable (NVMe) · 40 GB/s read · NFS/S3 + GPUDirect Storage · 2× 100G · 1U short-depth . The QUASAR 50 TB Edge AI Storage is an all-flash NVMe storage system built to keep GPUs fed during AI training and inference. It delivers 50 TB usable (NVMe) at 40 GB/s read with GPUDirect Storage, so training data, checkpoints and model weights stream to the GPUs without the storage becoming the bottleneck — on-premises, in INR, on a GST invoice. Engineered for AI/ML data pipelines at the edge, it pairs dense NVMe with a nfs/s3 and high-speed networking, delivered racked, configured and validated as a single system with one warranty and one support contract. Key highlights 50 TB usable (NVMe) · 40 GB/s read — high-bandwidth flash sized to feed GPU clusters during training. GPUDirect Storage — data streams from NVMe straight to GPU memory, bypassing the CPU bounce for maximum throughput. NFS/S3 + GPUDirect Storage — parallel/standard protocols so existing pipelines and frameworks just work. 12× 7.68 TB NVMe — dense, enterprise NVMe with end-to-end data integrity. 2× 100G — high-speed networking to the GPU fabric; no I/O wall. 2.5M random read — high random-read IOPS for many small files and metadata-heavy AI datasets. On-prem data sovereignty — datasets and weights stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Where it fits Training data lake (primary): the high-bandwidth tier that streams datasets to GPU servers and clusters without starving them. Checkpoints & weights: fast write/read of large checkpoints during long training runs. RAG & vector stores: low-latency storage for embeddings, indexes and retrieval corpora. Inference assets: model weights and caches served at line rate to inference nodes. How it works An all-flash NVMe array exposes a NFS/S3 + GPUDirect Storage namespace over 2× 100G. With GPUDirect Storage, reads bypass the CPU and land directly in GPU memory, so the GPUs spend time computing, not waiting on I/O. The system scales by adding nodes; capacity and bandwidth grow together. Honest note: real throughput depends on dataset shape, file sizes and the client fabric — we validate it on your data rather than quoting only a peak number. Industry use cases AI/ML platforms — feed GPU clusters with tr" }, { "type": "product", "title": "DRACO 1 PB Parallel-FS NVMe AI Storage", "url": "https://rdp.in/gpu-mart/product/draco-1-pb-parallel-fs-nvme-ai-storage/", "sku": "202415", "text": "DRACO 1 PB Parallel-FS NVMe AI Storage. SKU 202415. 1 PB usable (NVMe) · 640 GB/s read · Parallel FS (Lustre/GPFS-class) · 16× 200G InfiniBand/Ethernet · 8U (4-node) . The DRACO 1 PB Parallel-FS NVMe AI Storage is a scale-out parallel-filesystem NVMe storage system built to feed entire GPU clusters during large-scale AI training. It delivers 1 PB usable (NVMe) at 640 GB/s read with GPUDirect Storage across a clustered namespace, so datasets, checkpoints and weights stream to many GPU nodes in parallel without the storage becoming the bottleneck — on-premises, in INR, on a GST invoice. Engineered for cluster-scale AI/HPC data pipelines, it presents a single parallel namespace over high-speed networking and scales capacity and bandwidth together by adding nodes — delivered racked, configured and validated as one system with one warranty and one support contract. Key highlights 1 PB usable (NVMe) · 640 GB/s read — cluster-scale bandwidth sized to feed many GPU nodes during training. Parallel filesystem + GPUDirect Storage — a single namespace; data streams from NVMe straight to GPU memory across the cluster. Parallel FS (Lustre/GPFS-class) + NFS/S3, GPUDirect Storage — parallel and standard protocols so existing pipelines and schedulers just work. 96× 15.36 TB NVMe (4 nodes) — dense enterprise NVMe with end-to-end data integrity, scaling across nodes. 16× 200G InfiniBand/Ethernet — high-bandwidth networking to the GPU fabric; bandwidth grows with capacity. 40M random read — high aggregate random-read IOPS for metadata- and small-file-heavy AI datasets. On-prem data sovereignty — datasets and weights stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Where it fits Cluster training data lake (primary): the high-bandwidth tier that streams datasets to a GPU cluster in parallel without starving any node. Checkpoints & weights: fast parallel write/read of large checkpoints during long multi-node runs. RAG & vector stores: low-latency storage for large embeddings, indexes and retrieval corpora. HPC scratch: high-throughput scratch for simulation alongside AI. How it works A clustered parallel filesystem stripes data across NVMe nodes and presents one namespace over 16× 200G InfiniBand/Ethernet. With GPUDirect Storage, reads bypass the CPU and land directly in G" }, { "type": "product", "title": "QUASAR 250 TB All-Flash NVMe AI Storage", "url": "https://rdp.in/gpu-mart/product/quasar-250-tb-all-flash-nvme-ai-storage/", "sku": "298000", "text": "QUASAR 250 TB All-Flash NVMe AI Storage. SKU 298000. 250 TB usable (NVMe) · 160 GB/s read · Parallel FS + NFS/S3, GPUDirect Storage · 4× 200G InfiniBand/Ethernet · 2U . The QUASAR 250 TB All-Flash NVMe AI Storage is an all-flash NVMe storage system built to keep GPUs fed during AI training and inference. It delivers 250 TB usable (NVMe) at 160 GB/s read with GPUDirect Storage, so training data, checkpoints and model weights stream to the GPUs without the storage becoming the bottleneck — on-premises, in INR, on a GST invoice. Engineered for AI/ML data pipelines, it pairs dense NVMe with a parallel fs and high-speed networking, delivered racked, configured and validated as a single system with one warranty and one support contract. Key highlights 250 TB usable (NVMe) · 160 GB/s read — high-bandwidth flash sized to feed GPU clusters during training. GPUDirect Storage — data streams from NVMe straight to GPU memory, bypassing the CPU bounce for maximum throughput. Parallel FS + NFS/S3, GPUDirect Storage — parallel/standard protocols so existing pipelines and frameworks just work. 24× 15.36 TB NVMe — dense, enterprise NVMe with end-to-end data integrity. 4× 200G InfiniBand/Ethernet — high-speed networking to the GPU fabric; no I/O wall. 10M random read — high random-read IOPS for many small files and metadata-heavy AI datasets. On-prem data sovereignty — datasets and weights stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Where it fits Training data lake (primary): the high-bandwidth tier that streams datasets to GPU servers and clusters without starving them. Checkpoints & weights: fast write/read of large checkpoints during long training runs. RAG & vector stores: low-latency storage for embeddings, indexes and retrieval corpora. Inference assets: model weights and caches served at line rate to inference nodes. How it works An all-flash NVMe array exposes a Parallel FS + NFS/S3, GPUDirect Storage namespace over 4× 200G InfiniBand/Ethernet. With GPUDirect Storage, reads bypass the CPU and land directly in GPU memory, so the GPUs spend time computing, not waiting on I/O. The system scales by adding nodes; capacity and bandwidth grow together. Honest note: real throughput depends on dataset shape, file sizes and the client fabric — we validate it on your" }, { "type": "product", "title": "DRACO 4U Mission-Critical Server", "url": "https://rdp.in/gpu-mart/product/draco-4u-mission-critical-server/", "sku": "543296", "text": "DRACO 4U Mission-Critical Server. SKU 543296. 2× AMD EPYC 9005 or 2× Intel Xeon 6 (6900-series) · up to 9 TB DDR5-6000 ECC RDIMM · up to 24× Gen5 NVMe hot-swap + rear boot · 4U rack . The DRACO 4U Mission-Critical Server is a RAS-hardened 4U scale-up enterprise server — 2× AMD EPYC 9005 or 2× Intel Xeon 6 (6900-series), up to 9 TB DDR5-6000 ECC RDIMM, up to 24× Gen5 NVMe hot-swap + rear boot — built in India by RDP for mission-critical scale-up, large in-memory databases and ERP consolidation. It is the dependable enterprise compute that runs the rest of the datacentre around your AI: virtualization, databases, control planes, storage front-ends and line-of-business workloads, on a GST invoice in INR. Engineered with current-generation AMD EPYC / Intel Xeon 6 silicon, all-NVMe options and lights-out management, it is delivered racked, burned-in and validated, with RDP as your single support contact pan-India. Key highlights Processor: 2× AMD EPYC 9005 or 2× Intel Xeon 6 (6900-series) — up to 256 cores. Memory: up to 9 TB DDR5-6000 ECC RDIMM. Storage: up to 24× Gen5 NVMe hot-swap + rear boot. Networking: dual-100GbE LOM + OCP 3.0, fully redundant. Form factor: 4U rack, air-cooled with liquid-assist option, N+N redundant hot-swap PSUs. GPU option: up to 4× NVIDIA L40S (optional, double-width). Management: dedicated BMC / IPMI with redfish, remote KVM and out-of-band update. Make-in-India OEM — INR pricing, GST tax invoice, pan-India onsite support, GeM-procurable. What it runs Mission-critical consolidation (primary) — RAS-hardened 4U for the largest single-system workloads. Large in-memory databases — multi-TB SAP HANA-class and real-time analytics. Control-plane & infrastructure services — Kubernetes control nodes, AD/DNS/DHCP, backup, monitoring. Line-of-business apps — ERP, file/print, web/app tiers. Configuration & scale Up to 9 TB DDR5 and 24 Gen5 NVMe in a 4U chassis with full power/cooling redundancy and optional GPU acceleration. Specify CPU SKU, memory, drives and NICs at quote; we ship it configured, not a bare chassis. Honest note: exact maximums depend on the CPU SKU and DIMM/drive population chosen — confirmed on your quote. Industry use cases Government & PSU — on-prem virtualization, storage and databases, GeM-procurable. BFSI — OLTP, core-banking adjuncts and DR with input-credit-eligible billing. Healthcare — HIS/LIS/PACS back-ends under data" }, { "type": "product", "title": "DRACO 2U High-Core Virtualization Server", "url": "https://rdp.in/gpu-mart/product/draco-2u-high-core-virtualization-server/", "sku": "638459", "text": "DRACO 2U High-Core Virtualization Server. SKU 638459. 2× AMD EPYC 9005 (Turin / Turin Dense) · up to 6 TB DDR5-6000 ECC RDIMM (24 DIMM) · up to 24× Gen5 NVMe hot-swap (all-flash) · 2U rack . The DRACO 2U High-Core Virtualization Server is a maximum-density 2U dual-socket virtualization host — 2× AMD EPYC 9005 (Turin / Turin Dense), up to 6 TB DDR5-6000 ECC RDIMM (24 DIMM), up to 24× Gen5 NVMe hot-swap (all-flash) — built in India by RDP for maximum VM/container density and large private clouds. It is the dependable enterprise compute that runs the rest of the datacentre around your AI: virtualization, databases, control planes, storage front-ends and line-of-business workloads, on a GST invoice in INR. Engineered with current-generation AMD EPYC silicon, all-NVMe options and lights-out management, it is delivered racked, burned-in and validated, with RDP as your single support contact pan-India. Key highlights Processor: 2× AMD EPYC 9005 (Turin / Turin Dense) — up to 384 cores (2× 192C). Memory: up to 6 TB DDR5-6000 ECC RDIMM (24 DIMM). Storage: up to 24× Gen5 NVMe hot-swap (all-flash). Networking: 2× 100GbE LOM + OCP 3.0. Form factor: 2U rack, air-cooled with optional liquid-assist, N+1 hot-swap PSUs. GPU option: up to 2× NVIDIA L40S (optional, for VDI/inference). Management: dedicated BMC / IPMI with redfish, remote KVM and out-of-band update. Make-in-India OEM — INR pricing, GST tax invoice, pan-India onsite support, GeM-procurable. What it runs Maximum-density virtualization (primary) — 384 cores for the highest VM/container count per 2U. Kubernetes & container nodes — dense worker nodes for large on-prem clusters. Control-plane & infrastructure services — Kubernetes control nodes, AD/DNS/DHCP, backup, monitoring. Line-of-business apps — ERP, file/print, web/app tiers. Configuration & scale Dual EPYC 9005 with up to 384 cores, 6 TB DDR5 and 24 Gen5 NVMe bays for the densest 2U consolidation. Specify CPU SKU, memory, drives and NICs at quote; we ship it configured, not a bare chassis. Honest note: exact maximums depend on the CPU SKU and DIMM/drive population chosen — confirmed on your quote. Industry use cases Government & PSU — on-prem virtualization, storage and databases, GeM-procurable. BFSI — OLTP, core-banking adjuncts and DR with input-credit-eligible billing. Healthcare — HIS/LIS/PACS back-ends under data-residency rules. Manufacturing & ITES — E" }, { "type": "product", "title": "QUASAR 2U Storage Server", "url": "https://rdp.in/gpu-mart/product/quasar-2u-storage-server/", "sku": "688249", "text": "QUASAR 2U Storage Server. SKU 688249. 1–2× Intel Xeon 6 (6500-series) or single AMD EPYC 9005 · up to 2 TB DDR5-5600 ECC RDIMM · up to 12× 3.5″ LFF (HDD/SATA) + 2–4× rear NVMe cache/boot · 2U storage chassis . The QUASAR 2U Storage Server is a storage-dense 2U software-defined storage node — 1–2× Intel Xeon 6 (6500-series) or single AMD EPYC 9005, up to 2 TB DDR5-5600 ECC RDIMM, up to 12× 3.5″ LFF (HDD/SATA) + 2–4× rear NVMe cache/boot — built in India by RDP for software-defined storage, backup repositories and NAS/object stores. It is the dependable enterprise compute that runs the rest of the datacentre around your AI: virtualization, databases, control planes, storage front-ends and line-of-business workloads, on a GST invoice in INR. Engineered with current-generation Intel Xeon 6 / AMD EPYC silicon, all-NVMe options and lights-out management, it is delivered racked, burned-in and validated, with RDP as your single support contact pan-India. Key highlights Processor: 1–2× Intel Xeon 6 (6500-series) or single AMD EPYC 9005 — up to 128 cores. Memory: up to 2 TB DDR5-5600 ECC RDIMM. Storage: up to 12× 3.5″ LFF (HDD/SATA) + 2–4× rear NVMe cache/boot. Networking: 2× 25GbE LOM + dual-100GbE OCP 3.0 option. Form factor: 2U storage chassis, air-cooled, N+1 hot-swap PSUs. GPU option: not required (capacity/IO-optimised); up to 1× NVIDIA L4 optional. Management: dedicated BMC / IPMI with redfish, remote KVM and out-of-band update. Make-in-India OEM — INR pricing, GST tax invoice, pan-India onsite support, GeM-procurable. What it runs Software-defined storage (primary) — Ceph, MinIO, ZFS/TrueNAS nodes with dense HDD plus NVMe cache. Backup & archive target — high-capacity Veeam/Commvault repository and cold tier. Control-plane & infrastructure services — Kubernetes control nodes, AD/DNS/DHCP, backup, monitoring. Line-of-business apps — ERP, file/print, web/app tiers. Configuration & scale Twelve large-form-factor bays plus rear NVMe cache, scaled out as a storage cluster across multiple nodes. Specify CPU SKU, memory, drives and NICs at quote; we ship it configured, not a bare chassis. Honest note: exact maximums depend on the CPU SKU and DIMM/drive population chosen — confirmed on your quote. Industry use cases Government & PSU — on-prem virtualization, storage and databases, GeM-procurable. BFSI — OLTP, core-banking adjuncts and DR with input-c" }, { "type": "product", "title": "CARINA Edge Server", "url": "https://rdp.in/gpu-mart/product/carina-edge-server/", "sku": "221414", "text": "CARINA Edge Server. SKU 221414. 1× Intel Xeon 6 (6300/6500-series) or Xeon D · up to 512 GB DDR5 ECC · up to 4× NVMe hot-swap · short-depth 1U/2U edge chassis . The CARINA Edge Server is a short-depth rugged edge server — 1× Intel Xeon 6 (6300/6500-series) or Xeon D, up to 512 GB DDR5 ECC, up to 4× NVMe hot-swap — built in India by RDP for remote sites, branches, retail, factories and telco edge. It is the dependable enterprise compute that runs the rest of the datacentre around your AI: virtualization, databases, control planes, storage front-ends and line-of-business workloads, on a GST invoice in INR. Engineered with current-generation Intel Xeon 6 / Xeon D silicon, all-NVMe options and lights-out management, it is delivered racked, burned-in and validated, with RDP as your single support contact pan-India. Key highlights Processor: 1× Intel Xeon 6 (6300/6500-series) or Xeon D — up to 32 cores. Memory: up to 512 GB DDR5 ECC. Storage: up to 4× NVMe hot-swap. Networking: 2× 10/25GbE LOM, optional 5G/LTE. Form factor: short-depth 1U/2U edge chassis, air-cooled, extended 0–45°C operating range, filtered intake. GPU option: up to 1× NVIDIA L4 (optional, for edge inference). Management: dedicated BMC / IPMI with redfish, remote KVM and out-of-band update. Make-in-India OEM — INR pricing, GST tax invoice, pan-India onsite support, GeM-procurable. What it runs Edge inference & local compute — run models and apps close to data at remote sites. Local virtualization & caching — a few VMs, CDN cache and store-and-forward at the edge. Control-plane & infrastructure services — Kubernetes control nodes, AD/DNS/DHCP, backup, monitoring. Line-of-business apps — ERP, file/print, web/app tiers. Configuration & scale Single-socket Xeon 6/Xeon D, up to 512 GB DDR5 and four NVMe bays in a short-depth, extended-temperature chassis. Specify CPU SKU, memory, drives and NICs at quote; we ship it configured, not a bare chassis. Honest note: exact maximums depend on the CPU SKU and DIMM/drive population chosen — confirmed on your quote. Industry use cases Government & PSU — on-prem virtualization and databases, GeM-procurable. BFSI — OLTP, core-banking adjuncts and DR with input-credit-eligible billing. Healthcare — HIS/LIS/PACS back-ends under data-residency rules. Manufacturing & ITES — ERP, MES, VDI and private-cloud hosts. Education & research — shared virtualization and storage" }, { "type": "product", "title": "QUASAR 2U Database Server", "url": "https://rdp.in/gpu-mart/product/quasar-2u-database-server/", "sku": "742033", "text": "QUASAR 2U Database Server. SKU 742033. 2× AMD EPYC 9005 (high-frequency) or 2× Intel Xeon 6 · up to 4 TB DDR5-6000 ECC RDIMM · up to 24× Gen5 NVMe hot-swap (all-flash) · 2U rack . The QUASAR 2U Database Server is a NVMe-dense 2U database and OLTP server — 2× AMD EPYC 9005 (high-frequency) or 2× Intel Xeon 6, up to 4 TB DDR5-6000 ECC RDIMM, up to 24× Gen5 NVMe hot-swap (all-flash) — built in India by RDP for transactional databases, OLTP and low-latency data services. It is the dependable enterprise compute that runs the rest of the datacentre around your AI: virtualization, databases, control planes, storage front-ends and line-of-business workloads, on a GST invoice in INR. Engineered with current-generation AMD EPYC / Intel Xeon 6 silicon, all-NVMe options and lights-out management, it is delivered racked, burned-in and validated, with RDP as your single support contact pan-India. Key highlights Processor: 2× AMD EPYC 9005 (high-frequency) or 2× Intel Xeon 6 — up to 128 high-frequency cores. Memory: up to 4 TB DDR5-6000 ECC RDIMM. Storage: up to 24× Gen5 NVMe hot-swap (all-flash). Networking: 2× 25GbE LOM + dual-100GbE OCP 3.0 option. Form factor: 2U rack, air-cooled with optional liquid-assist, N+1 hot-swap PSUs. GPU option: not required (CPU/IO-optimised); up to 1× NVIDIA L4 optional. Management: dedicated BMC / IPMI with redfish, remote KVM and out-of-band update. Make-in-India OEM — INR pricing, GST tax invoice, pan-India onsite support, GeM-procurable. What it runs Databases & OLTP (primary) — Gen5 NVMe-backed SQL/NoSQL with low-latency IO. In-memory & analytics — large-DIMM SAP HANA-class and real-time analytics. Control-plane & infrastructure services — Kubernetes control nodes, AD/DNS/DHCP, backup, monitoring. Line-of-business apps — ERP, file/print, web/app tiers. Configuration & scale Dual EPYC 9005 or Xeon 6 tuned for clock speed, up to 4 TB DDR5 and 24 Gen5 NVMe bays for all-flash databases. Specify CPU SKU, memory, drives and NICs at quote; we ship it configured, not a bare chassis. Honest note: exact maximums depend on the CPU SKU and DIMM/drive population chosen — confirmed on your quote. Industry use cases Government & PSU — on-prem virtualization and databases, GeM-procurable. BFSI — OLTP, core-banking adjuncts and DR with input-credit-eligible billing. Healthcare — HIS/LIS/PACS back-ends under data-residency rules. Manufacturing & ITES —" }, { "type": "product", "title": "CARINA 2U Virtualization Server", "url": "https://rdp.in/gpu-mart/product/carina-2u-virtualization-server/", "sku": "514643", "text": "CARINA 2U Virtualization Server. SKU 514643. 1–2× Intel Xeon 6 (6500/6700-series) · up to 2 TB DDR5-5600 ECC RDIMM · up to 12× 3.5″/2.5″ hybrid hot-swap (NVMe/SATA) · 2U rack . The CARINA 2U Virtualization Server is a entry 2U dual-socket virtualization host — 1–2× Intel Xeon 6 (6500/6700-series), up to 2 TB DDR5-5600 ECC RDIMM, up to 12× 3.5″/2.5″ hybrid hot-swap (NVMe/SATA) — built in India by RDP for SMB and departmental virtualization and private cloud. It is the dependable enterprise compute that runs the rest of the datacentre around your AI: virtualization, databases, control planes, storage front-ends and line-of-business workloads, on a GST invoice in INR. Engineered with current-generation Intel Xeon 6 silicon, all-NVMe options and lights-out management, it is delivered racked, burned-in and validated, with RDP as your single support contact pan-India. Key highlights Processor: 1–2× Intel Xeon 6 (6500/6700-series) — up to 128 cores. Memory: up to 2 TB DDR5-5600 ECC RDIMM. Storage: up to 12× 3.5″/2.5″ hybrid hot-swap (NVMe/SATA). Networking: 2× 10/25GbE LOM + OCP 3.0 slot. Form factor: 2U rack, air-cooled, N+1 hot-swap PSUs. GPU option: up to 1× NVIDIA L40S (optional, for light VDI/inference). Management: dedicated BMC / IPMI with redfish, remote KVM and out-of-band update. Make-in-India OEM — INR pricing, GST tax invoice, pan-India onsite support, GeM-procurable. What it runs Virtualization & private cloud — entry-density VM consolidation with hybrid storage. Backup & DR target — large-capacity hybrid bays for veeam/proxmox backup. Control-plane & infrastructure services — Kubernetes control nodes, AD/DNS/DHCP, backup, monitoring. Line-of-business apps — ERP, file/print, web/app tiers. Configuration & scale Single or dual Xeon 6, up to 2 TB DDR5 and twelve hybrid bays for cost-effective consolidation. Specify CPU SKU, memory, drives and NICs at quote; we ship it configured, not a bare chassis. Honest note: exact maximums depend on the CPU SKU and DIMM/drive population chosen — confirmed on your quote. Industry use cases Government & PSU — on-prem virtualization and databases, GeM-procurable. BFSI — OLTP, core-banking adjuncts and DR with input-credit-eligible billing. Healthcare — HIS/LIS/PACS back-ends under data-residency rules. Manufacturing & ITES — ERP, MES, VDI and private-cloud hosts. Education & research" }, { "type": "product", "title": "DRACO 512-Node InfiniBand XDR Fabric", "url": "https://rdp.in/gpu-mart/product/draco-512-node-infiniband-xdr-fabric/", "sku": "429789", "text": "DRACO 512-Node InfiniBand XDR Fabric. SKU 429789. 512 nodes · 2,048× 800G · 1.6 Pb/s aggregate · InfiniBand XDR (Quantum-X800) · Sub-600 ns · Multi-rack spine-leaf . The DRACO 512-Node InfiniBand XDR Fabric is RDP’s flagship turnkey InfiniBand fabric — a non-blocking spine-leaf interconnect that wires an entire GPU supercluster, providing 512 nodes · 2,048× 800G at 1.6 Pb/s aggregate of aggregate bandwidth over InfiniBand XDR (Quantum-X800), with Sub-600 ns. It is the interconnect that turns a data hall of GPU servers into one supercluster, carrying the collective (all-reduce) traffic that dominates frontier AI training — on-premises, in INR, on a GST invoice. Engineered as the fabric layer of an RDP AI supercluster, it is delivered designed, cabled and validated alongside the compute and storage it connects, as a single non-blocking system with one warranty and one support contract. Key highlights 512 nodes · 2,048× 800G · 1.6 Pb/s aggregate — a complete non-blocking fabric to wire 512 GPU nodes at full bandwidth. InfiniBand XDR (Quantum-X800) — RDMA, lossless, in-network compute (SHARP) for fast collectives at scale. Sub-600 ns — low latency so frontier-scale training scales with near-linear efficiency. 800G per port — matched to your GPU NICs/DPUs. Turnkey, validated fabric — delivered designed, cabled and tested as one system, not loose boxes. Validated with RDP compute & storage — part of a tested supercluster. On-prem sovereignty — your fabric, your data path; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8517), pan-India onsite support, GeM-procurable. Where it fits Supercluster fabric (primary): the non-blocking interconnect carrying distributed-training collectives across the data hall. Storage fabric: high-bandwidth path between GPU nodes and the NVMe parallel-FS (GPUDirect). Spine-leaf at scale: a full non-blocking topology for thousands of GPUs. HPC interconnect: tightly-coupled MPI and AI collectives at frontier scale. How it works The fabric forms a non-blocking spine-leaf topology with RDMA over InfiniBand; the subnet manager programs routes, in-network compute (SHARP) offloads reductions, and adaptive routing avoids hotspots — so all-reduce traffic, which dominates multi-node training, completes fast even at 512 nodes. RDP sizes the topology (oversubscription, spine count) to your supercl" }, { "type": "product", "title": "DRACO 256-Node InfiniBand XDR Fabric", "url": "https://rdp.in/gpu-mart/product/draco-256-node-infiniband-xdr-fabric/", "sku": "241753", "text": "DRACO 256-Node InfiniBand XDR Fabric. SKU 241753. 256 nodes · 1,024× 800G · 820 Tb/s aggregate · InfiniBand XDR (Quantum-X800) · Sub-600 ns · Multi-rack fabric . The DRACO 256-Node InfiniBand XDR Fabric is a turnkey InfiniBand fabric that wires a GPU cluster end-to-end — switches, the subnet manager and the leaf-spine topology — providing 256 nodes · 1,024× 800G at 820 Tb/s aggregate over InfiniBand XDR (Quantum-X800), with Sub-600 ns. It is the interconnect that turns a hall of GPU servers into one cluster, carrying the collective (all-reduce) traffic that dominates multi-node AI training — on-premises, in INR, on a GST invoice. Engineered as the fabric layer of an RDP AI cluster or supercluster, it is delivered designed, cabled and validated alongside the compute and storage it connects, as a single non-blocking system with one warranty and one support contract. Key highlights 256 nodes · 1,024× 800G · 820 Tb/s aggregate — a complete non-blocking fabric to wire 256 GPU nodes at full bandwidth. InfiniBand XDR (Quantum-X800) — RDMA, lossless, in-network compute (SHARP) for fast collectives. Sub-600 ns — low latency so distributed training scales with near-linear efficiency. 800G per port — matched to your GPU NICs/DPUs. Turnkey, validated fabric — delivered cabled and tested as one system, not loose boxes. Validated with RDP compute & storage — part of a tested cluster. On-prem sovereignty — your fabric, your data path; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8517), pan-India onsite support, GeM-procurable. Where it fits GPU cluster fabric (primary): the interconnect that carries distributed-training collectives across the cluster. Storage fabric: high-bandwidth path between GPU nodes and the NVMe parallel-FS (GPUDirect). Scale-out spine: a non-blocking leaf-spine topology for large clusters and superclusters. HPC interconnect: tightly-coupled MPI and AI collectives. How it works The fabric forms a non-blocking leaf/spine topology with RDMA over InfiniBand; the subnet manager programs routes, in-network compute (SHARP) offloads reductions, and adaptive routing avoids hotspots — so all-reduce traffic, which dominates multi-node training, completes fast. RDP sizes the topology (oversubscription, spine count) to your cluster. Honest note: real scaling efficiency depends on topology, collective library and m" }, { "type": "product", "title": "DRACO 128-Node InfiniBand XDR Fabric", "url": "https://rdp.in/gpu-mart/product/draco-128-node-infiniband-xdr-fabric/", "sku": "973489", "text": "DRACO 128-Node InfiniBand XDR Fabric. SKU 973489. 128 nodes · 512× 800G · 410 Tb/s aggregate · InfiniBand XDR (Quantum-X800) · Sub-600 ns · Leaf-spine fabric (multi-rack) . The DRACO 128-Node InfiniBand XDR Fabric is a turnkey InfiniBand fabric that wires a GPU cluster end-to-end — switches, the subnet manager and the leaf-spine topology — providing 128 nodes · 512× 800G at 410 Tb/s aggregate over InfiniBand XDR (Quantum-X800), with Sub-600 ns. It is the interconnect that turns a hall of GPU servers into one cluster, carrying the collective (all-reduce) traffic that dominates multi-node AI training — on-premises, in INR, on a GST invoice. Engineered as the fabric layer of an RDP AI cluster or supercluster, it is delivered designed, cabled and validated alongside the compute and storage it connects, as a single non-blocking system with one warranty and one support contract. Key highlights 128 nodes · 512× 800G · 410 Tb/s aggregate — a complete non-blocking fabric to wire 128 GPU nodes at full bandwidth. InfiniBand XDR (Quantum-X800) — RDMA, lossless, in-network compute (SHARP) for fast collectives. Sub-600 ns — low latency so distributed training scales with near-linear efficiency. 800G per port — matched to your GPU NICs/DPUs. Turnkey, validated fabric — delivered cabled and tested as one system, not loose boxes. Validated with RDP compute & storage — part of a tested cluster. On-prem sovereignty — your fabric, your data path; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8517), pan-India onsite support, GeM-procurable. Where it fits GPU cluster fabric (primary): the interconnect that carries distributed-training collectives across the cluster. Storage fabric: high-bandwidth path between GPU nodes and the NVMe parallel-FS (GPUDirect). Scale-out spine: a non-blocking leaf-spine topology for large clusters and superclusters. HPC interconnect: tightly-coupled MPI and AI collectives. How it works The fabric forms a non-blocking leaf/spine topology with RDMA over InfiniBand; the subnet manager programs routes, in-network compute (SHARP) offloads reductions, and adaptive routing avoids hotspots — so all-reduce traffic, which dominates multi-node training, completes fast. RDP sizes the topology (oversubscription, spine count) to your cluster. Honest note: real scaling efficiency depends on topology, collective librar" }, { "type": "product", "title": "QUASAR 32-Port 200G Ethernet AI Switch", "url": "https://rdp.in/gpu-mart/product/quasar-32-port-200g-ethernet-ai-switch/", "sku": "865824", "text": "QUASAR 32-Port 200G Ethernet AI Switch. SKU 865824. 32× 200G QSFP56 · 12.8 Tb/s switching · Spectrum-X Ethernet (RoCE) · Low-latency cut-through · 1U short-depth . The QUASAR 32-Port 200G Ethernet AI Switch is the high-bandwidth interconnect that turns a pile of GPU servers into a cluster. It provides 32× 200G QSFP56 at 12.8 Tb/s of non-blocking switching over Spectrum-X Ethernet (RoCE), with Low-latency cut-through — the low-latency, lossless fabric that lets distributed AI training scale across nodes without the network becoming the bottleneck. On-premises, in INR, on a GST invoice. Engineered as the fabric layer of an RDP AI cluster, it carries the collective (all-reduce) traffic that dominates multi-node training, and is delivered configured, cabled and validated alongside the compute and storage it connects. Key highlights 32× 200G QSFP56 · 12.8 Tb/s — non-blocking switching to wire a GPU cluster at full bandwidth. Spectrum-X Ethernet (RoCE) — RoCE with adaptive routing and congestion control tuned for AI. Low-latency cut-through — low latency so distributed training scales with near-linear efficiency. 200G / 100G per port — flexible speeds to match your GPU NICs/DPUs. Spine-leaf ready — combine switches into a non-blocking fabric for hundreds to thousands of GPUs. Validated with RDP compute — delivered as part of a tested cluster, not a loose box. On-prem sovereignty — your fabric, your data path; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8517), pan-India onsite support, GeM-procurable. Where it fits GPU cluster fabric (primary): the interconnect between GPU servers that carries distributed-training collectives. Storage fabric: high-bandwidth path between GPU nodes and the NVMe parallel-FS (GPUDirect). Scale-out spine: a leaf or spine in a non-blocking topology for large clusters. AI Ethernet fabric: RoCE-based AI fabric for teams standardising on Ethernet. How it works The switch forms a leaf/spine fabric with RoCE over Ethernet; GPU NICs/DPUs connect at 200G / 100G. Adaptive routing, PFC and congestion control keep the fabric lossless — so all-reduce traffic, which dominates multi-node training, completes fast. RDP sizes the topology (oversubscription, spine count) to your cluster. Honest note: real scaling efficiency depends on topology, collective library and model — we validate it on your cluste" }, { "type": "product", "title": "QUASAR 64-Node InfiniBand NDR Fabric", "url": "https://rdp.in/gpu-mart/product/quasar-64-node-infiniband-ndr-fabric/", "sku": "266769", "text": "QUASAR 64-Node InfiniBand NDR Fabric. SKU 266769. 64 nodes · 256× 400G · 102 Tb/s aggregate · InfiniBand NDR (Quantum-2) · Sub-600 ns · Leaf-spine fabric (4U) . The QUASAR 64-Node InfiniBand NDR Fabric is a turnkey InfiniBand fabric that wires a GPU cluster end-to-end — switches, the subnet manager and the leaf-spine topology — providing 64 nodes · 256× 400G at 102 Tb/s aggregate over InfiniBand NDR (Quantum-2), with Sub-600 ns. It is the interconnect that turns a hall of GPU servers into one cluster, carrying the collective (all-reduce) traffic that dominates multi-node AI training — on-premises, in INR, on a GST invoice. Engineered as the fabric layer of an RDP AI cluster or supercluster, it is delivered designed, cabled and validated alongside the compute and storage it connects, as a single non-blocking system with one warranty and one support contract. Key highlights 64 nodes · 256× 400G · 102 Tb/s aggregate — a complete non-blocking fabric to wire 64 GPU nodes at full bandwidth. InfiniBand NDR (Quantum-2) — RDMA, lossless, in-network compute (SHARP) for fast collectives. Sub-600 ns — low latency so distributed training scales with near-linear efficiency. 400G per port — matched to your GPU NICs/DPUs. Turnkey, validated fabric — delivered cabled and tested as one system, not loose boxes. Validated with RDP compute & storage — part of a tested cluster. On-prem sovereignty — your fabric, your data path; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8517), pan-India onsite support, GeM-procurable. Where it fits GPU cluster fabric (primary): the interconnect that carries distributed-training collectives across the cluster. Storage fabric: high-bandwidth path between GPU nodes and the NVMe parallel-FS (GPUDirect). Scale-out spine: a non-blocking leaf-spine topology for large clusters and superclusters. HPC interconnect: tightly-coupled MPI and AI collectives. How it works The fabric forms a non-blocking leaf/spine topology with RDMA over InfiniBand; the subnet manager programs routes, in-network compute (SHARP) offloads reductions, and adaptive routing avoids hotspots — so all-reduce traffic, which dominates multi-node training, completes fast. RDP sizes the topology (oversubscription, spine count) to your cluster. Honest note: real scaling efficiency depends on topology, collective library and model — we vali" }, { "type": "product", "title": "QUASAR 16-Node InfiniBand NDR Fabric", "url": "https://rdp.in/gpu-mart/product/quasar-16-node-infiniband-ndr-fabric/", "sku": "353168", "text": "QUASAR 16-Node InfiniBand NDR Fabric. SKU 353168. 16 nodes · 64× 400G · 25.6 Tb/s aggregate · InfiniBand NDR (Quantum-2) · Sub-600 ns · Single-switch fabric (1U) . The QUASAR 16-Node InfiniBand NDR Fabric is a turnkey InfiniBand fabric that wires a GPU cluster end-to-end — switches, the subnet manager and the topology, providing 16 nodes · 64× 400G at 25.6 Tb/s aggregate over InfiniBand NDR (Quantum-2), with Sub-600 ns. It is the interconnect that turns a set of GPU servers into a cluster, carrying the collective (all-reduce) traffic that dominates multi-node AI training — on-premises, in INR, on a GST invoice. Engineered as the fabric layer of an RDP AI cluster, it is delivered configured, cabled and validated alongside the compute and storage it connects. Key highlights 16 nodes · 64× 400G · 25.6 Tb/s aggregate — a complete non-blocking fabric to wire a GPU cluster at full bandwidth. InfiniBand NDR (Quantum-2) — RDMA, lossless, in-network compute (SHARP) for fast collectives. Sub-600 ns — low latency so distributed training scales with near-linear efficiency. 400G per port — matched to your GPU NICs/DPUs. Turnkey, validated fabric — delivered cabled and tested as one system, not loose boxes. Validated with RDP compute & storage — part of a tested cluster. On-prem sovereignty — your fabric, your data path; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8517), pan-India onsite support, GeM-procurable. Where it fits GPU cluster fabric (primary): the interconnect that carries distributed-training collectives between GPU servers. Storage fabric: high-bandwidth path between GPU nodes and the NVMe parallel-FS (GPUDirect). Scale-out spine: a leaf/spine building block for larger clusters. HPC interconnect: tightly-coupled MPI and AI collectives. How it works The fabric forms a leaf/spine topology with RDMA over InfiniBand; the subnet manager programs routes, in-network compute (SHARP) offloads reductions, and adaptive routing avoids hotspots — so all-reduce traffic, which dominates multi-node training, completes fast. RDP sizes the topology (oversubscription, spine count, DPU count) to your cluster. Honest note: real scaling efficiency depends on topology, collective library and model — we validate it on your cluster, not just a peak number. Industry use cases AI/ML & foundation-model teams — the fabric that lets trai" }, { "type": "product", "title": "QUASAR 2× RTX PRO 6000 Blackwell Agentic AI PC", "url": "https://rdp.in/gpu-mart/product/quasar-2x-rtx-pro-6000-blackwell-agentic-ai-pc/", "sku": "419524", "text": "QUASAR 2× RTX PRO 6000 Blackwell Agentic AI PC. SKU 419524. Intel Xeon W-3500 · 512 GB DDR5 ECC · 16 TB NVMe · 192 GB GDDR7 · Tower . The QUASAR 2× RTX PRO 6000 Blackwell Agentic AI PC runs many AI agents locally — a tower workstation with 2× NVIDIA RTX PRO 6000 Blackwell (192 GB GDDR7) built to run private LLM agents, RAG and automation at scale on your own hardware, offline if needed. It puts serious agentic AI on the desk without sending prompts or data to the cloud — in INR, on a GST invoice. Engineered for teams running multiple concurrent agents or larger local models, it pairs a high-core Xeon W with two Blackwell GPUs, plus large memory and fast NVMe, so local models and agent fleets respond instantly and keep data in-house. Key highlights 2× RTX PRO 6000 Blackwell · 192 GB GDDR7 — run larger local LLMs (70B+) and many concurrent agents on-device. Dual Blackwell GPUs + Xeon W — data-parallel serving of multiple models or larger quantised models for agent fleets. Intel Xeon W-3500 + 512 GB DDR5 ECC — high-core orchestration for many multi-step agents and RAG. 16 TB NVMe NVMe — large local model store, vector DB and document corpus; no egress. Tower, 25 GbE — quiet desk-side footprint with high-throughput networking. Private & offline-capable — prompts, data and models stay on-device; air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Upgrade path — step up to an agentic inference server for fleet-scale concurrent agents, or an AI Workstation for heavy fine-tuning. AI workload fit (what it actually runs — honestly) Local agents at scale (primary): run 70B+ models and many concurrent agentic workflows — tool use, RAG, automation and copilots. RAG & document AI: on-device retrieval over large local corpora and vector DBs. Fine-tuning, vision & speech: QLoRA fine-tuning, local CV, speech and multimodal inference. Engineering note: with 192 GB GDDR7 of GPU memory this serves 70B+ quantised models; the two PCIe GPUs (no NVLink) are ideal for data-parallel multi-model serving — for one model larger than 96 GB use tensor parallelism across the pair. It is built for responsive local agent fleets, not large-scale training. AI workload positioning This sits at the local-agent-fleet stage: the machine that runs many AI agents privately, on the desk. With 192 GB GDDR7 across 2 Blackwell" }, { "type": "product", "title": "QUASAR 2× RTX PRO 5000 Blackwell Agentic AI PC", "url": "https://rdp.in/gpu-mart/product/quasar-2x-rtx-pro-5000-blackwell-agentic-ai-pc/", "sku": "972155", "text": "QUASAR 2× RTX PRO 5000 Blackwell Agentic AI PC. SKU 972155. Intel Xeon W-3500 · 256 GB DDR5 ECC · 8 TB NVMe · 96 GB GDDR7 · Tower . The QUASAR 2× RTX PRO 5000 Blackwell Agentic AI PC runs many AI agents locally — a tower workstation with 2× NVIDIA RTX PRO 5000 Blackwell (96 GB GDDR7) built to run private LLM agents, RAG and automation at scale on your own hardware, offline if needed. It puts serious agentic AI on the desk without sending prompts or data to the cloud — in INR, on a GST invoice. Engineered for teams running multiple concurrent agents or larger local models, it pairs a high-core Xeon W with two Blackwell GPUs, plus large memory and fast NVMe, so local models and agent fleets respond instantly and keep data in-house. Key highlights 2× RTX PRO 5000 Blackwell · 96 GB GDDR7 — run larger local LLMs (up to 70B) and many concurrent agents on-device. Dual Blackwell GPUs + Xeon W — data-parallel serving of multiple models or larger quantised models for agent fleets. Intel Xeon W-3500 + 256 GB DDR5 ECC — high-core orchestration for many multi-step agents and RAG. 8 TB NVMe NVMe — large local model store, vector DB and document corpus; no egress. Tower, 10 GbE — quiet desk-side footprint with high-throughput networking. Private & offline-capable — prompts, data and models stay on-device; air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Upgrade path — step up to an agentic inference server for fleet-scale concurrent agents, or an AI Workstation for heavy fine-tuning. AI workload fit (what it actually runs — honestly) Local agents at scale (primary): run up to 70B models and many concurrent agentic workflows — tool use, RAG, automation and copilots. RAG & document AI: on-device retrieval over large local corpora and vector DBs. Fine-tuning, vision & speech: QLoRA fine-tuning, local CV, speech and multimodal inference. Engineering note: with 96 GB GDDR7 of GPU memory this serves up to 70B quantised models; the two PCIe GPUs (no NVLink) are ideal for data-parallel multi-model serving — for one model larger than 96 GB use tensor parallelism across the pair. It is built for responsive local agent fleets, not large-scale training. AI workload positioning This sits at the local-agent-fleet stage: the machine that runs many AI agents privately, on the desk. With 96 GB GDDR7 across 2 Bl" }, { "type": "product", "title": "QUASAR 1× RTX PRO 6000 Blackwell Agentic AI PC", "url": "https://rdp.in/gpu-mart/product/quasar-1x-rtx-pro-6000-blackwell-agentic-ai-pc/", "sku": "599917", "text": "QUASAR 1× RTX PRO 6000 Blackwell Agentic AI PC. SKU 599917. Intel Xeon W-3500 · 256 GB DDR5 ECC · 8 TB NVMe · 96 GB GDDR7 · Tower . The QUASAR 1× RTX PRO 6000 Blackwell Agentic AI PC runs many AI agents locally — a tower workstation with 1× NVIDIA RTX PRO 6000 Blackwell (96 GB GDDR7) built to run private LLM agents, RAG and automation at scale on your own hardware, offline if needed. It puts serious agentic AI on the desk without sending prompts or data to the cloud — in INR, on a GST invoice. Engineered for teams running multiple concurrent agents or larger local models, it pairs a high-core Xeon W with a Blackwell GPU, plus large memory and fast NVMe, so local models and agent fleets respond instantly and keep data in-house. Key highlights 1× RTX PRO 6000 Blackwell · 96 GB GDDR7 — run larger local LLMs (up to 70B) and many concurrent agents on-device. Blackwell GPU + Xeon W — high-capacity local inference for agent fleets. Intel Xeon W-3500 + 256 GB DDR5 ECC — high-core orchestration for many multi-step agents and RAG. 8 TB NVMe NVMe — large local model store, vector DB and document corpus; no egress. Tower, 10 GbE — quiet desk-side footprint with high-throughput networking. Private & offline-capable — prompts, data and models stay on-device; air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Upgrade path — step up to an agentic inference server for fleet-scale concurrent agents, or an AI Workstation for heavy fine-tuning. AI workload fit (what it actually runs — honestly) Local agents at scale (primary): run up to 70B models and many concurrent agentic workflows — tool use, RAG, automation and copilots. RAG & document AI: on-device retrieval over large local corpora and vector DBs. Fine-tuning, vision & speech: QLoRA fine-tuning, local CV, speech and multimodal inference. Engineering note: with 96 GB GDDR7 of GPU memory this serves up to 70B quantised models. It is built for responsive local agent fleets, not large-scale training. AI workload positioning This sits at the local-agent-fleet stage: the machine that runs many AI agents privately, on the desk. With 96 GB GDDR7 across 1 Blackwell GPU and a high-core Xeon W, it is sized to sustain concurrent local inference and agent loops — where cloud APIs are slow, costly or non-compliant. Industry use cases Software & product teams" }, { "type": "product", "title": "CARINA 1× RTX PRO 2000 Blackwell Compact Agentic AI PC", "url": "https://rdp.in/gpu-mart/product/carina-1x-rtx-pro-2000-blackwell-compact-agentic-ai-pc/", "sku": "113585", "text": "CARINA 1× RTX PRO 2000 Blackwell Compact Agentic AI PC. SKU 113585. Intel Core Ultra 9 (with NPU) · 64 GB DDR5 · 2 TB NVMe · 16 GB GDDR7 · Compact / SFF . The CARINA 1× RTX PRO 2000 Blackwell Compact Agentic AI PC runs AI agents locally — a compact / sff workstation with 1× NVIDIA RTX PRO 2000 Blackwell (16 GB GDDR7) built to run private LLM agents, RAG and automation on your own hardware, offline if needed. It puts agentic AI on the desk without sending prompts or data to the cloud — in INR, on a GST invoice. Engineered for developers, prosumers and teams adopting local agentic AI, it pairs a modern Intel Core Ultra 9 with on-chip NPU and the Blackwell GPU, plus fast memory and NVMe, so local models and agent workflows respond instantly and keep data in-house. Key highlights 1× RTX PRO 2000 Blackwell · 16 GB GDDR7 — run quantised local LLMs (7B–14B) and agent workflows on-device. Blackwell GPU + on-chip NPU — accelerated local inference with an AI-PC NPU for always-on agents. Intel Core Ultra 9 (with NPU) + 64 GB DDR5 — responsive orchestration for multi-step agents and RAG. 2 TB NVMe NVMe — local model store, vector DB and document corpus; no egress. Compact / SFF, 2.5 GbE — small-footprint desk-side or counter placement. Private & offline-capable — prompts, data and models stay on-device; air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Upgrade path — step up to higher-memory RTX PRO Blackwell agentic PCs, or an agentic inference server for many concurrent agents. AI workload fit (what it actually runs — honestly) Local agents (primary): run quantised 7B–14B LLMs for private agentic workflows — tool use, RAG, automation and copilots. RAG & document AI: on-device retrieval over your local corpus and vector DB. Light fine-tuning, vision & speech: QLoRA on small models, local CV, speech-to-text and multimodal inference. Engineering note: with 16 GB GDDR7 of GPU memory this runs quantised models up to ~14B comfortably; for larger models or many concurrent agents, step up to a higher-memory PC or an agentic inference server. It is built for responsive local agents, not large-model training. AI workload positioning This sits at the local-agent stage: the machine that runs your AI agents privately, on the desk. With 16 GB GDDR7 and a GPU plus NPU, it is sized to sustain responsive lo" }, { "type": "product", "title": "QUASAR 1× RTX PRO 5000 Blackwell Agentic AI PC", "url": "https://rdp.in/gpu-mart/product/quasar-1x-rtx-pro-5000-blackwell-agentic-ai-pc/", "sku": "812913", "text": "QUASAR 1× RTX PRO 5000 Blackwell Agentic AI PC. SKU 812913. Intel Xeon W-2500 · 256 GB DDR5 ECC · 4 TB NVMe · 48 GB GDDR7 · Tower . The QUASAR 1× RTX PRO 5000 Blackwell Agentic AI PC runs AI agents locally — a tower workstation with 1× NVIDIA RTX PRO 5000 Blackwell (48 GB GDDR7) built to run private LLM agents, RAG and automation on your own hardware, offline if needed. It puts agentic AI on the desk without sending prompts or data to the cloud — in INR, on a GST invoice. Engineered for developers, prosumers and teams adopting local agentic AI, it pairs a modern Intel Xeon W-2500 with on-chip NPU and the Blackwell GPU, plus fast memory and NVMe, so local models and agent workflows respond instantly and keep data in-house. Key highlights 1× RTX PRO 5000 Blackwell · 48 GB GDDR7 — run quantised local LLMs (34B–70B) and agent workflows on-device. Blackwell GPU + on-chip NPU — accelerated local inference with an AI-PC NPU for always-on agents. Intel Xeon W-2500 + 256 GB DDR5 ECC — responsive orchestration for multi-step agents and RAG. 4 TB NVMe NVMe — local model store, vector DB and document corpus; no egress. Tower, 10 GbE — quiet desk-side footprint. Private & offline-capable — prompts, data and models stay on-device; air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Upgrade path — step up to higher-memory RTX PRO Blackwell agentic PCs, or an agentic inference server for many concurrent agents. AI workload fit (what it actually runs — honestly) Local agents (primary): run quantised 34B–70B LLMs for private agentic workflows — tool use, RAG, automation and copilots. RAG & document AI: on-device retrieval over your local corpus and vector DB. Light fine-tuning, vision & speech: QLoRA on small models, local CV, speech-to-text and multimodal inference. Engineering note: with 48 GB GDDR7 of GPU memory this runs quantised models up to ~70B comfortably; for larger models or many concurrent agents, step up to a higher-memory PC or an agentic inference server. It is built for responsive local agents, not large-model training. AI workload positioning This sits at the local-agent stage: the machine that runs your AI agents privately, on the desk. With 48 GB GDDR7 and a GPU plus NPU, it is sized to sustain responsive local inference and agent loops — where sending every prompt to a cloud API i" }, { "type": "product", "title": "CARINA 1× RTX PRO 4000 Blackwell Agentic AI PC", "url": "https://rdp.in/gpu-mart/product/carina-1x-rtx-pro-4000-blackwell-agentic-ai-pc/", "sku": "991169", "text": "CARINA 1× RTX PRO 4000 Blackwell Agentic AI PC. SKU 991169. Intel Core Ultra 9 (with NPU) · 128 GB DDR5 · 4 TB NVMe · 24 GB GDDR7 · Tower / SFF . The CARINA 1× RTX PRO 4000 Blackwell Agentic AI PC runs AI agents locally — a tower / sff system with 1× NVIDIA RTX PRO 4000 Blackwell (24 GB GDDR7) built to run private LLM agents, RAG and automation on your own hardware, offline if needed. It puts agentic AI on the desk without sending prompts or data to the cloud — in INR, on a GST invoice. Engineered for developers, prosumers and teams adopting local agentic AI, it pairs a modern Intel Core Ultra 9 with on-chip NPU and the GPU with fast memory and NVMe so local models and agent workflows respond instantly and keep data in-house. Key highlights 1× RTX PRO 4000 Blackwell · 24 GB GDDR7 — run quantised local LLMs (7B–34B) and agent workflows on-device. GPU + on-chip NPU — accelerated local inference with an AI-PC NPU for always-on agents. Intel Core Ultra 9 (with NPU) + 128 GB DDR5 — responsive orchestration for multi-step agents and RAG. 4 TB NVMe NVMe — local model store, vector DB and document corpus; no egress. Tower / SFF, 10 GbE — compact desk-side or edge footprint. Private & offline-capable — prompts, data and models stay on-device; air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Upgrade path — step up to higher-memory RTX PRO Blackwell agentic PCs, or an agentic inference server for many concurrent agents. AI workload fit (what it actually runs — honestly) Local agents (primary): run quantised 7B–34B LLMs for private agentic workflows — tool use, RAG, automation and copilots. RAG & document AI: on-device retrieval over your local corpus and vector DB. Vision & speech: local CV, speech-to-text and multimodal inference. Engineering note: with 24 GB GDDR7 of GPU memory this runs quantised models up to ~34B comfortably; for larger models or many concurrent agents, step up to a higher-memory PC or an agentic inference server. It is built for responsive local agents, not large-model training. AI workload positioning This sits at the local-agent stage: the device that runs your AI agents privately, on the desk. With 24 GB GDDR7 and a GPU plus NPU, it is sized to sustain responsive local inference and agent loops — where sending every prompt to a cloud API is slow, costly or non-compl" }, { "type": "product", "title": "DRACO 4× RTX PRO 6000 Blackwell AI Workstation", "url": "https://rdp.in/gpu-mart/product/draco-4x-rtx-pro-6000-blackwell-ai-workstation/", "sku": "262431", "text": "DRACO 4× RTX PRO 6000 Blackwell AI Workstation. SKU 262431. Intel Xeon W-3500 · 512 GB DDR5 ECC · 16 TB NVMe · Liquid-cooled 4-GPU tower . The DRACO 4× RTX PRO 6000 Blackwell AI Workstation is RDP’s flagship desk-side AI machine — four NVIDIA RTX PRO 6000 Blackwell GPUs and a full 384 GB of next-generation GDDR7 GPU memory in a single quiet, liquid-cooled tower, engineered for teams that want data-centre-class fine-tuning and inference without a data centre. It puts a private, on-premises alternative to four rented top-end cloud GPUs under one desk: your models and data never leave the building, costs are fixed in INR, and the box is productive on day one. Built for AI/ML teams, research labs and product-engineering groups standardising on a repeatable, secure local-AI platform, it balances 384 GB of aggregate GPU memory, a high-core Intel Xeon W-3500 data-prep engine, 512 GB of ECC system memory and 16 TB of NVMe — the difference between a workstation that benchmarks well and one that sustains real large-model training and serving. Key highlights 384 GB of GPU memory across 4× RTX PRO 6000 Blackwell — fine-tune and serve very large models locally; run several large models at once without queueing for shared cloud capacity. 96 GB per GPU, Blackwell architecture with FP4 — next-gen accuracy and inference efficiency; ECC throughout for long, stable fine-tune runs. Intel Xeon W-3500 + 512 GB DDR5 ECC — a high-core data-prep, tokenisation and orchestration engine so the four GPUs aren’t starved. 16 TB NVMe + 25 GbE — fast local datasets, checkpoints and weights, with high-speed networking for multi-node scaling; no egress fees. Liquid-cooled, desk-side — sustained all-GPU clocks under load, quiet enough for an office, not a server room. On-prem data sovereignty — your IP and customer data stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Upgrade path — when you outgrow four desk-side GPUs or need trillion-parameter training, move to an RDP rack-scale GPU server / NVL-class system. AI workload fit (what it actually runs — honestly) Full-precision large models: a 70B model in FP16 (~140 GB) runs comfortably; with 384 GB aggregate you can hold much larger models or several in parallel, tensor-parallel across all four cards . Inference: serve 70B–" }, { "type": "product", "title": "DRACO 4× RTX PRO 5000 Blackwell AI Workstation", "url": "https://rdp.in/gpu-mart/product/draco-4x-rtx-pro-5000-blackwell-ai-workstation/", "sku": "376739", "text": "DRACO 4× RTX PRO 5000 Blackwell AI Workstation. SKU 376739. Intel Xeon W-3500 · 512 GB DDR5 ECC · 8 TB NVMe · Liquid-cooled 4-GPU tower . The DRACO 4× RTX PRO 5000 Blackwell AI Workstation is RDP’s mid-flagship desk-side machine — four NVIDIA RTX PRO 5000 Blackwell GPUs and 192 GB of next-generation GDDR7 in a single quiet, liquid-cooled tower, sized to run a 70B model in FP16 on-premises. It puts a private alternative to four rented high-memory cloud GPUs under one desk: your models and data never leave the building, costs are fixed in INR, and the box is productive on day one. Built for AI/ML teams, research labs and product-engineering groups standardising on a repeatable, secure local-AI platform, it balances 192 GB of aggregate Blackwell GPU memory, a high-core Intel Xeon W-3500 data-prep engine, 512 GB of ECC system memory and 8 TB of NVMe — so the GPUs stay fed for serious training and serving. Key highlights 192 GB of GPU memory across 4× RTX PRO 5000 Blackwell — run a 70B model in FP16 or fine-tune large models locally; serve several models at once without queueing for cloud capacity. Blackwell architecture with FP4 support — next-gen inference efficiency, ECC throughout for stable long fine-tune runs. Intel Xeon W-3500 + 512 GB DDR5 ECC — a high-core data-prep, tokenisation and orchestration engine so the four GPUs aren’t starved. 8 TB NVMe + 25 GbE — fast local datasets, checkpoints and weights, with high-speed networking for multi-node experiments; no egress fees. Liquid-cooled, desk-side — sustained all-GPU clocks under load, quiet enough for an office, not a server room. On-prem data sovereignty — IP and customer data stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Upgrade path — step up within DRACO to 4× RTX PRO 6000 Blackwell (384 GB), or to a rack-scale RDP system when you outgrow four GPUs. AI workload fit (what it actually runs — honestly) Full-precision large models: a 70B model in FP16 (~140 GB) runs tensor-parallel across all four cards using the 192 GB aggregate pool. Inference: serve 70B-class models, or run several quantised 7B–34B models concurrently across the four GPUs. Fine-tuning: QLoRA / LoRA up to ~70B, and full fine-tuning of 7B–13B models, data-parallel across the four GPUs. Vision, multimodal, RAG & ag" }, { "type": "product", "title": "QUASAR 2× RTX PRO 6000 Blackwell AI Workstation", "url": "https://rdp.in/gpu-mart/product/quasar-2x-rtx-pro-6000-blackwell-ai-workstation/", "sku": "132355", "text": "QUASAR 2× RTX PRO 6000 Blackwell AI Workstation. SKU 132355. Intel Xeon W-3500 · 256 GB DDR5 ECC · 8 TB NVMe · Dual-GPU tower . The QUASAR 2× RTX PRO 6000 Blackwell AI Workstation is the top of RDP’s performance tier — two NVIDIA RTX PRO 6000 Blackwell GPUs and a full 192 GB of next-generation GDDR7 in a single quiet tower. It gives AI/ML teams the GPU-memory headroom to fine-tune and serve 70B-class models on-premises in a desk-side form factor, as a private, fixed-cost alternative to renting top-end cloud GPUs: models and data stay in the building, billing is in INR, and the system is productive on day one. Built for research labs, applied-AI groups and product-engineering teams standardising on a repeatable local-AI platform, it balances 192 GB of aggregate Blackwell GPU memory, a high-core Intel Xeon W-3500 data-prep engine, 256 GB of ECC system memory and 8 TB of NVMe — so the GPUs stay fed and the box sustains serious training and serving. Key highlights 192 GB of GPU memory across 2× RTX PRO 6000 Blackwell — the headroom to run a 70B model in FP16 or fine-tune large models locally, without queueing for shared cloud capacity. 96 GB per GPU, Blackwell architecture with FP4 — next-gen inference efficiency and accuracy, ECC throughout for stable long fine-tune runs. Intel Xeon W-3500 + 256 GB DDR5 ECC — a high-core data-prep, tokenisation and orchestration engine so the GPUs are never starved. 8 TB NVMe — fast local datasets, checkpoints and weights; no egress fees, no network bottleneck. Quiet dual-GPU tower — data-centre-class GPU memory at the desk, not in a server room. On-prem data sovereignty — IP and customer data stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Upgrade path — when you outgrow two GPUs, step up to a DRACO 4-GPU flagship or an RDP rack-scale system. AI workload fit (what it actually runs — honestly) Full-precision large models: a 70B model in FP16 (~140 GB) runs tensor-parallel across both cards using the 192 GB aggregate pool. Inference: serve 70B-class models, or run several quantised 7B–34B models concurrently across the two GPUs. Fine-tuning: QLoRA / LoRA up to ~70B, and full fine-tuning of 7B–13B models, data-parallel across both GPUs. Vision, multimodal, RAG & agentic: train/serve vision and multimodal models, bu" }, { "type": "product", "title": "DRACO 4× RTX PRO 4500 Blackwell AI Workstation", "url": "https://rdp.in/gpu-mart/product/draco-4x-rtx-pro-4500-blackwell-ai-workstation/", "sku": "667031", "text": "DRACO 4× RTX PRO 4500 Blackwell AI Workstation. SKU 667031. Intel Xeon W-3500 · 256 GB DDR5 ECC · 8 TB NVMe · Liquid-cooled 4-GPU tower . The DRACO 4× RTX PRO 4500 Blackwell AI Workstation is RDP’s flagship desk-side machine at the accessible end of the 4-GPU tier — four NVIDIA RTX PRO 4500 Blackwell GPUs and 128 GB of next-generation GDDR7 in a single quiet, liquid-cooled tower. It puts a private, on-premises alternative to four rented cloud GPUs under one desk: your models and data never leave the building, costs are fixed in INR, and the box is productive on day one. Built for AI/ML teams, research labs and product-engineering groups standardising on a repeatable, secure local-AI platform, it balances 128 GB of aggregate Blackwell GPU memory, a high-core Intel Xeon W-3500 data-prep engine, 256 GB of ECC system memory and 8 TB of NVMe — the difference between a workstation that benchmarks well and one that sustains real training and serving. Key highlights 128 GB of GPU memory across 4× RTX PRO 4500 Blackwell — fine-tune and serve large models locally; run several models at once without queueing for shared cloud capacity. Blackwell architecture with FP4 support — next-gen inference efficiency and accuracy, ECC throughout for long, stable fine-tune runs. Intel Xeon W-3500 + 256 GB DDR5 ECC — a high-core data-prep, tokenisation and orchestration engine so the four GPUs aren’t starved. 8 TB NVMe — fast local datasets, checkpoints and model weights; no egress fees, no network bottleneck. Liquid-cooled, desk-side — sustained all-GPU clocks under load, quiet enough for an office, not a server room. On-prem data sovereignty — IP and customer data stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Upgrade path — step up within DRACO to 4× RTX PRO 5000/6000 Blackwell, or to a rack-scale RDP system when you outgrow four GPUs. AI workload fit (what it actually runs — honestly) Inference: serve quantised models up to ~70B (4-bit ≈ 40 GB fits on a single card) and run multiple quantised 7B–34B models concurrently across the four GPUs. Full-precision models: a 70B model in FP16 (~140 GB) exceeds 128 GB — run it quantised here, or step up to the 192 GB+ DRACO tiers for FP16. Fine-tuning: QLoRA / LoRA up to ~70B, and full fine-tuning of 7B–13B models, da" }, { "type": "product", "title": "QUASAR 2× RTX PRO 5000 Blackwell AI Workstation", "url": "https://rdp.in/gpu-mart/product/quasar-2x-rtx-pro-5000-blackwell-ai-workstation/", "sku": "128297", "text": "QUASAR 2× RTX PRO 5000 Blackwell AI Workstation. SKU 128297. Intel Xeon W-2500 · 192 GB DDR5 ECC · 4 TB NVMe · Dual-GPU tower . The QUASAR 2× RTX PRO 5000 Blackwell AI Workstation is RDP’s performance-tier desk-side machine for teams that need more GPU memory headroom — two NVIDIA RTX PRO 5000 Blackwell GPUs and 96 GB of next-generation GDDR7 in a single quiet tower. It gives AI/ML teams a private, fixed-cost on-premises alternative to renting two high-memory cloud GPUs: models and data stay in the building, billing is in INR, and the system is productive on day one. Built for research labs, applied-AI groups and product-engineering teams standardising on a repeatable local-AI platform, it balances 96 GB of aggregate Blackwell GPU memory, an Intel Xeon W-2500 data-prep engine, 192 GB of ECC system memory and 4 TB of NVMe — so the GPUs stay fed and the box sustains real fine-tuning and serving. Key highlights 96 GB of GPU memory across 2× RTX PRO 5000 Blackwell — fine-tune larger models and serve 70B-class models locally without queueing for shared cloud capacity. Blackwell architecture with FP4 support — next-gen inference efficiency, ECC throughout for stable long fine-tune runs. Intel Xeon W-2500 + 192 GB DDR5 ECC — a serious tokenisation, data-prep and orchestration engine so the GPUs are never starved. 4 TB NVMe — fast local datasets, checkpoints and weights; no egress fees, no network bottleneck. Quiet dual-GPU tower — sized for an office, not a server room. On-prem data sovereignty — IP and customer data stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Upgrade path — step up within QUASAR to 2× RTX PRO 6000 Blackwell, or to a DRACO 4-GPU flagship when you outgrow two cards. AI workload fit (what it actually runs — honestly) Inference: serve a 70B model in 4-bit (~40 GB) comfortably, or several quantised 7B–34B models concurrently across the two cards. Full-precision mid models: a 70B model in FP16 (~140 GB) exceeds 96 GB — run it quantised, or step up to the 192 GB DRACO/2× RTX PRO 6000 tier for FP16. Fine-tuning: QLoRA / LoRA up to ~70B, and full fine-tuning of 7B–13B models, data-parallel across both GPUs. Vision, multimodal, RAG & agentic: train/serve vision and multimodal models, build RAG pipelines on the 4 TB NVMe, and run multi-age" }, { "type": "product", "title": "CARINA 1× RTX PRO 6000 Blackwell AI Workstation", "url": "https://rdp.in/gpu-mart/product/carina-1x-rtx-pro-6000-blackwell-ai-workstation/", "sku": "692485", "text": "CARINA 1× RTX PRO 6000 Blackwell AI Workstation. SKU 692485. Intel Xeon W-3500 · 128 GB DDR5 ECC · 4 TB NVMe · Tower . The CARINA 1× RTX PRO 6000 Blackwell AI Workstation is RDP’s big-memory single-GPU AI machine on NVIDIA’s current Blackwell generation — one RTX PRO 6000 Blackwell with a full 96 GB of GDDR7 in a quiet, air-cooled desk-side tower. It is the most capable single-card workstation in the line: enough memory to fine-tune and serve genuinely large models locally, without multi-GPU complexity — with Blackwell FP4 for efficient inference, data kept in-house, INR pricing, and day-one readiness. A workstation-class Intel Xeon W-3500 with ECC memory, 128 GB DDR5 and 4 TB NVMe keep that 96 GB GPU fed for sustained work — the top of CARINA before stepping into multi-GPU QUASAR/DRACO. Key highlights 96 GB on a single RTX PRO 6000 Blackwell — one of the largest single-card pools available; fine-tune and serve large models with no partitioning. Blackwell + FP4 — current-generation architecture with efficient low-precision inference; ECC GPU memory. Intel Xeon W-3500 + 128 GB DDR5 ECC — high-core workstation platform with error-correcting memory. 4 TB NVMe — fast local datasets, checkpoints and weights; no egress fees. Quiet, air-cooled tower — office-friendly. On-prem data sovereignty — IP and data stay in-house; DPDP-friendly. Make-in-India OEM — INR pricing, GST invoice (HSN 8471), pan-India onsite support, GeM-procurable. AI workload fit Inference: serve quantised models up to ~ 70B (4-bit) on the single 96 GB card; FP4 boosts throughput. Fine-tuning: QLoRA / LoRA up to ~ 34–70B ; full fine-tuning of 7B–13B models. Build & serve: vision, multimodal, RAG and agentic workloads — locally, with no cloud bill. Engineering note: 96 GB on one card avoids multi-GPU partitioning entirely — the simplest way to work with large models. For more throughput or parallel jobs, step up to 2×/4× in QUASAR/DRACO. AI workload positioning This sits at the fine-tune-and-deploy stage in a single box: enough memory for large-model work on-desk, far cheaper to own than a cluster, and private by design. The natural choice when one big GPU beats juggling several. Industry use cases Software & AI teams — large-model fine-tuning and agentic development on one box." }, { "type": "product", "title": "DRACO 2048× MI300A AI Supercomputer", "url": "https://rdp.in/gpu-mart/product/draco-2048x-mi300a-ai-supercomputer/", "sku": "253181", "text": "DRACO 2048× MI300A AI Supercomputer. SKU 253181. 2048× MI300A · Integrated AMD Zen4 (APU, per node) · Unified APU memory (HBM3) · 32 PB parallel NVMe · Multi-Rack data hall · liquid-cooled . The DRACO 2048× MI300A AI Supercomputer is a turnkey, liquid-cooled exascale-class HPC + AI supercomputer built on 2048 AMD Instinct MI300A APUs — the same accelerator architecture behind the world’s leadership-class FP64 systems. It delivers ~262 TB unified HBM3 of unified accelerator memory across a multi-rack data hall with a non-blocking InfiniBand spine, fusing scientific simulation and frontier AI in one machine — on-premises, in INR, on a GST invoice. Delivered as a single national-scale engagement, RDP co-designs the reference architecture, integrates, cools and burns it in, and hands over one validated supercomputer with one warranty and one support contract. Its defining strength: FP64 HPC leadership and AI fused in one APU with unified CPU-GPU memory, removing host-device copies. Key highlights 2048× MI300A · ~262 TB unified HBM3 aggregate — exascale-class accelerator memory for the largest simulations and frontier AI. Infinity Fabric + non-blocking InfiniBand — AMD Infinity Fabric across the APUs and a non-blocking InfiniBand spine between nodes. Unified CPU-GPU APU memory — Zen4 CPU and CDNA GPU share one HBM3 pool, eliminating host-device transfers for HPC + AI. FP64 HPC leadership — the architecture of the world’s top FP64 supercomputers, with mixed-precision AI on the same nodes. 32 PB parallel NVMe parallel filesystem — exascale-grade storage for datasets, checkpoints and simulation output. Multi-Rack data hall, liquid-cooled, turnkey — delivered, integrated and validated; one engagement, one warranty. On-prem data sovereignty — data, models and codes stay in-country; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. AI workload fit (what it actually runs — honestly) HPC + simulation: leadership-class FP64 scientific computing (CFD, climate, molecular dynamics, finite-element) at national scale. Frontier AI training: distributed training of the largest models across the 2048 APUs with 3D parallelism. Large-scale inference & fine-tuning: serve and fine-tune many large models in parallel. Engineering note: this is an AMD Instinct system — it runs the o" }, { "type": "product", "title": "DRACO 1024× MI300A AI Supercomputer", "url": "https://rdp.in/gpu-mart/product/draco-1024x-mi300a-ai-supercomputer/", "sku": "716835", "text": "DRACO 1024× MI300A AI Supercomputer. SKU 716835. 1024× MI300A · Integrated AMD Zen4 (APU, per node) · Unified APU memory (HBM3) · 16 PB parallel NVMe · Multi-Rack data hall · liquid-cooled . The DRACO 1024× MI300A AI Supercomputer is a turnkey, liquid-cooled HPC + AI supercomputer built on 1024 AMD Instinct MI300A accelerators, delivering ~131 TB unified HBM3 of aggregate accelerator memory across a multi-rack data hall system with a non-blocking InfiniBand spine. It is engineered for organisations that need both traditional HPC (simulation, FP64) and frontier AI on one machine — on-premises, in INR, on a GST invoice. Delivered as a single engagement, RDP designs the reference architecture, integrates, cools and burns it in, and hands over one validated supercomputer with one warranty and one support contract. Its defining strength: FP64 HPC leadership and AI fused in one APU with unified CPU-GPU memory (the El Capitan-class architecture). Key highlights 1024× MI300A · ~131 TB unified HBM3 aggregate — accelerator memory for large simulations and frontier AI. Infinity Fabric + non-blocking InfiniBand — AMD Infinity Fabric across the APUs and a non-blocking InfiniBand spine between nodes. HPC + AI convergence — strong FP64/HPC throughput alongside mixed-precision AI; unified CPU-GPU memory removes host-device copies. Integrated AMD Zen4 (APU, per node) + Unified APU memory (HBM3) — unified APU compute and memory. 16 PB parallel NVMe parallel filesystem — high-throughput storage for datasets, checkpoints and simulation output. Multi-Rack data hall, liquid-cooled, turnkey — delivered, integrated and validated; one engagement, one warranty. On-prem data sovereignty — data and models stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. AI workload fit (what it actually runs — honestly) HPC + simulation: FP64 scientific computing (CFD, weather, molecular dynamics, finite-element) alongside AI — MI300A is the architecture behind leadership-class FP64 systems. Frontier AI training: distributed training of large models across the 1024 accelerators with 3D parallelism. Large-scale inference & fine-tuning: serve and fine-tune many large models in parallel. Engineering note: this is an AMD Instinct system: it runs the open ROCm/HIP software stack, not CUDA — we valid" }, { "type": "product", "title": "DRACO 256× MI300A AI Supercomputer", "url": "https://rdp.in/gpu-mart/product/draco-256x-mi300a-ai-supercomputer/", "sku": "297996", "text": "DRACO 256× MI300A AI Supercomputer. SKU 297996. 256× MI300A · Integrated AMD Zen4 (APU, per node) · Unified APU memory (HBM3) · 4 PB parallel NVMe · Multi-Rack · liquid-cooled . The DRACO 256× MI300A AI Supercomputer is a turnkey, liquid-cooled HPC + AI supercomputer built on 256 AMD Instinct MI300A accelerators, delivering ~33 TB unified HBM3 of aggregate accelerator memory across a multi-rack system with a non-blocking InfiniBand spine. It is engineered for organisations that need both traditional HPC (simulation, FP64) and frontier AI on one machine — on-premises, in INR, on a GST invoice. Delivered as a single engagement, RDP designs the reference architecture, integrates, cools and burns it in, and hands over one validated supercomputer with one warranty and one support contract. Its defining strength: FP64 HPC leadership and AI fused in one APU with unified CPU-GPU memory (the El Capitan-class architecture). Key highlights 256× MI300A · ~33 TB unified HBM3 aggregate — accelerator memory for large simulations and frontier AI. Infinity Fabric + non-blocking InfiniBand — AMD Infinity Fabric across the APUs and a non-blocking InfiniBand spine between nodes. HPC + AI convergence — strong FP64/HPC throughput alongside mixed-precision AI; unified CPU-GPU memory removes host-device copies. Integrated AMD Zen4 (APU, per node) + Unified APU memory (HBM3) — unified APU compute and memory. 4 PB parallel NVMe parallel filesystem — high-throughput storage for datasets, checkpoints and simulation output. Multi-Rack, liquid-cooled, turnkey — delivered, integrated and validated; one engagement, one warranty. On-prem data sovereignty — data and models stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. AI workload fit (what it actually runs — honestly) HPC + simulation: FP64 scientific computing (CFD, weather, molecular dynamics, finite-element) alongside AI — MI300A is the architecture behind leadership-class FP64 systems. Frontier AI training: distributed training of large models across the 256 accelerators with 3D parallelism. Large-scale inference & fine-tuning: serve and fine-tune many large models in parallel. Engineering note: this is an AMD Instinct system: it runs the open ROCm/HIP software stack, not CUDA — we validate your models and HPC codes on ROCm be" }, { "type": "product", "title": "DRACO 512× MI300X AI Supercomputer", "url": "https://rdp.in/gpu-mart/product/draco-512x-mi300x-ai-supercomputer/", "sku": "457680", "text": "DRACO 512× MI300X AI Supercomputer. SKU 457680. 512× MI300X · 128× AMD EPYC (64 nodes) · 128 TB DDR5 ECC · 8 PB parallel NVMe · Multi-Rack · liquid-cooled . The DRACO 512× MI300X AI Supercomputer is a turnkey, liquid-cooled HPC + AI supercomputer built on 512 AMD Instinct MI300X accelerators, delivering ~98 TB HBM3 of aggregate accelerator memory across a multi-rack system with a non-blocking InfiniBand spine. It is engineered for organisations that need both traditional HPC (simulation, FP64) and frontier AI on one machine — on-premises, in INR, on a GST invoice. Delivered as a single engagement, RDP designs the reference architecture, integrates, cools and burns it in, and hands over one validated supercomputer with one warranty and one support contract. Its defining strength: a large 192 GB HBM3 pool per GPU for memory-bound AI. Key highlights 512× MI300X · ~98 TB HBM3 aggregate — accelerator memory for large simulations and frontier AI. Infinity Fabric + non-blocking InfiniBand — AMD Infinity Fabric within each node and a non-blocking InfiniBand spine between nodes. HPC + AI convergence — strong FP64/HPC throughput alongside mixed-precision AI. 128× AMD EPYC (64 nodes) + 128 TB DDR5 ECC — CPU and memory matched to 512 accelerators. 8 PB parallel NVMe parallel filesystem — high-throughput storage for datasets, checkpoints and simulation output. Multi-Rack, liquid-cooled, turnkey — delivered, integrated and validated; one engagement, one warranty. On-prem data sovereignty — data and models stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. AI workload fit (what it actually runs — honestly) HPC + simulation: FP64 scientific computing (CFD, weather, molecular dynamics, finite-element) alongside AI. Frontier AI training: distributed training of large models across the 512 accelerators with 3D parallelism. Large-scale inference & fine-tuning: serve and fine-tune many large models in parallel. Engineering note: this is an AMD Instinct system: it runs the open ROCm/HIP software stack, not CUDA — we validate your models and HPC codes on ROCm before you commit. At this scale the network and parallelism strategy decide real performance; we run a scaling test on your codes and models rather than quoting a peak number. AI workload positioning This sits at the H" }, { "type": "product", "title": "DRACO 256× MI300X AI Supercomputer", "url": "https://rdp.in/gpu-mart/product/draco-256x-mi300x-ai-supercomputer/", "sku": "907019", "text": "DRACO 256× MI300X AI Supercomputer. SKU 907019. 256× MI300X · 64× AMD EPYC (32 nodes) · 64 TB DDR5 ECC · 4 PB parallel NVMe · Multi-Rack · liquid-cooled . The DRACO 256× MI300X AI Supercomputer is a turnkey, liquid-cooled HPC + AI supercomputer built on 256 AMD Instinct MI300X accelerators, delivering ~49 TB HBM3 of aggregate accelerator memory across a multi-rack system with a non-blocking InfiniBand spine. It is engineered for organisations that need both traditional HPC (simulation, FP64) and frontier AI on one machine — on-premises, in INR, on a GST invoice. Delivered as a single engagement, RDP designs the reference architecture, integrates, cools and burns it in, and hands over one validated supercomputer with one warranty and one support contract — removing multi-vendor integration risk. Its defining strength: large 192 GB HBM3 per GPU for memory-bound AI. Key highlights 256× MI300X · ~49 TB HBM3 aggregate — accelerator memory for large simulations and frontier AI. Infinity Fabric + non-blocking InfiniBand — AMD Infinity Fabric within each node and a non-blocking InfiniBand spine between nodes. HPC + AI convergence — strong FP64/HPC throughput alongside mixed-precision AI on one system. 64× AMD EPYC (32 nodes) + 64 TB DDR5 ECC — CPU and memory matched to 256 accelerators. 4 PB parallel NVMe parallel filesystem — high-throughput storage for datasets, checkpoints and simulation output. Multi-Rack, liquid-cooled, turnkey — delivered, integrated and validated; one engagement, one warranty. On-prem data sovereignty — data and models stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. AI workload fit (what it actually runs — honestly) HPC + simulation: FP64 scientific computing (CFD, weather, molecular dynamics, finite-element) alongside AI. Frontier AI training: distributed training of large models across the 256 accelerators with 3D parallelism. Large-scale inference & fine-tuning: serve and fine-tune many large models in parallel. Engineering note: this is an AMD Instinct system: it runs the open ROCm/HIP software stack, not CUDA — we validate your models and HPC codes on ROCm before you commit. At this scale the network and parallelism strategy decide real performance; we run a scaling test on your codes and models rather than quoting a peak number" }, { "type": "product", "title": "DRACO 512× GH200 AI Supercomputer", "url": "https://rdp.in/gpu-mart/product/draco-512x-gh200-ai-supercomputer/", "sku": "736564", "text": "DRACO 512× GH200 AI Supercomputer. SKU 736564. 512× GH200 · 512× Grace (ARM) · Grace LPDDR5X coherent memory · 8 PB parallel NVMe · Multi-Rack · liquid-cooled . The DRACO 512× GH200 AI Supercomputer is a turnkey, liquid-cooled HPC + AI supercomputer built on 512 NVIDIA GH200 Grace-Hopper accelerators, delivering ~74 TB HBM3e of aggregate accelerator memory across a multi-rack system with a non-blocking InfiniBand spine. It is engineered for organisations that need both traditional HPC (simulation, FP64) and frontier AI on one machine — on-premises, in INR, on a GST invoice. Delivered as a single engagement, RDP designs the reference architecture, integrates, cools and burns it in, and hands over one validated supercomputer with one warranty and one support contract — removing multi-vendor integration risk. Its defining strength: tightly-coupled Grace CPU + Hopper GPU with coherent memory for HPC + AI. Key highlights 512× GH200 · ~74 TB HBM3e aggregate — accelerator memory for large simulations and frontier AI. NVLink-C2C + non-blocking InfiniBand — NVLink-C2C coherent CPU-GPU links and a non-blocking InfiniBand spine between superchips. HPC + AI convergence — strong FP64/HPC throughput alongside mixed-precision AI on one system. 512× Grace (ARM) + Grace LPDDR5X coherent memory — CPU and memory matched to 512 accelerators. 8 PB parallel NVMe parallel filesystem — high-throughput storage for datasets, checkpoints and simulation output. Multi-Rack, liquid-cooled, turnkey — delivered, integrated and validated; one engagement, one warranty. On-prem data sovereignty — data and models stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. AI workload fit (what it actually runs — honestly) HPC + simulation: FP64 scientific computing (CFD, weather, molecular dynamics, finite-element) alongside AI. Frontier AI training: distributed training of large models across the 512 accelerators with 3D parallelism. Large-scale inference & fine-tuning: serve and fine-tune many large models in parallel. Engineering note: this is an NVIDIA Grace-Hopper system on the CUDA software stack. At this scale the network and parallelism strategy decide real performance; we run a scaling test on your codes and models rather than quoting a peak number. AI workload positioning This sits at t" }, { "type": "product", "title": "DRACO 64-Node H200 HPC Cluster", "url": "https://rdp.in/gpu-mart/product/draco-64-node-h200-hpc-cluster/", "sku": "148193", "text": "DRACO 64-Node H200 HPC Cluster. SKU 148193. 64 nodes · 128× AMD EPYC 9005 (12,288 cores) · 64 TB DDR5 ECC · 256× H200 · 4 PB NVMe · InfiniBand · liquid-cooled . The DRACO 64-Node H200 HPC Cluster is a turnkey 64-node HPC cluster pairing massive CPU-forward compute with large-scale GPU acceleration — 12288 AMD EPYC cores across 64 nodes plus 256× H200 accelerators (36,096 GB HBM3e HBM3e, NVLink in-node), wired with a non-blocking InfiniBand fabric. It runs traditional FP64/MPI HPC and large-model AI on one cluster, on-premises, in INR, on a GST invoice. Engineered for organisations whose workload spans serious simulation and serious AI, it is delivered racked, cabled, scheduled and validated as a single system — RDP sizes the nodes, fabric, parallel storage, scheduler and cooling, with one warranty and one support contract. Key highlights 12288 EPYC cores across 64 nodes — large-scale CPU throughput for FP64, MPI and memory-bound HPC. 256× H200 · 36,096 GB HBM3e — large-scale GPU acceleration for model training and high-throughput inference alongside HPC. Non-blocking InfiniBand NDR fabric — full-bisection bandwidth for tightly-coupled MPI jobs and distributed training. 64 TB DDR5 ECC + 4 PB NVMe parallel NVMe — large memory and a high-throughput parallel filesystem at cluster scale. Scheduler-ready, turnkey — delivered with Slurm/Kubernetes, validated; one SKU, one warranty. On-prem data sovereignty — codes, data and models stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Scale path — grow node count toward supercomputer scale, or specialise into GPU-dense rack-scale systems. AI workload fit (what it actually runs — honestly) HPC + simulation (primary): large FP64/MPI workloads — CFD, FEA, molecular dynamics, EDA, risk and Monte-Carlo — across 12288 cores. AI training & inference: train and fine-tune large models across the NVLink-connected H200 GPUs and serve them at high throughput. RAG & agentic: production AI services co-located with HPC for engineering and research teams. Engineering note: each node’s H200 GPUs are NVLink-connected for efficient in-node tensor parallelism, and nodes scale over a non-blocking InfiniBand spine — this cluster trains and serves large models alongside FP64 HPC. The CPU cores carry the simulation/MPI side; the G" }, { "type": "product", "title": "DRACO 32-Node H200 HPC Cluster", "url": "https://rdp.in/gpu-mart/product/draco-32-node-h200-hpc-cluster/", "sku": "692341", "text": "DRACO 32-Node H200 HPC Cluster. SKU 692341. 32 nodes · 64× AMD EPYC 9005 (6,144 cores) · 32 TB DDR5 ECC · 128× H200 · 2 PB NVMe · InfiniBand · liquid-cooled . The DRACO 32-Node H200 HPC Cluster is a turnkey 32-node HPC cluster pairing massive CPU-forward compute with large-scale GPU acceleration — 6144 AMD EPYC cores across 32 nodes plus 128× H200 accelerators (18,048 GB HBM3e HBM3e, NVLink in-node), wired with a non-blocking InfiniBand fabric. It runs traditional FP64/MPI HPC and large-model AI on one cluster, on-premises, in INR, on a GST invoice. Engineered for organisations whose workload spans serious simulation and serious AI, it is delivered racked, cabled, scheduled and validated as a single system — RDP sizes the nodes, fabric, parallel storage, scheduler and cooling, with one warranty and one support contract. Key highlights 6144 EPYC cores across 32 nodes — large-scale CPU throughput for FP64, MPI and memory-bound HPC. 128× H200 · 18,048 GB HBM3e — large-scale GPU acceleration for model training and high-throughput inference alongside HPC. Non-blocking InfiniBand NDR fabric — full-bisection bandwidth for tightly-coupled MPI jobs and distributed training. 32 TB DDR5 ECC + 2 PB NVMe parallel NVMe — large memory and a high-throughput parallel filesystem at cluster scale. Scheduler-ready, turnkey — delivered with Slurm/Kubernetes, validated; one SKU, one warranty. On-prem data sovereignty — codes, data and models stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Scale path — grow node count toward supercomputer scale, or specialise into GPU-dense rack-scale systems. AI workload fit (what it actually runs — honestly) HPC + simulation (primary): large FP64/MPI workloads — CFD, FEA, molecular dynamics, EDA, risk and Monte-Carlo — across 6144 cores. AI training & inference: train and fine-tune large models across the NVLink-connected H200 GPUs and serve them at high throughput. RAG & agentic: production AI services co-located with HPC for engineering and research teams. Engineering note: each node’s H200 GPUs are NVLink-connected for efficient in-node tensor parallelism, and nodes scale over a non-blocking InfiniBand spine — this cluster trains and serves large models alongside FP64 HPC. The CPU cores carry the simulation/MPI side; the GPUs c" }, { "type": "product", "title": "DRACO 16-Node H200 HPC Cluster", "url": "https://rdp.in/gpu-mart/product/draco-16-node-h200-hpc-cluster/", "sku": "665993", "text": "DRACO 16-Node H200 HPC Cluster. SKU 665993. 16 nodes · 32× AMD EPYC 9005 (3,072 cores) · 16 TB DDR5 ECC · 64× H200 · 960 TB NVMe · InfiniBand · liquid/air . The DRACO 16-Node H200 HPC Cluster is a turnkey 16-node HPC cluster pairing CPU-forward compute with GPU acceleration — 3072 AMD EPYC cores across 16 nodes plus H200 accelerators (9,024 GB HBM3e HBM3e, NVLink in-node) for large-model training and high-throughput inference, wired with a low-latency InfiniBand fabric. It runs traditional FP64/MPI HPC and large-model AI on one cluster, on-premises, in INR, on a GST invoice. Engineered for engineering, research and analytics teams that need real HPC throughput with serious AI, it is delivered racked, cabled, scheduled and validated as a single system — RDP sizes the nodes, fabric, parallel storage, scheduler and cooling, with one warranty and one support contract. Key highlights 3072 EPYC cores across 16 nodes — serious CPU throughput for FP64, MPI and memory-bound HPC. 64× H200 · 9,024 GB HBM3e — GPU acceleration for large-model AI training and inference alongside HPC. InfiniBand NDR fabric — low-latency, high-bandwidth interconnect for tightly-coupled MPI jobs and collectives. 16 TB DDR5 ECC + 960 TB NVMe parallel NVMe — large memory and a high-throughput parallel filesystem. Scheduler-ready, turnkey — delivered with Slurm/Kubernetes, validated; one SKU, one warranty. On-prem data sovereignty — codes, data and models stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Scale path — grow node count and step up the accelerator as workloads demand. AI workload fit (what it actually runs — honestly) HPC + simulation (primary): FP64/MPI workloads — CFD, FEA, molecular dynamics, EDA, risk and Monte-Carlo — across 3072 cores. AI training & inference: train and fine-tune large models across the NVLink-connected H200 GPUs, and serve them at high throughput alongside HPC jobs. RAG & agentic: production AI services co-located with HPC for engineering and research teams. Engineering note: each node’s H200 GPUs are NVLink-connected for efficient in-node tensor parallelism, and nodes scale over InfiniBand — this cluster trains and serves large models alongside FP64 HPC. The CPU cores carry the simulation/MPI side; the GPUs carry the AI side. AI workload positi" }, { "type": "product", "title": "DRACO 8-Node H200 HPC Cluster", "url": "https://rdp.in/gpu-mart/product/draco-8-node-h200-hpc-cluster/", "sku": "858948", "text": "DRACO 8-Node H200 HPC Cluster. SKU 858948. 8 nodes · 16× AMD EPYC 9005 (1,536 cores) · 8 TB DDR5 ECC · 32× H200 · 480 TB NVMe · InfiniBand · liquid/air . The DRACO 8-Node H200 HPC Cluster is a turnkey 8-node HPC cluster pairing CPU-forward compute with GPU acceleration — 1536 AMD EPYC cores across 8 nodes plus H200 accelerators (4,512 GB HBM3e HBM3e, NVLink in-node) for large-model training and high-throughput inference, wired with a low-latency InfiniBand fabric. It runs traditional FP64/MPI HPC and large-model AI on one cluster, on-premises, in INR, on a GST invoice. Engineered for engineering, research and analytics teams that need real HPC throughput with serious AI, it is delivered racked, cabled, scheduled and validated as a single system — RDP sizes the nodes, fabric, parallel storage, scheduler and cooling, with one warranty and one support contract. Key highlights 1536 EPYC cores across 8 nodes — serious CPU throughput for FP64, MPI and memory-bound HPC. 32× H200 · 4,512 GB HBM3e — GPU acceleration for large-model AI training and inference alongside HPC. InfiniBand NDR fabric — low-latency, high-bandwidth interconnect for tightly-coupled MPI jobs and collectives. 8 TB DDR5 ECC + 480 TB NVMe parallel NVMe — large memory and a high-throughput parallel filesystem. Scheduler-ready, turnkey — delivered with Slurm/Kubernetes, validated; one SKU, one warranty. On-prem data sovereignty — codes, data and models stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Scale path — grow node count and step up the accelerator as workloads demand. AI workload fit (what it actually runs — honestly) HPC + simulation (primary): FP64/MPI workloads — CFD, FEA, molecular dynamics, EDA, risk and Monte-Carlo — across 1536 cores. AI training & inference: train and fine-tune large models across the NVLink-connected H200 GPUs, and serve them at high throughput alongside HPC jobs. RAG & agentic: production AI services co-located with HPC for engineering and research teams. Engineering note: each node’s H200 GPUs are NVLink-connected for efficient in-node tensor parallelism, and nodes scale over InfiniBand — this cluster trains and serves large models alongside FP64 HPC. The CPU cores carry the simulation/MPI side; the GPUs carry the AI side. AI workload positioning Th" }, { "type": "product", "title": "DRACO 32-Node L40S HPC Cluster", "url": "https://rdp.in/gpu-mart/product/draco-32-node-l40s-hpc-cluster/", "sku": "728703", "text": "DRACO 32-Node L40S HPC Cluster. SKU 728703. 32 nodes · 64× AMD EPYC 9005 (6,144 cores) · 24 TB DDR5 ECC · 128× L40S · 960 TB NVMe · InfiniBand · liquid/air . The DRACO 32-Node L40S HPC Cluster is a turnkey 32-node HPC cluster pairing CPU-forward compute with GPU acceleration — 6144 AMD EPYC cores across 32 nodes plus L40S accelerators (6,144 GB GDDR6) for AI inference, fine-tuning and visualisation, wired with a low-latency InfiniBand fabric. It runs traditional FP64/MPI HPC and applied AI on one cluster, on-premises, in INR, on a GST invoice. Engineered for engineering, research and analytics teams that need real HPC throughput with AI on the side, it is delivered racked, cabled, scheduled and validated as a single system — RDP sizes the nodes, fabric, parallel storage, scheduler and cooling, with one warranty and one support contract. Key highlights 6144 EPYC cores across 32 nodes — serious CPU throughput for FP64, MPI and memory-bound HPC. 128× L40S · 6,144 GB GDDR6 — GPU acceleration for AI inference, fine-tuning and visualisation alongside HPC. InfiniBand NDR fabric — low-latency, high-bandwidth interconnect for tightly-coupled MPI jobs and collectives. 24 TB DDR5 ECC + 960 TB NVMe parallel NVMe — large memory and a high-throughput parallel filesystem. Scheduler-ready, turnkey — delivered with Slurm/Kubernetes, validated; one SKU, one warranty. On-prem data sovereignty — codes, data and models stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Scale path — grow node count and step up the accelerator as workloads demand. AI workload fit (what it actually runs — honestly) HPC + simulation (primary): FP64/MPI workloads — CFD, FEA, molecular dynamics, EDA, risk and Monte-Carlo — across 6144 cores. AI inference & visualisation: serve and fine-tune mid-size models, render and run mixed-precision AI alongside HPC jobs. RAG & agentic: production AI services co-located with HPC for engineering and research teams. Engineering note: the L40S (48 GB, no NVLink) is an Ada-generation accelerator built for inference, fine-tuning and visualisation — not large-model pre-training. For heavy training, choose the H200 node variant or a GPU Server/SuperCluster. This cluster’s strength is balanced CPU-HPC + accelerated AI. AI workload positioning This sits at the" }, { "type": "product", "title": "DRACO 8-Node L40S HPC Cluster", "url": "https://rdp.in/gpu-mart/product/draco-8-node-l40s-hpc-cluster/", "sku": "180924", "text": "DRACO 8-Node L40S HPC Cluster. SKU 180924. 8 nodes · 16× AMD EPYC 9005 (1,536 cores) · 6 TB DDR5 ECC · 32× L40S · 240 TB NVMe · InfiniBand · liquid/air . The DRACO 8-Node L40S HPC Cluster is a turnkey 8-node HPC cluster that pairs CPU-forward compute with GPU acceleration — 1536 AMD EPYC cores across 8 nodes plus 32× L40S accelerators (1,536 GB GDDR6), wired with a low-latency InfiniBand fabric. It runs traditional FP64/MPI HPC and mixed AI on one cluster, on-premises, in INR, on a GST invoice. Engineered for engineering, research and analytics teams that need real HPC throughput with AI on the side, it is delivered racked, cabled, scheduled and validated as a single system — RDP sizes the nodes, fabric, parallel storage, scheduler and cooling, with one warranty and one support contract. Key highlights 1536 EPYC cores across 8 nodes — serious CPU throughput for FP64, MPI and memory-bound HPC. 32× L40S · 1,536 GB GDDR6 — GPU acceleration for AI inference, training and visualisation alongside HPC. InfiniBand NDR fabric — low-latency, high-bandwidth interconnect for tightly-coupled MPI jobs and collectives. 6 TB DDR5 ECC + 240 TB NVMe parallel NVMe — large memory and a high-throughput parallel filesystem for datasets and scratch. Scheduler-ready, turnkey — delivered with Slurm/Kubernetes, validated; one SKU, one warranty. On-prem data sovereignty — codes, data and models stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Scale path — grow node count and step up the accelerator (H200) as workloads demand. AI workload fit (what it actually runs — honestly) HPC + simulation (primary): FP64/MPI workloads — CFD, FEA, molecular dynamics, EDA, risk and Monte-Carlo — across 1536 cores. AI inference & visualisation: the L40S is an Ada-generation accelerator strong at inference, rendering and mixed-precision AI; serve and fine-tune mid-size models alongside HPC jobs. RAG & agentic: production AI services co-located with HPC for engineering and research teams. Engineering note: the L40S (48 GB, no NVLink) is built for inference, visualisation and mid-size AI — not large-model pre-training. For heavy training, choose the H200 node variant or a GPU Server/SuperCluster. This cluster’s strength is balanced CPU-HPC + accelerated AI. AI workload positioning This sit" }, { "type": "product", "title": "DRACO 8× B200 SXM GPU Server", "url": "https://rdp.in/gpu-mart/product/draco-8x-b200-sxm-gpu-server/", "sku": "526177", "text": "DRACO 8× B200 SXM GPU Server. SKU 526177. 2× Intel Xeon 6 · 3 TB DDR5 ECC · 60 TB NVMe · 8U rack . The DRACO 8× B200 SXM GPU Server is an Rack 8U HGX B200 rack server — the densest single-node Blackwell platform RDP builds. Eight NVIDIA B200 SXM (HGX B200) GPUs on one HGX baseboard deliver 1,440 GB HBM3e of HBM3e, linked by NVLink and NVSwitch into a single tightly-coupled accelerator with Blackwell FP4/FP8 throughput — sized to train and serve trillion-parameter-class models on one node, behind your firewall, in INR, on a GST invoice. Engineered for organisations standing up serious AI capability on-premises, it pairs the eight GPUs with a 2× Intel Xeon 6 host, 3 TB DDR5 ECC and 60 TB NVMe, with 8× 400G InfiniBand for scale-out, redundant power and liquid cooling — and full BMC/IPMI for lights-out operation. Key highlights 1,440 GB HBM3e of HBM3e across 8× B200 SXM — a single-node memory pool sized for trillion-parameter-class training and serving. NVLink + NVSwitch fabric — full all-to-all GPU bandwidth across all eight Blackwell GPUs for efficient tensor parallelism. Blackwell FP4/FP8 — next-generation throughput for training and high-efficiency inference at scale. 2× Intel Xeon 6 + 3 TB DDR5 ECC — high core count and memory bandwidth to feed eight Blackwell GPUs. Rack 8U, liquid-cooled, redundant PSU, BMC/IPMI — sustained clocks under full load, lights-out management. 60 TB NVMe + 8× InfiniBand NDR 400G — large local storage and a high-bandwidth scale-out fabric; no egress fees. On-prem data sovereignty — training data and weights stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. AI workload fit (what it actually runs — honestly) Training & fine-tuning: full pre-training and fine-tuning of very large (toward trillion-parameter) models, tensor- and pipeline-parallel across the eight NVSwitch-linked Blackwell GPUs. Inference: high-efficiency FP4/FP8 serving of the largest models, or many large models concurrently. RAG, vision, multimodal & agentic: production pipelines on the 60 TB NVMe and large multi-agent back-ends. Engineering note: all eight SXM GPUs share an NVLink+NVSwitch fabric for full all-to-all bandwidth — the configuration large-model training actually needs; for scale beyond one node, multiple units link over the 400G InfiniBand fabric" }, { "type": "product", "title": "DRACO 4× B200 SXM GPU Server", "url": "https://rdp.in/gpu-mart/product/draco-4x-b200-sxm-gpu-server/", "sku": "191978", "text": "DRACO 4× B200 SXM GPU Server. SKU 191978. 2× Intel Xeon 6 · 2 TB DDR5 ECC · 30 TB NVMe · 4U rack . The DRACO 4× B200 SXM GPU Server is a Rack 4U rack server that brings NVIDIA’s Blackwell generation into your own data centre. Four NVIDIA B200 SXM (HGX B200 baseboard) GPUs deliver 720 GB HBM3e of HBM3e, linked by NVLink and NVSwitch into one tightly-coupled accelerator with Blackwell’s FP4/FP8 throughput — sized to train and serve up to 405B-class models, behind your firewall, in INR, on a GST invoice. Engineered for AI platform teams adopting Blackwell on-prem, it pairs the four GPUs with a 2× Intel Xeon 6 host, 2 TB DDR5 ECC and 30 TB NVMe, with 400G InfiniBand for scale-out, redundant power and full BMC/IPMI — a liquid-cooled training node that racks and runs. Key highlights 720 GB HBM3e of HBM3e across 4× B200 SXM — Blackwell-generation memory and bandwidth to train and serve up to 405B-class models. NVLink + NVSwitch fabric — full all-to-all GPU bandwidth for efficient tensor-parallel training. Blackwell FP4/FP8 — next-generation throughput for both training and high-efficiency inference. 2× Intel Xeon 6 + 2 TB DDR5 ECC — high core count and memory bandwidth to feed four Blackwell GPUs. Rack 4U, liquid-cooled, redundant PSU, BMC/IPMI — sustained clocks, hot-swap drives, lights-out management. 30 TB NVMe + InfiniBand NDR 400G — fast local storage with a high-bandwidth scale-out fabric; no egress fees. On-prem data sovereignty — training data and weights stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. AI workload fit (what it actually runs — honestly) Training & fine-tuning: full and parameter-efficient training of 405B-class models, tensor- and pipeline-parallel across the four NVSwitch-linked Blackwell GPUs. Inference: high-efficiency FP4/FP8 serving of 405B-class models, or several large models concurrently. RAG, vision, multimodal & agentic: production pipelines on the 30 TB NVMe and multi-agent back-ends. Engineering note: the four SXM GPUs sit on an HGX B200 baseboard with NVLink + NVSwitch — full all-to-all bandwidth for tensor-parallel models; Blackwell’s FP4 path is most valuable for inference efficiency and large-model serving. AI workload positioning This sits at the train-and-serve stage with Blackwell-generation effi" }, { "type": "product", "title": "DRACO 4× H200 SXM GPU Server", "url": "https://rdp.in/gpu-mart/product/draco-4x-h200-sxm-gpu-server/", "sku": "838996", "text": "DRACO 4× H200 SXM GPU Server. SKU 838996. 2× Intel Xeon 6 · 1.5 TB DDR5 ECC · 30 TB NVMe · 4U rack . The DRACO 4× H200 SXM GPU Server is a Rack 4U rack server built to bring training and high-throughput inference into your own data centre. 4 NVIDIA H200 SXM5 (HGX H200 baseboard) GPUs deliver 564 GB HBM3e of high-bandwidth GPU memory in a dense, serviceable chassis — sized to train and serve 180B-class models, behind your firewall, in INR, on a GST invoice. Engineered for AI platform and MLOps teams standardising training and large-model serving on owned infrastructure, it pairs the GPUs with a 2× Intel Xeon 6 host, 1.5 TB DDR5 ECC and 30 TB NVMe, with redundant power and full BMC/IPMI remote management — a production node that racks and runs, not a repurposed desktop. Key highlights 564 GB HBM3e of GPU memory across 4× H200 SXM — train and serve 180B-class models on-prem. NVLink + NVSwitch fabric — full all-to-all GPU bandwidth for tensor-parallel models, ECC throughout. 2× Intel Xeon 6 + 1.5 TB DDR5 ECC — high core count and memory bandwidth to feed 4 data-centre GPUs. Rack 4U, redundant PSU, BMC/IPMI — hot-swap drives, tool-less service, lights-out management. 30 TB NVMe + InfiniBand NDR 400G — fast dataset, checkpoint and weight storage with high-throughput networking; no egress fees. On-prem data sovereignty — data and weights stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Scale path — grow within the DRACO server line and out to RDP rack-scale systems as demand rises. AI workload fit (what it actually runs — honestly) Training & fine-tuning: full and parameter-efficient (QLoRA/LoRA) fine-tuning and training of 180B-class models, with tensor- and data-parallelism across the GPUs. Inference: serve 180B-class models at high throughput, or host several large models concurrently. RAG, vision, multimodal & agentic: production RAG endpoints, vision/multimodal inference and multi-agent back-ends on the 30 TB NVMe. Engineering note: the 4 SXM GPUs sit on an HGX baseboard with NVLink + NVSwitch — full all-to-all GPU bandwidth for efficient tensor-parallel training of the largest models, exactly what frontier-scale training needs. AI workload positioning This sits at the train-and-serve stage of the AI lifecycle. With 564 GB HBM3e of GPU memory, an NVLin" }, { "type": "product", "title": "QUASAR 8× RTX PRO 6000 Blackwell GPU Server", "url": "https://rdp.in/gpu-mart/product/quasar-8x-rtx-pro-6000-blackwell-gpu-server/", "sku": "695950", "text": "QUASAR 8× RTX PRO 6000 Blackwell GPU Server. SKU 695950. 2× Intel Xeon 6 · 2 TB DDR5 ECC · 30 TB NVMe · 4U rack . The QUASAR 8× RTX PRO 6000 Blackwell GPU Server is a Rack 4U rack server built to bring inference into your own data centre. 8 RTX PRO 6000 Blackwell Server Edition GPUs deliver 768 GB GDDR7 of high-bandwidth GPU memory in a dense, serviceable chassis — sized to serve 70B+ at scale-class models and host many models at once, behind your firewall, in INR, on a GST invoice. Engineered for AI platform and MLOps teams standardising production inference on owned infrastructure, it pairs the GPUs with a 2× Intel Xeon 6 host, 2 TB DDR5 ECC and 30 TB NVMe, with redundant power and full BMC/IPMI remote management — a production node that racks and runs, not a repurposed desktop. Key highlights 768 GB GDDR7 of GPU memory across 8× RTX PRO 6000 Blackwell — serve 70B+ at scale-class models or host many smaller models concurrently. Blackwell architecture with FP4 — next-generation inference efficiency and accuracy, ECC throughout. 2× Intel Xeon 6 + 2 TB DDR5 ECC — high core count and memory bandwidth to feed 8 data-centre GPUs. Rack 4U, redundant PSU, BMC/IPMI — hot-swap drives, tool-less service, lights-out management. 30 TB NVMe + 2× 100 GbE — fast dataset, checkpoint and weight storage with high-throughput networking; no egress fees. On-prem data sovereignty — data and weights stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Scale path — grow within the QUASAR server line and out to RDP rack-scale systems as demand rises. AI workload fit (what it actually runs — honestly) Inference (primary): serve 70B+ at scale-class models, or host multiple 7B–34B models concurrently for high aggregate throughput. Fine-tuning: QLoRA / LoRA up to ~70B+ and full fine-tuning of 7B-class models, data-parallel across the GPUs. RAG, vision, multimodal & agentic: production RAG endpoints, vision/multimodal inference and multi-agent back-ends on the 30 TB NVMe. Engineering note: the RTX PRO 6000 Blackwell Server Edition is a PCIe card with no NVLink — the 8 GPUs are ideal for data-parallel serving and multi-instance hosting; for a single model larger than 96 GB, use tensor parallelism across cards, or step up to an SXM/NVLink node. A production serving workhorse, not a la" }, { "type": "product", "title": "DRACO 8× H200 NVL GPU Server", "url": "https://rdp.in/gpu-mart/product/draco-8x-h200-nvl-gpu-server/", "sku": "876046", "text": "DRACO 8× H200 NVL GPU Server. SKU 876046. 2× AMD EPYC 9005 · 2 TB DDR5 ECC · 30 TB NVMe · 5U rack . The DRACO 8× H200 NVL GPU Server is a Rack 5U rack server built to bring training and high-throughput inference into your own data centre. 8 NVIDIA H200 NVL GPUs deliver 1,128 GB HBM3e of high-bandwidth GPU memory in a dense, serviceable chassis — sized to train and serve 180B+-class models, behind your firewall, in INR, on a GST invoice. Engineered for AI platform and MLOps teams standardising training and large-model serving on owned infrastructure, it pairs the GPUs with a 2× AMD EPYC 9005 host, 2 TB DDR5 ECC and 30 TB NVMe, with redundant power and full BMC/IPMI remote management — a production node that racks and runs, not a repurposed desktop. Key highlights 1,128 GB HBM3e of GPU memory across 8× H200 NVL — train and serve 180B+-class models on-prem. NVLink-bridged GPUs — fast GPU-to-GPU transfer for efficient tensor parallelism, ECC throughout. 2× AMD EPYC 9005 + 2 TB DDR5 ECC — high core count and memory bandwidth to feed 8 data-centre GPUs. Rack 5U, redundant PSU, BMC/IPMI — hot-swap drives, tool-less service, lights-out management. 30 TB NVMe + InfiniBand NDR 400G — fast dataset, checkpoint and weight storage with high-throughput networking; no egress fees. On-prem data sovereignty — data and weights stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Scale path — grow within the DRACO server line and out to RDP rack-scale systems as demand rises. AI workload fit (what it actually runs — honestly) Training & fine-tuning: full and parameter-efficient (QLoRA/LoRA) fine-tuning and training of 180B+-class models, with tensor- and data-parallelism across the GPUs. Inference: serve 180B+-class models at high throughput, or host several large models concurrently. RAG, vision, multimodal & agentic: production RAG endpoints, vision/multimodal inference and multi-agent back-ends on the 30 TB NVMe. Engineering note: the H200 NVL uses NVLink bridges between cards — much faster GPU-to-GPU than plain PCIe, though not the full all-to-all NVSwitch fabric of an SXM HGX node. For the densest tensor-parallel models, the SXM/HGX nodes are the step up. AI workload positioning This sits at the train-and-serve stage of the AI lifecycle. With 1,128 GB HBM3e of GPU memo" }, { "type": "product", "title": "QUASAR 4× RTX PRO 6000 Blackwell GPU Server", "url": "https://rdp.in/gpu-mart/product/quasar-4x-rtx-pro-6000-blackwell-gpu-server/", "sku": "778492", "text": "QUASAR 4× RTX PRO 6000 Blackwell GPU Server. SKU 778492. 2× Intel Xeon 6 · 1 TB DDR5 ECC · 16 TB NVMe · 4U rack . The QUASAR 4× RTX PRO 6000 Blackwell GPU Server is a Rack 4U rack server built to bring inference into your own data centre. 4 RTX PRO 6000 Blackwell Server Edition GPUs deliver 384 GB GDDR7 of high-bandwidth GPU memory in a dense, serviceable chassis — sized to serve 70B+-class models and host many models at once, behind your firewall, in INR, on a GST invoice. Engineered for AI platform and MLOps teams standardising production inference on owned infrastructure, it pairs the GPUs with a 2× Intel Xeon 6 host, 1 TB DDR5 ECC and 16 TB NVMe, with redundant power and full BMC/IPMI remote management — a production node that racks and runs, not a repurposed desktop. Key highlights 384 GB GDDR7 of GPU memory across 4× RTX PRO 6000 Blackwell — serve 70B+-class models or host many smaller models concurrently. Blackwell architecture with FP4 — next-generation inference efficiency and accuracy, ECC throughout. 2× Intel Xeon 6 + 1 TB DDR5 ECC — high core count and memory bandwidth to feed 4 data-centre GPUs. Rack 4U, redundant PSU, BMC/IPMI — hot-swap drives, tool-less service, lights-out management. 16 TB NVMe + 2× 25 GbE — fast dataset, checkpoint and weight storage with high-throughput networking; no egress fees. On-prem data sovereignty — data and weights stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Scale path — grow within the QUASAR server line and out to RDP rack-scale systems as demand rises. AI workload fit (what it actually runs — honestly) Inference (primary): serve 70B+-class models, or host multiple 7B–34B models concurrently for high aggregate throughput. Fine-tuning: QLoRA / LoRA up to ~70B+ and full fine-tuning of 7B-class models, data-parallel across the GPUs. RAG, vision, multimodal & agentic: production RAG endpoints, vision/multimodal inference and multi-agent back-ends on the 16 TB NVMe. Engineering note: the RTX PRO 6000 Blackwell Server Edition is a PCIe card with no NVLink — the 4 GPUs are ideal for data-parallel serving and multi-instance hosting; for a single model larger than 96 GB, use tensor parallelism across cards, or step up to an SXM/NVLink node. A production serving workhorse, not a large-scale training fabric. A" }, { "type": "product", "title": "DRACO 2× GB300 NVL72 Rack-Scale AI System", "url": "https://rdp.in/gpu-mart/product/draco-2x-gb300-nvl72-rack-scale-ai-system/", "sku": "110805", "text": "DRACO 2× GB300 NVL72 Rack-Scale AI System. SKU 110805. 2× GB300 NVL72 · 72× NVIDIA Grace (ARM) · Grace LPDDR5X coherent memory · 960 TB NVMe · Dual-Rack · liquid-cooled . The DRACO 2× GB300 NVL72 Rack-Scale AI System is a turnkey, liquid-cooled rack-scale AI system built on NVIDIA’s 2× GB300 NVL72 platform — 144 Grace-Blackwell Ultra GPUs joined in two coupled NVLink domains with 41,472 GB HBM3e of aggregate HBM3e. The racks behave as one enormous accelerator, sized to train and serve frontier-scale models on-premises — in INR, on a GST invoice. Engineered for national programmes, neoclouds and large enterprises building foundation-model capability in-house, it arrives racked, cabled, liquid-cooled and validated as a single SKU with one warranty and one support contract — RDP scopes the NVLink domain, InfiniBand spine, storage, power and cooling as one system so you don’t carry the integration risk. Key highlights 2× GB300 NVL72 · 41,472 GB HBM3e aggregate HBM3e — two unified NVLink domains of 144 Grace-Blackwell Ultra GPUs for frontier-scale training. Unified NVLink/NVSwitch domain — all GPUs in a rack act as a single accelerator; coherent Grace CPUs over NVLink-C2C; 400G+ InfiniBand spine for scale-out. 72× NVIDIA Grace (ARM) — Grace CPUs coherently attached to the Blackwell Ultra GPUs. 960 TB NVMe NVMe + parallel-FS ready — high-throughput data and checkpoint storage at frontier scale. Dual-Rack, liquid-cooled, turnkey — delivered racked, cabled, cooled and burned-in; one SKU, one warranty. On-prem data sovereignty — training data and weights stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Scale path — interconnect multiple systems into a multi-rack RDP AI SuperCluster. AI workload fit (what it actually runs — honestly) Frontier training: pre-train and fine-tune the largest (multi-hundred-billion to trillion-parameter) models, tensor-/pipeline-/data-parallel across the NVLink domain. Large-scale inference: serve the very largest models with the whole rack as one memory pool, or many large models concurrently. RAG, multimodal & agentic at scale: the most demanding production AI platforms. Engineering note: the defining feature of an NVL system is the unified NVLink domain — 144 GPUs addressed as one accelerator with coherent Grace memo" }, { "type": "product", "title": "DRACO GB200 NVL72 Rack-Scale AI System", "url": "https://rdp.in/gpu-mart/product/draco-gb200-nvl72-rack-scale-ai-system/", "sku": "438718", "text": "DRACO GB200 NVL72 Rack-Scale AI System. SKU 438718. GB200 NVL72 · 36× NVIDIA Grace (ARM) · Grace LPDDR5X coherent memory · 480 TB NVMe · Single-Rack (NVLink domain) · liquid-cooled . The DRACO GB200 NVL72 Rack-Scale AI System is a turnkey, liquid-cooled rack-scale AI system built on NVIDIA’s GB200 NVL72 platform — 72 Grace-Blackwell GPUs joined in a single NVLink domain with 13,824 GB HBM3e of aggregate HBM3e. The whole rack behaves as one enormous accelerator, sized to train and serve frontier-scale models on-premises — in INR, on a GST invoice. Engineered for national programmes, neoclouds and large enterprises building foundation-model capability in-house, it arrives racked, cabled, liquid-cooled and validated as a single SKU with one warranty and one support contract — RDP scopes the NVLink domain, InfiniBand spine, storage, power and cooling as one system so you don’t carry the integration risk. Key highlights GB200 NVL72 · 13,824 GB HBM3e aggregate HBM3e — one unified NVLink domain of 72 Grace-Blackwell GPUs for frontier-scale training. Unified NVLink/NVSwitch domain — all GPUs in a rack act as a single accelerator; coherent Grace CPUs over NVLink-C2C; 400G+ InfiniBand spine for scale-out. 36× NVIDIA Grace (ARM) — Grace CPUs coherently attached to the Blackwell GPUs. 480 TB NVMe NVMe + parallel-FS ready — high-throughput data and checkpoint storage at frontier scale. Single-Rack (NVLink domain), liquid-cooled, turnkey — delivered racked, cabled, cooled and burned-in; one SKU, one warranty. On-prem data sovereignty — training data and weights stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Scale path — interconnect multiple systems into a multi-rack RDP AI SuperCluster. AI workload fit (what it actually runs — honestly) Frontier training: pre-train and fine-tune the largest (multi-hundred-billion to trillion-parameter) models, tensor-/pipeline-/data-parallel across the NVLink domain. Large-scale inference: serve the very largest models with the whole rack as one memory pool, or many large models concurrently. RAG, multimodal & agentic at scale: the most demanding production AI platforms. Engineering note: the defining feature of an NVL system is the unified NVLink domain — 72 GPUs addressed as one accelerator with coherent Grace mem" }, { "type": "product", "title": "DRACO GB200 NVL36 Rack-Scale AI System", "url": "https://rdp.in/gpu-mart/product/draco-gb200-nvl36-rack-scale-ai-system/", "sku": "696670", "text": "DRACO GB200 NVL36 Rack-Scale AI System. SKU 696670. GB200 NVL36 · 18× NVIDIA Grace (ARM) · Grace LPDDR5X coherent memory · 240 TB NVMe · Single-Rack (NVLink domain) · liquid-cooled . The DRACO GB200 NVL36 Rack-Scale AI System is a turnkey, liquid-cooled single-rack (nvlink domain) AI training cluster delivering 6,912 GB HBM3e of aggregate HBM3e in a single unified NVLink domain. It arrives racked, cabled, cooled and validated — ready to train and serve the largest models on-premises, in INR, on a GST invoice. Engineered for organisations building serious in-house AI capacity, it removes the integration risk of assembling a cluster yourself: RDP sizes the NVLink domain, fabric, storage, power and cooling as one validated system delivered as a single SKU with one warranty and one support contract. Key highlights GB200 NVL36 · 6,912 GB HBM3e aggregate HBM3e — one unified NVLink memory domain for trillion-parameter training and serving. Unified NVLink domain, 400G InfiniBand spine — a single NVLink domain — all 36 Blackwell GPUs connected by NVLink/NVSwitch as one giant accelerator, with a 400G InfiniBand spine for scale-out. 18× NVIDIA Grace (ARM) coherently attached + Grace LPDDR5X coherent memory — host/CPU compute matched to 36 Blackwell GPUs. 240 TB NVMe NVMe + parallel-FS ready — high-throughput data and checkpoint storage across the system. Single-Rack (NVLink domain), liquid-cooled, turnkey — delivered racked, cabled, cooled and burned-in; one SKU, one warranty. On-prem data sovereignty — training data and weights stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Scale path — grow to multi-rack RDP AI SuperClusters on the same fabric. AI workload fit (what it actually runs — honestly) Distributed training: data-, tensor- and pipeline-parallel training of Trillion-scale-class models across the 36 GPUs. Large-scale inference: serve many large models, or shard the very largest models across the NVLink domain for high throughput. RAG, multimodal & agentic at scale: production AI platforms on the system’s storage and fabric. Engineering note: in an NVL system the 36 GPUs share one NVLink domain — they behave as a single large accelerator, which is what makes training the very largest models efficient; Grace CPUs are coherently attached to the GPU" }, { "type": "product", "title": "DRACO 64× B200 SXM Rack-Scale AI System", "url": "https://rdp.in/gpu-mart/product/draco-64x-b200-sxm-rack-scale-ai-system/", "sku": "209450", "text": "DRACO 64× B200 SXM Rack-Scale AI System. SKU 209450. 8-node HGX B200 · 16× Intel Xeon 6 · 16 TB DDR5 ECC · 480 TB NVMe · Full-Rack · liquid-cooled . The DRACO 64× B200 SXM Rack-Scale AI System is a turnkey, liquid-cooled full-rack AI training cluster delivering 11,520 GB HBM3e of aggregate HBM3e across 8 Blackwell HGX nodes. It arrives racked, cabled, cooled and validated — ready to train and serve the largest models on-premises, in INR, on a GST invoice. Engineered for organisations building serious in-house AI capacity, it removes the integration risk of assembling a cluster yourself: RDP sizes the nodes, fabric, storage, power and cooling as one validated system delivered as a single SKU with one warranty and one support contract. Key highlights 64× B200 SXM · 11,520 GB HBM3e aggregate HBM3e — cluster-scale GPU memory for trillion-parameter training and serving. NVLink + NVSwitch per node, 400G InfiniBand spine — NVLink + NVSwitch inside each HGX node and a 400G InfiniBand spine between the 8 nodes. 16× Intel Xeon 6 + 16 TB DDR5 ECC — host/CPU compute matched to 64 Blackwell GPUs. 480 TB NVMe NVMe + parallel-FS ready — high-throughput data and checkpoint storage across the system. Full-Rack, liquid-cooled, turnkey — delivered racked, cabled, cooled and burned-in; one SKU, one warranty. On-prem data sovereignty — training data and weights stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Scale path — grow to multi-rack RDP AI SuperClusters on the same fabric. AI workload fit (what it actually runs — honestly) Distributed training: data-, tensor- and pipeline-parallel training of Trillion-scale-class models across the 64 GPUs. Large-scale inference: serve many large models, or shard the very largest models across nodes for high throughput. RAG, multimodal & agentic at scale: production AI platforms on the system’s storage and fabric. Engineering note: within each HGX B200 node the eight GPUs share an NVLink+NVSwitch fabric; across nodes a 400G InfiniBand spine carries the all-reduce traffic. Real scaling efficiency depends on model and parallelism — we validate it for your workload rather than quoting peak FLOPS. AI workload positioning This sits at the cluster-scale train-and-serve stage: a complete, validated AI system rather than a single se" }, { "type": "product", "title": "DRACO 32× B200 SXM Rack-Scale AI System", "url": "https://rdp.in/gpu-mart/product/draco-32x-b200-sxm-rack-scale-ai-system/", "sku": "263701", "text": "DRACO 32× B200 SXM Rack-Scale AI System. SKU 263701. 4-node HGX B200 · 8× Intel Xeon 6 · 8 TB DDR5 ECC · 240 TB NVMe · Half-Rack · liquid-cooled . The DRACO 32× B200 SXM Rack-Scale AI System is a turnkey, liquid-cooled half-rack AI training cluster delivering 5,760 GB HBM3e of aggregate HBM3e across 4 Blackwell HGX nodes. It arrives racked, cabled, cooled and validated — ready to train and serve the largest models on-premises, in INR, on a GST invoice. Engineered for organisations building serious in-house AI capacity, it removes the integration risk of assembling a cluster yourself: RDP sizes the nodes, fabric, storage, power and cooling as one validated system delivered as a single SKU with one warranty and one support contract. Key highlights 32× B200 SXM · 5,760 GB HBM3e aggregate HBM3e — cluster-scale GPU memory for trillion-parameter training and serving. NVLink + NVSwitch per node, 400G InfiniBand spine — NVLink + NVSwitch inside each HGX node and a 400G InfiniBand spine between the 4 nodes. 8× Intel Xeon 6 + 8 TB DDR5 ECC — host/CPU compute matched to 32 Blackwell GPUs. 240 TB NVMe NVMe + parallel-FS ready — high-throughput data and checkpoint storage across the system. Half-Rack, liquid-cooled, turnkey — delivered racked, cabled, cooled and burned-in; one SKU, one warranty. On-prem data sovereignty — training data and weights stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Scale path — grow to multi-rack RDP AI SuperClusters on the same fabric. AI workload fit (what it actually runs — honestly) Distributed training: data-, tensor- and pipeline-parallel training of Trillion-scale-class models across the 32 GPUs. Large-scale inference: serve many large models, or shard the very largest models across nodes for high throughput. RAG, multimodal & agentic at scale: production AI platforms on the system’s storage and fabric. Engineering note: within each HGX B200 node the eight GPUs share an NVLink+NVSwitch fabric; across nodes a 400G InfiniBand spine carries the all-reduce traffic. Real scaling efficiency depends on model and parallelism — we validate it for your workload rather than quoting peak FLOPS. AI workload positioning This sits at the cluster-scale train-and-serve stage: a complete, validated AI system rather than a single server." }, { "type": "product", "title": "DRACO 32× H200 SXM Rack-Scale AI System", "url": "https://rdp.in/gpu-mart/product/draco-32x-h200-sxm-rack-scale-ai-system/", "sku": "547997", "text": "DRACO 32× H200 SXM Rack-Scale AI System. SKU 547997. 4-node HGX H200 · 8× Intel Xeon 6 · 8 TB DDR5 ECC · 240 TB NVMe · Half-Rack · liquid-cooled . The DRACO 32× H200 SXM Rack-Scale AI System is a turnkey, liquid-cooled half-rack AI training cluster — 32 NVIDIA H200 SXM GPUs across 4 HGX nodes, wired into one system with NVLink inside each node and a 400G InfiniBand spine between them. It delivers 4,512 GB HBM3e of aggregate HBM3e and arrives racked, cabled, cooled and tested, ready to train and serve the largest models on-premises — in INR, on a GST invoice. Engineered for organisations building serious in-house AI capacity, it removes the integration risk of assembling a cluster yourself: RDP sizes the nodes, fabric, storage, power and cooling as one validated system and delivers it as a single SKU with one warranty and one support contract. Key highlights 32× H200 SXM · 4,512 GB HBM3e aggregate HBM3e — cluster-scale GPU memory for trillion-token training and large-model serving. NVLink + NVSwitch in each node, 400G InfiniBand spine — full intra-node bandwidth and low-latency inter-node collectives for near-linear scaling. 8× Intel Xeon 6 + 8 TB DDR5 ECC — host compute and memory matched to 32 data-centre GPUs. 240 TB NVMe NVMe + parallel-FS ready — high-throughput data and checkpoint storage across the cluster. Half-Rack, liquid-cooled, turnkey — delivered racked, cabled, cooled and burned-in; one SKU, one warranty. On-prem data sovereignty — training data and weights stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Scale path — grow to larger rack-scale systems and multi-rack AI SuperClusters on the same fabric. AI workload fit (what it actually runs — honestly) Distributed training: data-, tensor- and pipeline-parallel training of Trillion-scale-class models across the 32 GPUs. Large-scale inference: serve many large models, or shard the largest models across nodes for high throughput. RAG, multimodal & agentic at scale: production AI platforms on the cluster’s storage and fabric. Engineering note: within each HGX node the eight GPUs share an NVLink+NVSwitch fabric; across nodes, a 400G InfiniBand spine carries the collective (all-reduce) traffic. Real-world scaling efficiency depends on model and parallelism strategy — we validate it for y" }, { "type": "product", "title": "DRACO 16× GB300 NVL72 AI SuperCluster", "url": "https://rdp.in/gpu-mart/product/draco-16x-gb300-nvl72-ai-supercluster/", "sku": "423579", "text": "DRACO 16× GB300 NVL72 AI SuperCluster. SKU 423579. 16× GB300 NVL72 · 576× NVIDIA Grace (ARM) · Grace LPDDR5X coherent memory · 16 PB parallel NVMe · 16-Rack SuperPOD · liquid-cooled . The DRACO 16× GB300 NVL72 AI SuperCluster is a turnkey, liquid-cooled GB300 NVL72 SuperPOD — 1152 Grace-Blackwell Ultra GPUs across 16 unified NVLink-domain racks, joined by a non-blocking spine-leaf InfiniBand fabric, delivering ~332 TB HBM3e of aggregate GPU memory. It arrives as a complete, validated AI factory — power, cooling, fabric, storage and software — ready to train frontier models on-premises, in INR, on a GST invoice. Engineered for sovereign-AI programmes, neoclouds and national-scale enterprises, it is delivered as a single engagement: RDP designs the reference architecture, integrates and burns it in, and hands over one validated SuperPOD with one warranty and one support contract — removing multi-vendor integration risk at frontier scale. Key highlights 16× GB300 NVL72 · ~332 TB HBM3e aggregate — 1152 Grace-Blackwell Ultra GPUs for the largest foundation-model training. Unified NVLink domains + non-blocking InfiniBand spine — each NVL72 rack is one 72-GPU accelerator; the racks scale over a full-bisection fabric. 576× NVIDIA Grace (ARM) (coherent) + Grace LPDDR5X coherent memory — Grace CPUs coherently attached to the Blackwell Ultra GPUs. 16 PB parallel NVMe parallel filesystem — high-throughput training data and checkpoint storage at SuperPOD scale. 16-Rack SuperPOD, liquid-cooled, turnkey — delivered racked, cabled, cooled, validated; one SKU, one warranty. On-prem data sovereignty — training data and weights stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Scale path — extend the fabric to multi-pod data halls. AI workload fit (what it actually runs — honestly) Frontier training: distributed pre-training of the largest foundation models across 1152 GPUs with 3D parallelism. Large-scale fine-tuning & serving: fine-tune and serve many large models in parallel, or shard the very largest across NVLink domains. RAG, multimodal & agentic platforms: national- or organisation-wide production AI on the SuperPOD’s storage and fabric. Engineering note: a GB300 SuperPOD combines unified NVLink domains (72 Blackwell Ultra GPUs each, 288 GB per GPU) over a" }, { "type": "product", "title": "DRACO 8× GB300 NVL72 AI SuperCluster", "url": "https://rdp.in/gpu-mart/product/draco-8x-gb300-nvl72-ai-supercluster/", "sku": "676547", "text": "DRACO 8× GB300 NVL72 AI SuperCluster. SKU 676547. 8× GB300 NVL72 · 288× NVIDIA Grace (ARM) · Grace LPDDR5X coherent memory · 8 PB parallel NVMe · 8-Rack SuperPOD · liquid-cooled . The DRACO 8× GB300 NVL72 AI SuperCluster is a turnkey, liquid-cooled GB300 NVL72 SuperPOD — 576 Grace-Blackwell Ultra GPUs across 8 unified NVLink-domain racks, joined by a non-blocking spine-leaf InfiniBand fabric, delivering ~166 TB HBM3e of aggregate GPU memory. It arrives as a complete, validated AI factory — power, cooling, fabric, storage and software — ready to train frontier models on-premises, in INR, on a GST invoice. Engineered for sovereign-AI programmes, neoclouds and national-scale enterprises, it is delivered as a single engagement: RDP designs the reference architecture, integrates and burns it in, and hands over one validated SuperPOD with one warranty and one support contract — removing multi-vendor integration risk at frontier scale. Key highlights 8× GB300 NVL72 · ~166 TB HBM3e aggregate — 576 Grace-Blackwell Ultra GPUs for the largest foundation-model training. Unified NVLink domains + non-blocking InfiniBand spine — each NVL72 rack is one 72-GPU accelerator; the racks scale over a full-bisection fabric. 288× NVIDIA Grace (ARM) (coherent) + Grace LPDDR5X coherent memory — Grace CPUs coherently attached to the Blackwell Ultra GPUs. 8 PB parallel NVMe parallel filesystem — high-throughput training data and checkpoint storage at SuperPOD scale. 8-Rack SuperPOD, liquid-cooled, turnkey — delivered racked, cabled, cooled, validated; one SKU, one warranty. On-prem data sovereignty — training data and weights stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Scale path — extend the fabric to multi-pod data halls. AI workload fit (what it actually runs — honestly) Frontier training: distributed pre-training of the largest foundation models across 576 GPUs with 3D parallelism. Large-scale fine-tuning & serving: fine-tune and serve many large models in parallel, or shard the very largest across NVLink domains. RAG, multimodal & agentic platforms: national- or organisation-wide production AI on the SuperPOD’s storage and fabric. Engineering note: a GB300 SuperPOD combines unified NVLink domains (72 Blackwell Ultra GPUs each, 288 GB per GPU) over a non-blocking" }, { "type": "product", "title": "DRACO 4× GB200 NVL72 AI SuperCluster", "url": "https://rdp.in/gpu-mart/product/draco-4x-gb200-nvl72-ai-supercluster/", "sku": "232676", "text": "DRACO 4× GB200 NVL72 AI SuperCluster. SKU 232676. 4× GB200 NVL72 · 144× NVIDIA Grace (ARM) · Grace LPDDR5X coherent memory · 4 PB parallel NVMe · 4-Rack SuperPOD · liquid-cooled . The DRACO 4× GB200 NVL72 AI SuperCluster is a turnkey, liquid-cooled NVL72 SuperPOD delivering ~55 TB HBM3e of aggregate GPU memory across 4× NVL72 racks. It arrives as a complete, validated system — power, cooling, fabric, storage and software — ready to train frontier models on-premises, in INR, on a GST invoice. Engineered for sovereign-AI programmes, neoclouds and large enterprises building data-hall-scale capacity, it is delivered as a single engagement: RDP designs the reference architecture, integrates and burns it in, and hands over one validated SuperPOD with one warranty and one support contract — removing multi-vendor integration risk. Key highlights 4× GB200 NVL72 · ~55 TB HBM3e aggregate — data-hall-scale GPU memory for training and serving the largest models. Unified NVLink domains + non-blocking InfiniBand spine — each NVL72 rack is a unified NVLink domain of 72 Grace-Blackwell GPUs; the 4× racks are joined by a non-blocking spine-leaf InfiniBand fabric. 144× NVIDIA Grace (ARM) (coherent) + Grace LPDDR5X coherent memory — host/CPU compute matched to 288 Blackwell GPUs. 4 PB parallel NVMe parallel filesystem — high-throughput training data and checkpoint storage at cluster scale. 4-Rack SuperPOD, liquid-cooled, turnkey — delivered racked, cabled, cooled, validated; one SKU, one warranty. On-prem data sovereignty — training data and weights stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Scale path — extend the fabric to larger SuperPODs and multi-pod data halls. AI workload fit (what it actually runs — honestly) Frontier training: distributed pre-training of large foundation models across the 288 GPUs with 3D parallelism. Large-scale fine-tuning & serving: fine-tune and serve many large models in parallel, or shard the very largest across the NVLink domains. RAG, multimodal & agentic platforms: organisation-wide production AI on the cluster’s storage and fabric. Engineering note: an NVL SuperPOD combines several unified NVLink domains (72 GPUs each) over a non-blocking InfiniBand spine — within a rack the GPUs act as one accelerator, across racks the sp" }, { "type": "product", "title": "DRACO 512× B200 SXM AI SuperCluster", "url": "https://rdp.in/gpu-mart/product/draco-512x-b200-sxm-ai-supercluster/", "sku": "526886", "text": "DRACO 512× B200 SXM AI SuperCluster. SKU 526886. 64× HGX nodes · 128× Intel Xeon 6 (64 nodes) · 128 TB DDR5 ECC · 8 PB parallel NVMe · 8-Rack pod · liquid-cooled . The DRACO 512× B200 SXM AI SuperCluster is a turnkey, liquid-cooled multi-rack AI supercluster delivering ~92 TB HBM3e of aggregate GPU memory across 64 HGX B200 nodes. It arrives as a complete, validated system — power, cooling, fabric, storage and software — ready to train frontier models on-premises, in INR, on a GST invoice. Engineered for sovereign-AI programmes, neoclouds and large enterprises building data-hall-scale capacity, it is delivered as a single engagement: RDP designs the reference architecture, integrates and burns it in, and hands over one validated supercluster with one warranty and one support contract — removing multi-vendor integration risk. Key highlights 512× B200 SXM · ~92 TB HBM3e aggregate — data-hall-scale GPU memory for training and serving the largest models. NVLink/NVSwitch per node + non-blocking InfiniBand spine — NVLink + NVSwitch within each HGX node, joined by a non-blocking spine-leaf InfiniBand fabric across the 64 nodes. 128× Intel Xeon 6 (64 nodes) + 128 TB DDR5 ECC — host/CPU compute matched to 512 Blackwell GPUs. 8 PB parallel NVMe parallel filesystem — high-throughput training data and checkpoint storage at cluster scale. 8-Rack pod, liquid-cooled, turnkey — delivered racked, cabled, cooled, validated; one SKU, one warranty. On-prem data sovereignty — training data and weights stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Scale path — extend the fabric to larger SuperPODs and multi-pod data halls. AI workload fit (what it actually runs — honestly) Frontier training: distributed pre-training of large foundation models across the 512 GPUs with 3D parallelism. Large-scale fine-tuning & serving: fine-tune and serve many large models in parallel, or shard the very largest across nodes. RAG, multimodal & agentic platforms: organisation-wide production AI on the cluster’s storage and fabric. Engineering note: at supercluster scale the network is the limiter, not a single GPU — a non-blocking spine-leaf InfiniBand fabric keeps collective (all-reduce) traffic scaling across 512 GPUs. Real efficiency depends on model and parallelism strategy; we r" }, { "type": "product", "title": "DRACO 256× B200 SXM AI SuperCluster", "url": "https://rdp.in/gpu-mart/product/draco-256x-b200-sxm-ai-supercluster/", "sku": "159289", "text": "DRACO 256× B200 SXM AI SuperCluster. SKU 159289. 32× HGX B200 nodes · 64× Intel Xeon 6 (32 nodes) · 64 TB DDR5 ECC · 4 PB parallel NVMe · 4-Rack pod · liquid-cooled . The DRACO 256× B200 SXM AI SuperCluster is a turnkey, liquid-cooled multi-rack AI supercluster — 256 NVIDIA B200 SXM GPUs across 32 HGX nodes in a 4-rack pod, wired with a non-blocking spine-leaf InfiniBand fabric. It delivers ~46 TB HBM3e of aggregate GPU memory and arrives as a complete, validated system — power, cooling, fabric, storage and software — ready to train frontier models on-premises, in INR, on a GST invoice. Engineered for sovereign-AI programmes, neoclouds and large enterprises building data-hall-scale capacity, it is delivered as a single engagement: RDP designs the reference architecture, integrates and burns it in, and hands over one validated supercluster with one warranty and one support contract — removing the multi-vendor integration risk of building it yourself. Key highlights 256× B200 SXM · ~46 TB HBM3e aggregate — data-hall-scale GPU memory for training and serving the largest models. Non-blocking spine-leaf InfiniBand (NDR/XDR) — full-bisection bandwidth for near-linear scaling across all 32 nodes. NVLink + NVSwitch within each node — full intra-node bandwidth, complemented by the InfiniBand spine between nodes. 64× Intel Xeon 6 (32 nodes) + 64 TB DDR5 ECC — host compute and memory matched to 256 data-centre GPUs. 4 PB parallel NVMe parallel filesystem — high-throughput training data and checkpoint storage at cluster scale. 4-Rack pod, liquid-cooled, turnkey — delivered racked, cabled, cooled, validated; one SKU, one warranty. On-prem data sovereignty — training data and weights stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. AI workload fit (what it actually runs — honestly) Frontier training: distributed pre-training of large foundation models across the 256 GPUs with 3D parallelism (data, tensor, pipeline). Large-scale fine-tuning & serving: fine-tune and serve many large models in parallel, or shard the very largest across nodes. RAG, multimodal & agentic platforms: production AI platforms for an entire organisation on the cluster’s storage and fabric. Engineering note: at supercluster scale the limiting factor is the network, not a single GPU — th" }, { "type": "product", "title": "DRACO 512× H200 SXM AI SuperCluster", "url": "https://rdp.in/gpu-mart/product/draco-512x-h200-sxm-ai-supercluster/", "sku": "478897", "text": "DRACO 512× H200 SXM AI SuperCluster. SKU 478897. 64× HGX H200 nodes · 128× Intel Xeon 6 (64 nodes) · 128 TB DDR5 ECC · 8 PB parallel NVMe · 8-Rack pod · liquid-cooled . The DRACO 512× H200 SXM AI SuperCluster is a turnkey, liquid-cooled multi-rack AI supercluster — 512 NVIDIA H200 SXM GPUs across 64 HGX nodes in a 8-rack pod, wired with a non-blocking spine-leaf InfiniBand fabric. It delivers ~72 TB HBM3e of aggregate GPU memory and arrives as a complete, validated system — power, cooling, fabric, storage and software — ready to train frontier models on-premises, in INR, on a GST invoice. Engineered for sovereign-AI programmes, neoclouds and large enterprises building data-hall-scale capacity, it is delivered as a single engagement: RDP designs the reference architecture, integrates and burns it in, and hands over one validated supercluster with one warranty and one support contract — removing the multi-vendor integration risk of building it yourself. Key highlights 512× H200 SXM · ~72 TB HBM3e aggregate — data-hall-scale GPU memory for training and serving the largest models. Non-blocking spine-leaf InfiniBand (NDR/XDR) — full-bisection bandwidth for near-linear scaling across all 64 nodes. NVLink + NVSwitch within each node — full intra-node bandwidth, complemented by the InfiniBand spine between nodes. 128× Intel Xeon 6 (64 nodes) + 128 TB DDR5 ECC — host compute and memory matched to 512 data-centre GPUs. 8 PB parallel NVMe parallel filesystem — high-throughput training data and checkpoint storage at cluster scale. 8-Rack pod, liquid-cooled, turnkey — delivered racked, cabled, cooled, validated; one SKU, one warranty. On-prem data sovereignty — training data and weights stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. AI workload fit (what it actually runs — honestly) Frontier training: distributed pre-training of large foundation models across the 512 GPUs with 3D parallelism (data, tensor, pipeline). Large-scale fine-tuning & serving: fine-tune and serve many large models in parallel, or shard the very largest across nodes. RAG, multimodal & agentic platforms: production AI platforms for an entire organisation on the cluster’s storage and fabric. Engineering note: at supercluster scale the limiting factor is the network, not a single GPU" }, { "type": "product", "title": "DRACO Infrastructure Financing and As-a-Service", "url": "https://rdp.in/gpu-mart/product/draco-infrastructure-financing-and-as-a-service/", "sku": "206811", "text": "DRACO Infrastructure Financing and As-a-Service. SKU 206811. Financing, lease and infrastructure-as-a-service · Per master service agreement · Pan-India · 1–5 years . The DRACO Infrastructure Financing and As-a-Service is a financing and as-a-service option for AI infrastructure from RDP — Financing, lease and infrastructure-as-a-service, delivered pan-india on a GST tax invoice in INR. It wraps your RDP GPU Mart infrastructure in the people, process and SLA that keep it running, so your team focuses on the AI, not the operations. It turns a large CapEx purchase into a predictable monthly OpEx — lease or consume RDP GPU Mart infrastructure as-a-service, with an option to scale capacity as demand grows. Key highlights Service: Financing, lease and infrastructure-as-a-service. SLA: Per master service agreement. Coverage: Pan-India. Engagement: OpEx — lease / pay-as-you-grow. Term: 1–5 years. Single point of contact — RDP owns the outcome end-to-end. Made-in-India OEM-direct — no third-party reseller layer between you and the people who built the hardware. GST invoice, INR billing, GeM-procurable. Scope of work Lease / EMI financing — spread the cost of hardware over the asset life. Infrastructure-as-a-service — consume capacity on a monthly basis, on-prem. Pay-as-you-grow — add nodes and capacity without re-procuring. Bundled support — AMC and managed operations can be folded into one OpEx line. How it works You choose a lease or as-a-service model; RDP deploys the infrastructure on your premises and bills a predictable monthly amount, with options to grow. Honest note: exact scope, response times and pricing are confirmed in the service agreement at quote — we do not quote SLAs we cannot staff for in your location. Industry use cases Government & PSU — SLA-backed operations and GeM-procurable contracts. BFSI — mission-critical uptime with audit-ready documentation. Healthcare — supported infrastructure under data-residency and continuity rules. Manufacturing & ITES — multi-site coverage and predictable OpEx. Neocloud & research — run-and-grow operations and flexible financing. SLA and how to be sure The commitment is Per master service agreement. Want certainty? Ask for a reference customer and a sample SLA report before you sign — we will show you how response, resolution and uptime are measured and reported. We do not promise SLAs we cannot meet in your reg" }, { "type": "product", "title": "QUASAR 5-Year Onsite AMC", "url": "https://rdp.in/gpu-mart/product/quasar-5-year-onsite-amc/", "sku": "178006", "text": "QUASAR 5-Year Onsite AMC. SKU 178006. Extended hardware support and maintenance (5-year AMC) · Same-day onsite response, optional onsite spares · Pan-India · 5 years . The QUASAR 5-Year Onsite AMC is a multi-year onsite support contract (5-year AMC) from RDP — Extended hardware support and maintenance (5-year AMC), delivered pan-india on a GST tax invoice in INR. It wraps your RDP GPU Mart infrastructure in the people, process and SLA that keep it running, so your team focuses on the AI, not the operations. It locks in five years of onsite support, spares and firmware management at a fixed cost — protecting long-life infrastructure against price drift and end-of-warranty risk. Key highlights Service: Extended hardware support and maintenance (5-year AMC). SLA: Same-day onsite response, optional onsite spares. Coverage: Pan-India. Engagement: Multi-year prepaid AMC. Term: 5 years. Single point of contact — RDP owns the outcome end-to-end. Made-in-India OEM-direct — no third-party reseller layer between you and the people who built the hardware. GST invoice, INR billing, GeM-procurable. Scope of work 5-year onsite break-fix — same-day engineer dispatch for the full term. Genuine spares — OEM parts guaranteed for the contract life, optional onsite kit. Proactive firmware & health — scheduled updates and annual health reviews. Lifecycle planning — refresh and capacity advice as the estate ages. How it works You prepay a five-year term; RDP guarantees same-day onsite support, spares and firmware management across the full asset life. Honest note: exact scope, response times and pricing are confirmed in the service agreement at quote — we do not quote SLAs we cannot staff for in your location. Industry use cases Government & PSU — SLA-backed support and GeM-procurable service contracts. BFSI — mission-critical uptime with audit-ready documentation. Healthcare — supported infrastructure under data-residency and continuity rules. Manufacturing & ITES — multi-site coverage and predictable OpEx. Research & higher-ed — long-life support for shared clusters on tight budgets. SLA and how to be sure The commitment is Same-day onsite response, optional onsite spares. Want certainty? Ask for a reference customer and a sample SLA report before you sign — we will show you how response, resolution and uptime are measured and reported. We do not promise SLAs we cannot meet in y" }, { "type": "product", "title": "CARINA Onsite Deployment & Commissioning", "url": "https://rdp.in/gpu-mart/product/carina-onsite-deployment-and-commissioning/", "sku": "219552", "text": "CARINA Onsite Deployment & Commissioning. SKU 219552. Deployment, installation and commissioning · Scheduled to an agreed project plan · Pan-India onsite · One-time (per deployment) . The CARINA Onsite Deployment & Commissioning is a one-time deployment and commissioning service from RDP — Deployment, installation and commissioning, delivered pan-india onsite on a GST tax invoice in INR. It wraps your RDP GPU Mart infrastructure in the people, process and SLA that keep it running, so your team focuses on the AI, not the operations. RDP engineers rack, cable, power, configure and validate your servers, storage, fabric and cooling on site, then hand over a tested, documented system — so day one is production, not a project. Key highlights Service: Deployment, installation and commissioning. SLA: Scheduled to an agreed project plan. Coverage: Pan-India onsite. Engagement: Fixed-fee, one-time engagement. Term: One-time (per deployment). Single point of contact — RDP owns the outcome end-to-end. Made-in-India OEM-direct — no third-party reseller layer between you and the people who built the hardware. GST invoice, INR billing, GeM-procurable. Scope of work Rack & stack — physical install, cabling, power and labelling to standard. Bring-up & firmware — BIOS/BMC, firmware baseline, network and storage configuration. Validation — burn-in, health checks and an acceptance test against a checklist. Handover — as-built documentation, asset register and knowledge transfer. How it works You schedule a window; RDP engineers deploy on site, validate to an acceptance checklist, and hand over a documented, production-ready system. Honest note: exact scope, response times and pricing are confirmed in the service agreement at quote — we do not quote SLAs we cannot staff for in your location. Industry use cases Government & PSU — SLA-backed support and GeM-procurable service contracts. BFSI — mission-critical uptime with audit-ready documentation. Healthcare — supported infrastructure under data-residency and continuity rules. Manufacturing & ITES — multi-site coverage and predictable OpEx. Research & higher-ed — long-life support for shared clusters on tight budgets. SLA and how to be sure The commitment is Scheduled to an agreed project plan. Want certainty? Ask for a reference customer and a sample SLA report before you sign — we will show you how response, resolution and upt" }, { "type": "product", "title": "DRACO Managed AI Software Platform", "url": "https://rdp.in/gpu-mart/product/draco-managed-ai-software-platform/", "sku": "145489", "text": "DRACO Managed AI Software Platform. SKU 145489. Managed AI software platform · On-prem (managed) · Cluster-wide · Annual subscription + managed service . The DRACO Managed AI Software Platform is a fully-managed AI software platform — the OS, GPU drivers, CUDA/ROCm, frameworks, inference servers and schedulers, pre-integrated, hardened and kept up to date by RDP, so your team runs models instead of maintaining a stack. It runs on-premises behind your firewall, in INR, on a GST invoice, and is delivered configured and validated with the RDP infrastructure it runs on. Engineered for AI/ML teams that want to skip stack-engineering, it delivers a maintained, secure, day-one-ready AI software environment, integrated with the rest of the RDP stack. Key highlights Managed AI software platform — a maintained OS + driver + CUDA/ROCm + framework + inference-server stack. On-prem (managed) — runs on-prem; models and data stay in-house. Cluster-wide — spans the cluster, licensed as a managed subscription. Kept up to date — RDP patches and updates drivers, CUDA and frameworks with tested releases. Day-one ready — frameworks, inference servers and a model zoo configured and tested. Integrations: NVIDIA/AMD stack, PyTorch/TensorFlow, vLLM/Triton, Slurm/Kubernetes. Validated with RDP infrastructure — delivered configured for your cluster. Make-in-India OEM — predictable INR pricing, GST tax invoice, pan-India support, GeM-procurable. What it does Maintained stack (primary): provides and maintains the full AI software stack on your cluster. Frameworks & inference: PyTorch/TensorFlow, vLLM/Triton/TensorRT-LLM, configured and tested. Security & updates: hardening, patching and tested release upgrades. Model & MLOps tooling: model zoo, registries and MLOps integration. How it works RDP installs, hardens and maintains the AI software stack on your cluster — OS, drivers, CUDA/ROCm, frameworks, inference servers and scheduler — delivering tested updates and support, so your team consumes a ready environment. RDP configures it for your cluster and integrates it with the RDP stack. Honest note: the managed scope and update cadence are defined in the service agreement. Industry use cases Neocloud / AI providers — a maintained software layer for a GPU cloud. Government & national labs — sovereign, maintained AI software. BFSI & enterprise — governed, supported AI platforms. Research &" }, { "type": "product", "title": "QUASAR DCIM Monitoring — up to 128 Nodes", "url": "https://rdp.in/gpu-mart/product/quasar-dcim-monitoring-up-to-128-nodes/", "sku": "316452", "text": "QUASAR DCIM Monitoring — up to 128 Nodes. SKU 316452. DCIM & cluster monitoring · On-prem · Up to 128 nodes · Per-node annual subscription . The QUASAR DCIM Monitoring — up to 128 Nodes gives operators a single pane of glass over the AI cluster — health, power, thermal and utilisation telemetry from servers, PDUs and CDUs, with alerting. It runs on-premises behind your firewall, in INR, on a GST invoice, and is delivered configured and validated with the RDP infrastructure it manages. Engineered for AI platform and operations teams, it turns raw infrastructure telemetry into actionable operations, integrated with the rest of the RDP stack. Key highlights DCIM & cluster monitoring — unified health, power, thermal and utilisation monitoring across the cluster. On-prem — runs on-prem; your data and telemetry never leave the site. Up to 128 nodes — sized for clusters of this scale, licensed per node. Proactive alerting — thresholds and anomaly alerts catch power/thermal issues before they cause downtime. Multi-tenant — role-based dashboards per team. Integrations: Redfish/IPMI, PDU, CDU, Prometheus/Grafana. Validated with RDP infrastructure — delivered configured for your cluster. Make-in-India OEM — predictable INR pricing, GST tax invoice, pan-India support, GeM-procurable. What it does Monitoring (primary): collect health, power, thermal and utilisation telemetry across servers, PDUs and CDUs. Alerting: thresholds, anomaly detection and notifications. Capacity planning: trends and reports for capacity and energy planning. Dashboards: role-based dashboards and historical analytics. How it works Agents and standard protocols (Redfish/IPMI, SNMP, PDU/CDU APIs) feed a time-series database and dashboards; rules engine raises alerts and the analytics layer reports trends. RDP configures it for your cluster topology and integrates it with the RDP stack. Honest note: real utilisation/observability depends on workload mix and configuration — we tune it for your cluster. Industry use cases Neocloud / AI providers — operations visibility across a GPU cloud. Government & national labs — sovereign cluster monitoring. BFSI & enterprise — shared AI platforms with governance. Research & higher-ed — fair-share access to shared clusters. Manufacturing & energy — managed HPC + AI operations. Telecom — large-scale cluster operations. Outcomes — and how to be sure The outcome is" }, { "type": "product", "title": "QUASAR Cluster Orchestration Suite", "url": "https://rdp.in/gpu-mart/product/quasar-cluster-orchestration-suite/", "sku": "755837", "text": "QUASAR Cluster Orchestration Suite. SKU 755837. Cluster orchestration & GPU scheduling · On-prem (bare-metal / Kubernetes) · Up to 1,024 nodes · Per-node annual subscription . The QUASAR Cluster Orchestration Suite schedules and orchestrates AI workloads across a GPU cluster — multi-tenant job queuing, GPU/MIG partitioning, fair-share and bin-packing so your expensive GPUs stay busy. It runs on-premises behind your firewall, in INR, on a GST invoice, and is delivered configured and validated with the RDP infrastructure it manages. Engineered for AI platform and operations teams, it turns a pile of GPU servers into a shared, well-utilised cluster, integrated with the rest of the RDP stack. Key highlights Cluster orchestration & GPU scheduling — job scheduling, GPU/MIG partitioning, queues and fair-share across tenants. On-prem (bare-metal / Kubernetes) — runs on-prem; your data and telemetry never leave the site. Up to 1,024 nodes — sized for clusters of this scale, licensed per node. High GPU utilisation — bin-packing and back-fill keep GPUs busy and reduce idle spend. Multi-tenant — isolate teams/projects with quotas and priorities. Integrations: Slurm, Kubernetes, NVIDIA GPU Operator, Prometheus. Validated with RDP infrastructure — delivered configured for your cluster. Make-in-India OEM — predictable INR pricing, GST tax invoice, pan-India support, GeM-procurable. What it does Scheduling (primary): queue, schedule and place AI jobs across the cluster with GPU-aware bin-packing. Partitioning: MIG/GPU partitioning and fractional GPUs for inference and dev. Multi-tenancy: quotas, priorities and fair-share across teams. Observability: job and GPU metrics for utilisation tracking. How it works A control plane runs the scheduler (Slurm and/or Kubernetes with a GPU operator), accepting jobs into queues, partitioning GPUs (MIG), and placing work to maximise utilisation while enforcing tenant quotas. RDP configures it for your cluster topology and integrates it with the RDP stack. Honest note: real utilisation/observability depends on workload mix and configuration — we tune it for your cluster. Industry use cases Neocloud / AI providers — multi-tenant GPU scheduling for a GPU cloud. Government & national labs — sovereign cluster scheduling. BFSI & enterprise — shared AI platforms with governance. Research & higher-ed — fair-share access to shared clusters. Manufa" }, { "type": "product", "title": "CARINA 2× L4 5G Edge AI Node", "url": "https://rdp.in/gpu-mart/product/carina-2x-l4-5g-edge-ai-node/", "sku": "977358", "text": "CARINA 2× L4 5G Edge AI Node. SKU 977358. Intel Xeon 6 · 128 GB DDR5 ECC · 4 TB NVMe · 48 GB GDDR6 · Short-depth 1U ruggedized . The CARINA 2× L4 5G Edge AI Node brings AI inference to the edge — a short-depth 1u ruggedized node with 2× NVIDIA L4 (48 GB GDDR6) built to run private, low-latency AI at the site where data is created with 5G connectivity for multi-access edge computing (MEC): a factory floor, retail store, hospital, branch, cell tower or 5G MEC site. Data never has to travel to the cloud; latency stays low and prompts stay in-house, in INR, on a GST invoice. Engineered for deployment outside a primary data centre, it fits short-depth and edge racks, runs the same software stack as RDP’s core servers, and ships with redundant power and BMC/IPMI for lights-out remote management of a fleet of sites. Key highlights 2× L4 · 48 GB GDDR6 — efficient AI inference and light fine-tuning at the edge. Short-depth 1U ruggedized — fits edge, retail and telco / 5G MEC racks where standard-depth servers won’t. Intel Xeon 6 + 128 GB DDR5 ECC — local pre/post-processing and orchestration without backhaul. 5G + 2× 25 GbE — 5G connectivity plus high-throughput Ethernet for MEC; data stays at the site. Redundant PSU, BMC/IPMI — remote power, console and health monitoring for unattended sites. Low-latency local inference — no round-trip to the cloud. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support for distributed estates, GeM-procurable. Fleet upgrade path — standardise the edge tier and scale the core with GPU servers and micro data centers. AI workload fit (what it actually runs — honestly) Edge inference (primary): serve quantised models and multiple small models locally for low-latency AI. Vision & multimodal: real-time defect detection, surveillance analytics and multimodal inference on local camera/sensor feeds. RAG & agentic: private, on-site RAG and agent back-ends over local document stores. Engineering note: the NVIDIA L4 (24 GB, low-power, single-slot) is built for inference and light fine-tuning, not large-model training — it is the right tool for low-power, low-latency edge AI. For heavy training, use a GPU Server or rack-scale system at the core. AI workload positioning This sits at the deploy-at-the-edge stage: the node you put where data is generated to keep latency low and data resident. W" }, { "type": "product", "title": "QUASAR 8× L40S Micro Data Center Pod", "url": "https://rdp.in/gpu-mart/product/quasar-8x-l40s-micro-data-center-pod/", "sku": "842306", "text": "QUASAR 8× L40S Micro Data Center Pod. SKU 842306. 8× L40S · 4× Intel Xeon 6 · 1 TB DDR5 ECC · 80 TB NVMe · Half-rack self-contained enclosure · Integrated in-row cooling + UPS . The QUASAR 8× L40S Micro Data Center Pod is a turnkey, self-contained AI data centre in an enclosure — 8× NVIDIA L40S (384 GB GDDR6) pre-integrated with integrated in-row cooling, UPS, power distribution, physical security and remote monitoring. It deploys AI compute where there is no built data centre: a factory, warehouse, branch, campus or remote site. You roll it in, connect power and network, and run private AI on-premises, in INR, on a GST invoice. Engineered to remove the need to build a server room, it bundles the GPU servers, networking, integrated in-row cooling, battery backup and DCIM monitoring into one validated, lockable enclosure — delivered, integrated and burned-in as a single SKU with one warranty and one support contract. Key highlights 8× L40S · 384 GB GDDR6 — real AI capacity for inference and fine-tuning, anywhere. Self-contained enclosure — GPU servers, networking, integrated in-row cooling, UPS, PDU, fire suppression and physical security in one lockable unit. No server room required — deploy in a warehouse, campus, branch or remote site with just power and network. 4× Intel Xeon 6 + 1 TB DDR5 ECC — host compute and memory matched to 8 GPUs. 80 TB NVMe NVMe + 2× 25 GbE — local storage and high-throughput networking. DCIM remote monitoring + BMC/IPMI — full remote management of power, cooling, environment and compute. On-prem data sovereignty — data and models stay at the site; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. AI workload fit (what it actually runs — honestly) Local inference (primary): serve many models and run real-time vision at the site with low latency. Fine-tuning & RAG: QLoRA/LoRA fine-tuning and private on-site RAG. Vision, multimodal & agentic: production AI services co-located with operations. Engineering note: this is infrastructure plus compute — the NVIDIA L40S (48 GB, Ada inference) is sized for inference, fine-tuning and visualisation, not large-model pre-training. The value is a complete, self-cooled, battery-backed AI site you can place anywhere, not just the GPUs inside it. AI workload positioning This sits at the deploy-anywhere sta" }, { "type": "product", "title": "CARINA 1× L4 Edge AI Node", "url": "https://rdp.in/gpu-mart/product/carina-1x-l4-edge-ai-node/", "sku": "990698", "text": "CARINA 1× L4 Edge AI Node. SKU 990698. Intel Xeon 6 · 128 GB DDR5 ECC · 4 TB NVMe · 24 GB GDDR6 · Short-depth 1U . The CARINA 1× L4 Edge AI Node brings AI inference to the edge — a short-depth 1u node with 1× NVIDIA L4 (24 GB GDDR6) built to run private, low-latency AI at the site where data is created: a factory floor, retail store, hospital, branch or remote facility. Data never has to travel to the cloud; latency stays low and prompts stay in-house, in INR, on a GST invoice. Engineered for deployment outside a primary data centre, it fits short-depth and edge racks, runs the same software stack as RDP’s core servers, and ships with redundant power and BMC/IPMI for lights-out remote management of a fleet of sites. Key highlights 1× L4 · 24 GB GDDR6 — efficient AI inference and light fine-tuning at the edge. Short-depth 1U — fits edge, retail and branch racks where standard-depth servers won’t. Intel Xeon 6 + 128 GB DDR5 ECC — local pre/post-processing and orchestration without backhaul. 2× 10 GbE — high-throughput Ethernet; data stays at the site. Redundant PSU, BMC/IPMI — remote power, console and health monitoring for unattended sites. Low-latency local inference — no round-trip to the cloud. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support for distributed estates, GeM-procurable. Fleet upgrade path — standardise the edge tier and scale the core with GPU servers and micro data centers. AI workload fit (what it actually runs — honestly) Edge inference (primary): serve quantised models and multiple small models locally for low-latency AI. Vision & multimodal: real-time defect detection, surveillance analytics and multimodal inference on local camera/sensor feeds. RAG & agentic: private, on-site RAG and agent back-ends over local document stores. Engineering note: the NVIDIA L4 (24 GB, low-power, single-slot) is built for inference and light fine-tuning, not large-model training — it is the right tool for low-power, low-latency edge AI. For heavy training, use a GPU Server or rack-scale system at the core. AI workload positioning This sits at the deploy-at-the-edge stage: the node you put where data is generated to keep latency low and data resident. With 24 GB GDDR6 in a compact, remotely-managed chassis, it is sized to sustain real local inference where backhauling to the cloud is too slow, too" }, { "type": "product", "title": "DRACO Rack Integration & Deployment", "url": "https://rdp.in/gpu-mart/product/draco-rack-integration-and-deployment/", "sku": "109040", "text": "DRACO Rack Integration & Deployment. SKU 109040. Rack integration, deployment & commissioning · Per project (typ. 2–8 weeks) · Pan-India · Fixed-fee per project . RDP Rack Integration & Deployment turns boxes into a working AI cluster. Our engineers receive, rack, cable, power, cool, image and validate your GPU servers, networking, storage and PDUs — then hand over a tested, documented, production-ready deployment. It removes the integration risk and weeks of effort of standing up AI infrastructure yourself — delivered on-site, in INR, on a GST invoice. Engineered around RDP’s GPU servers, rack-scale systems, fabrics, storage and cooling, the service covers physical build, power and cooling connection, fabric bring-up, software imaging and burn-in, with a clean handover and documentation. Key highlights Turnkey build — racking, structured cabling, power and cooling connection, labelling and dressing. Fabric bring-up — InfiniBand/Ethernet fabric configuration, subnet manager, and validation. Software imaging — OS, NVIDIA/AMD stack, schedulers and the AI software stack pre-configured. Burn-in & validation — thermal, power and scaling tests before handover; issues fixed, not shipped. Documentation & handover — as-built diagrams, IPs, credentials process, runbook and acceptance. Pan-India onsite — RDP engineers at your site, with a clear SLA. Single accountable partner — one team for compute, fabric, storage, power and cooling. Make-in-India OEM — predictable INR pricing, GST tax invoice, GeM-procurable. What’s included Physical build: receive, inventory, rack, cable and power the hardware. Power & cooling: connect PDUs, UPS and liquid cooling (CDU/manifold) and verify. Network: bring up the fabric, configure the subnet manager/RoCE, validate bandwidth. Software: image nodes, install the AI stack and scheduler, configure storage. Validation & handover: burn-in, scaling test, documentation and sign-off. How it works We scope the deployment, schedule the on-site engagement, then build, cable, power, cool, image and validate the system — running thermal, power and scaling tests before a documented handover. RDP coordinates the whole stack so you get one accountable partner. Honest note: timeline and scope depend on cluster size and site readiness — we confirm both in the statement of work. Industry use cases Government & PSU — turnkey sovereign AI deplo" }, { "type": "product", "title": "DRACO 250 kW Power & UPS Block", "url": "https://rdp.in/gpu-mart/product/draco-250-kw-power-and-ups-block/", "sku": "869446", "text": "DRACO 250 kW Power & UPS Block. SKU 869446. 250 kW · 2N UPS + static transfer switch · 415V 3-phase, busway distribution · UPS + distribution block (floor-standing) . The DRACO 250 kW Power & UPS Block is the resilient power backbone for a GPU deployment — 250 kW of protected power with 2N UPS + static transfer switch, distributing clean, conditioned power to the racks. It keeps GPU servers running through utility dips and outages, and isolates the AI load from the grid — on-premises, in INR, on a GST invoice. Engineered to feed RDP’s GPU racks and rack-scale systems, it combines UPS, battery, a static transfer switch and busway distribution into one validated power block, delivered sized, installed and commissioned with the compute it powers. Key highlights 250 kW protected — conditioned, backed-up power for Feeds up to 6-8 dense racks. 2N UPS + static transfer switch — 2N UPS topology with a static transfer switch for seamless failover. 415V 3-phase, busway distribution — busway distribution to the racks, sized for AI loads. Battery autonomy — ride-through for utility dips and graceful shutdown on extended outages. Power quality — clean, conditioned power that protects expensive GPU hardware. Monitoring — BMS/DCIM integration, metering and alarms. Validated with RDP compute — delivered as part of a tested, powered deployment. Make-in-India OEM — predictable INR pricing, GST tax invoice, pan-India onsite support, GeM-procurable. Where it fits GPU deployment power (primary): the protected power source feeding a row of GPU racks. Resilient AI sites: ride-through and backup for uptime-critical AI. New build or retrofit: the power block between the grid and the racks. Edge/micro-DC: protected power for a self-contained site. How it works The block conditions and protects incoming power through a 2N UPS topology, with batteries for ride-through and a static transfer switch for seamless source failover, then distributes via busway to the racks. RDP sizes the block, batteries and distribution to your load and uptime target. Honest note: real autonomy depends on load and battery sizing — we size and validate it for your deployment. Industry use cases AI data centres — protected power for GPU rows. Government & PSU — resilient sovereign AI power on GeM. BFSI & healthcare — uptime-critical AI under compliance. Manufacturing & energy — protected power at sites w" }, { "type": "product", "title": "QUASAR 42U 33 kW AI Rack + PDU", "url": "https://rdp.in/gpu-mart/product/quasar-42u-33-kw-ai-rack-pdu/", "sku": "898800", "text": "QUASAR 42U 33 kW AI Rack + PDU. SKU 898800. 33 kW per rack · N+1 PDU (A/B feeds) · 415V 3-phase · Air · 42U rack . The QUASAR 42U 33 kW AI Rack + PDU is an AI-ready rack with intelligent power distribution — 33 kW per rack of capacity, N+1 PDU (A/B feeds), and metered PDUs sized for dense GPU servers. It is the physical and power foundation a GPU deployment sits in, delivered integrated, cabled and validated with the compute it houses — on-premises, in INR, on a GST invoice. Engineered to match RDP’s GPU servers and rack-scale systems, it provides the structure, power, cable management and airflow that high-density AI hardware needs, with metered, monitored power feeds. Key highlights 33 kW per rack — power capacity sized for dense GPU servers, not a generic IT rack. N+1 PDU (A/B feeds) — redundant, metered PDUs on A/B feeds for resilient power. 415V 3-phase — the right distribution for AI rack loads. 42U · 33 kW/rack — usable height and depth for GPU servers with proper cable management. Air — airflow management (blanking, containment) and rear-door-ready for higher density. Per-outlet metering — visibility into power draw per server for capacity planning. Validated with RDP compute — delivered as part of a tested, powered rack. Make-in-India OEM — predictable INR pricing, GST tax invoice, pan-India onsite support, GeM-procurable. Where it fits GPU server homes (primary): the rack and power that house and feed dense GPU servers. Rack-scale building block: the cabinet and PDU layer of a larger deployment. Retrofit or new build: standardise on AI-ready racks across a room. Edge/micro-DC: the powered enclosure for a self-contained site. How it works The rack provides structure, airflow management and cable routing for GPU servers; redundant metered PDUs distribute 415V 3-phase power on A/B feeds with per-outlet metering and monitoring. RDP sizes the rack, power and airflow to your server density and facility. Honest note: usable power per rack depends on your facility feed and cooling — we size and validate it for your room. Industry use cases AI data centres — house and power dense GPU servers. Government & PSU — sovereign AI infrastructure on GeM-procurable racks. BFSI & healthcare — compliant, metered power for on-prem AI. Manufacturing & energy — rugged, well-powered racks near operations. Research & higher-ed — standardised racks for shared clusters" }, { "type": "product", "title": "QUASAR 20× RTX PRO 6000 Blackwell Multi-Node System", "url": "https://rdp.in/gpu-mart/product/quasar-20x-rtx-pro-6000-blackwell-multi-node-system/", "sku": "596060", "text": "QUASAR 20× RTX PRO 6000 Blackwell Multi-Node System. SKU 596060. 10-node compute block · 20× Intel Xeon 6 (10 nodes) · 5 TB DDR5 ECC · 80 TB NVMe · 10-Node Block 8U · shared power & cooling . The QUASAR 20× RTX PRO 6000 Blackwell Multi-Node System is a dense 10-node compute block system that packs 20 RTX PRO 6000 Blackwell Server Edition GPUs (1,920 GB GDDR7) into one shared-infrastructure chassis with pooled power and cooling. It sits between a single GPU server and a rack-scale system — ideal for consolidating many inference and fine-tune workloads, or a small training fleet, into one efficient footprint on-premises, in INR, on a GST invoice. Engineered for platform teams who want density and serviceability, it shares power supplies, cooling and management across the nodes/blades, so you deploy more GPUs per rack-U with one management plane — delivered racked, cabled and validated as a single SKU with one warranty. Key highlights 20× RTX PRO 6000 Blackwell · 1,920 GB GDDR7 — high GPU density for consolidated inference, fine-tuning and small-scale training. 10-node compute block, shared power & cooling — more GPUs per rack-U with pooled PSUs and a single management plane. 20× Intel Xeon 6 (10 nodes) + 5 TB DDR5 ECC — host compute and memory matched to 20 GPUs. 80 TB NVMe NVMe + InfiniBand NDR 400G — fast local storage and a low-latency InfiniBand fabric for multi-node jobs. Hot-swap, serviceable — node/blade-level service, redundant shared PSUs, full BMC/IPMI. On-prem data sovereignty — data and models stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Scale path — add nodes/blades, or step up to rack-scale systems and SuperClusters. AI workload fit (what it actually runs — honestly) Consolidated inference (primary): host many models across 20 GPUs for high aggregate throughput with one management plane. Fine-tuning & small-scale training: data-parallel fine-tuning across nodes; multi-node training over the InfiniBand fabric. RAG, vision, multimodal & agentic: dense production AI services and multi-agent back-ends. Engineering note: the RTX PRO 6000 Blackwell Server Edition is a PCIe card with no NVLink ; GPUs are ideal for data-parallel serving and multi-instance hosting. Across nodes, the InfiniBand fabric carries collective traffic for distributed" }, { "type": "product", "title": "DRACO 40× RTX PRO 6000 Blackwell Multi-Node System", "url": "https://rdp.in/gpu-mart/product/draco-40x-rtx-pro-6000-blackwell-multi-node-system/", "sku": "997790", "text": "DRACO 40× RTX PRO 6000 Blackwell Multi-Node System. SKU 997790. 10-blade chassis · 20× Intel Xeon 6 (10 blades) · 10 TB DDR5 ECC · 160 TB NVMe · Blade Chassis 8U · shared power & cooling . The DRACO 40× RTX PRO 6000 Blackwell Multi-Node System is a dense 10-blade chassis system that packs 40 RTX PRO 6000 Blackwell Server Edition GPUs (3,840 GB GDDR7) into one shared-infrastructure chassis with pooled power and cooling. It sits between a single GPU server and a rack-scale system — ideal for consolidating many inference and fine-tune workloads, or a small training fleet, into one efficient footprint on-premises, in INR, on a GST invoice. Engineered for platform teams who want density and serviceability, it shares power supplies, cooling and management across the nodes/blades, so you deploy more GPUs per rack-U with one management plane — delivered racked, cabled and validated as a single SKU with one warranty. Key highlights 40× RTX PRO 6000 Blackwell · 3,840 GB GDDR7 — high GPU density for consolidated inference, fine-tuning and small-scale training. 10-blade chassis, shared power & cooling — more GPUs per rack-U with pooled PSUs and a single management plane. 20× Intel Xeon 6 (10 blades) + 10 TB DDR5 ECC — host compute and memory matched to 40 GPUs. 160 TB NVMe NVMe + InfiniBand NDR 400G — fast local storage and a low-latency InfiniBand fabric for multi-node jobs. Hot-swap, serviceable — node/blade-level service, redundant shared PSUs, full BMC/IPMI. On-prem data sovereignty — data and models stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Scale path — add nodes/blades, or step up to rack-scale systems and SuperClusters. AI workload fit (what it actually runs — honestly) Consolidated inference (primary): host many models across 40 GPUs for high aggregate throughput with one management plane. Fine-tuning & small-scale training: data-parallel fine-tuning across nodes; multi-node training over the InfiniBand fabric. RAG, vision, multimodal & agentic: dense production AI services and multi-agent back-ends. Engineering note: the RTX PRO 6000 Blackwell Server Edition is a PCIe card with no NVLink ; GPUs are ideal for data-parallel serving and multi-instance hosting. Across nodes, the InfiniBand fabric carries collective traffic for distributed jobs. This" }, { "type": "product", "title": "QUASAR 8× RTX PRO 6000 Blackwell Multi-Node System", "url": "https://rdp.in/gpu-mart/product/quasar-8x-rtx-pro-6000-blackwell-multi-node-system/", "sku": "248914", "text": "QUASAR 8× RTX PRO 6000 Blackwell Multi-Node System. SKU 248914. 2-node twin · 4× Intel Xeon 6 (2 nodes) · 1 TB DDR5 ECC · 16 TB NVMe · Twin 2-Node 2U · shared power & cooling . The QUASAR 8× RTX PRO 6000 Blackwell Multi-Node System is a dense 2-node twin system that packs 8 RTX PRO 6000 Blackwell Server Edition GPUs (768 GB GDDR7) into one shared-infrastructure chassis with pooled power and cooling. It sits between a single GPU server and a rack-scale system — ideal for consolidating many inference and fine-tune workloads, or a small training fleet, into one efficient footprint on-premises, in INR, on a GST invoice. Engineered for platform teams who want density and serviceability, it shares power supplies, cooling and management across the nodes/blades, so you deploy more GPUs per rack-U with one management plane — delivered racked, cabled and validated as a single SKU with one warranty. Key highlights 8× RTX PRO 6000 Blackwell · 768 GB GDDR7 — high GPU density for consolidated inference, fine-tuning and small-scale training. 2-node twin, shared power & cooling — more GPUs per rack-U with pooled PSUs and a single management plane. 4× Intel Xeon 6 (2 nodes) + 1 TB DDR5 ECC — host compute and memory matched to 8 GPUs. 16 TB NVMe NVMe + 2× 25 GbE — fast local storage and high-throughput networking. Hot-swap, serviceable — node/blade-level service, redundant shared PSUs, full BMC/IPMI. On-prem data sovereignty — data and models stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Scale path — add nodes/blades, or step up to rack-scale systems and SuperClusters. AI workload fit (what it actually runs — honestly) Consolidated inference (primary): host many models across 8 GPUs for high aggregate throughput with one management plane. Fine-tuning & small-scale training: data-parallel fine-tuning across nodes; per-node training. RAG, vision, multimodal & agentic: dense production AI services and multi-agent back-ends. Engineering note: the RTX PRO 6000 Blackwell Server Edition is a PCIe card with no NVLink ; GPUs are ideal for data-parallel serving and multi-instance hosting. For tightly-coupled large-model training, choose an SXM/NVLink rack-scale system. This system’s strength is density and consolidation, not single-model giant training. AI workload pos" }, { "type": "product", "title": "QUASAR Direct-Liquid Cooling Kit (1-Rack)", "url": "https://rdp.in/gpu-mart/product/quasar-direct-liquid-cooling-kit-1-rack/", "sku": "598465", "text": "QUASAR Direct-Liquid Cooling Kit (1-Rack). SKU 598465. Up to 80 kW (cold-plate) · Manifold-fed (quick-disconnect) · Direct-to-chip cold plates + manifold · PG25 / treated water · In-rack manifold + cold plates . The QUASAR Direct-Liquid Cooling Kit (1-Rack) removes the heat that dense GPU racks generate — Up to 80 kW (cold-plate) of cooling via direct-to-chip cold plates + manifold, so today’s 700 W–1 kW+ GPUs run at full clocks without thermal throttling. It is the thermal layer that makes high-density AI racks possible on-premises, in INR, on a GST invoice. Engineered to match RDP’s GPU servers, rack-scale systems and superclusters, it integrates with your facility water or chilled-water loop and is delivered sized, plumbed and validated with the compute it cools — with leak detection and monitoring built in. Key highlights Up to 80 kW (cold-plate) — direct-to-chip cooling for the hottest GPUs and CPUs. Direct-to-chip cold plates + manifold — cold plates sit directly on the silicon, the most efficient way to cool 1 kW GPUs. Manifold-fed (quick-disconnect) · PG25 / treated water — controlled flow and coolant chemistry for reliable, corrosion-safe operation. Leak detection & monitoring — sensors and BMS/DCIM integration for safe, observable operation. Supports 1 rack — sized to the density of RDP GPU racks. Quiet, efficient — liquid moves heat far more efficiently than air, lowering fan power and PUE. Validated with RDP compute — delivered as part of a tested, cooled rack. Make-in-India OEM — predictable INR pricing, GST tax invoice, pan-India onsite support, GeM-procurable. Where it fits Dense GPU racks (primary): cools the GPUs/CPUs directly in liquid-cooled servers. Rack-scale & NVL systems: the cooling that keeps NVL72-class racks within thermal limits. Retrofit or new build: design a liquid-cooled hall from the start. Edge/micro-DC: sealed/compact options for self-contained sites. How it works Cold plates mounted on the GPUs and CPUs carry heat into a coolant loop via quick-disconnects and a manifold; the loop rejects heat to a CDU or facility water. RDP sizes the loop, flow and coolant to your rack density and facility. Honest note: real cooling capacity depends on inlet water temperature, flow and rack layout — we size and validate it for your room. Industry use cases AI data centres — cool dense GPU and NVL racks at full clocks. Governmen" }, { "type": "product", "title": "QUASAR 100 kW In-Row CDU", "url": "https://rdp.in/gpu-mart/product/quasar-100-kw-in-row-cdu/", "sku": "710001", "text": "QUASAR 100 kW In-Row CDU. SKU 710001. 100 kW · Up to 160 L/min · Liquid-to-air CDU (in-row) · PG25 / treated water · In-row (full-height) . The QUASAR 100 kW In-Row CDU removes the heat that dense GPU racks generate — 100 kW of cooling via liquid-to-air cdu (in-row), so today’s 700 W–1 kW+ GPUs run at full clocks without thermal throttling. It is the thermal layer that makes high-density AI racks possible on-premises, in INR, on a GST invoice. Engineered to match RDP’s GPU servers, rack-scale systems and superclusters, it integrates with your facility water or chilled-water loop and is delivered sized, plumbed and validated with the compute it cools — with leak detection and monitoring built in. Key highlights 100 kW — rack/row-level coolant distribution. Liquid-to-air CDU (in-row) — distributes treated coolant to cold-plate loops with filtration and control. Up to 160 L/min · PG25 / treated water — controlled flow and coolant chemistry for reliable, corrosion-safe operation. Leak detection & monitoring — sensors and BMS/DCIM integration for safe, observable operation. Supports 1-2 racks — sized to the density of RDP GPU racks. Quiet, efficient — liquid moves heat far more efficiently than air, lowering fan power and PUE. Validated with RDP compute — delivered as part of a tested, cooled rack. Make-in-India OEM — predictable INR pricing, GST tax invoice, pan-India onsite support, GeM-procurable. Where it fits Dense GPU racks (primary): feeds direct-to-chip cold-plate loops across a rack or row. Rack-scale & NVL systems: the cooling that keeps NVL72-class racks within thermal limits. Retrofit or new build: design a liquid-cooled hall from the start. Edge/micro-DC: sealed/compact options for self-contained sites. How it works The unit isolates the rack coolant loop from facility water, controls flow, temperature and pressure, filters the coolant, and distributes it to the cold-plate loops. RDP sizes the loop, flow and coolant to your rack density and facility. Honest note: real cooling capacity depends on inlet water temperature, flow and rack layout — we size and validate it for your room. Industry use cases AI data centres — cool dense GPU and NVL racks at full clocks. Government & national labs — sovereign HPC/AI cooling. Neocloud / AI providers — higher density per rack, lower PUE. Manufacturing & energy — HPC + AI thermal management. Research" }, { "type": "product", "title": "QUASAR 40 kW Rear-Door Heat Exchanger", "url": "https://rdp.in/gpu-mart/product/quasar-40-kw-rear-door-heat-exchanger/", "sku": "207546", "text": "QUASAR 40 kW Rear-Door Heat Exchanger. SKU 207546. 40 kW per rack · Up to 80 L/min · Rear-door heat exchanger (air-assist liquid) · Facility/chilled water (PG25 optional) · Rear-door (42U) . The QUASAR 40 kW Rear-Door Heat Exchanger removes the heat that dense GPU racks generate — 40 kW per rack of cooling via rear-door heat exchanger (air-assist liquid), so today’s 700 W–1 kW+ GPUs run at full clocks without thermal throttling. It is the thermal layer that makes high-density AI racks possible on-premises, in INR, on a GST invoice. Engineered to match RDP’s GPU servers, rack-scale systems and superclusters, it integrates with your facility water or chilled-water loop and is delivered sized, plumbed and validated with the compute it cools — with leak detection and monitoring built in. Key highlights 40 kW per rack — rack-level heat removal at the door. Rear-door heat exchanger (air-assist liquid) — mounts on the rack rear door; no raised floor or CDU required for entry density. Up to 80 L/min · Facility/chilled water (PG25 optional) — controlled flow and coolant chemistry for reliable, corrosion-safe operation. Leak detection & monitoring — sensors and BMS/DCIM integration for safe, observable operation. Supports 1 rack — sized to the density of RDP GPU racks. Quiet, efficient — liquid moves heat far more efficiently than air, lowering fan power and PUE. Validated with RDP compute — delivered as part of a tested, cooled rack. Make-in-India OEM — predictable INR pricing, GST tax invoice, pan-India onsite support, GeM-procurable. Where it fits Dense GPU racks (primary): retrofits air-cooled racks to higher density without a liquid loop to the chip. Rack-scale & NVL systems: the cooling that keeps NVL72-class racks within thermal limits. Retrofit or new build: add density to an existing air-cooled room. Edge/micro-DC: sealed/compact options for self-contained sites. How it works A coil on the rack rear door captures hot exhaust air and rejects it to facility/chilled water — turning a standard rack into a higher-density one without plumbing the chips. RDP sizes the loop, flow and coolant to your rack density and facility. Honest note: real cooling capacity depends on inlet water temperature, flow and rack layout — we size and validate it for your room. Industry use cases AI data centres — cool dense GPU and NVL racks at full clocks. Government & natio" }, { "type": "product", "title": "DRACO 10 PB Object AI Storage", "url": "https://rdp.in/gpu-mart/product/draco-10-pb-object-ai-storage/", "sku": "979096", "text": "DRACO 10 PB Object AI Storage. SKU 979096. 10 PB usable (erasure-coded) · 50 GB/s aggregate · S3-compatible object (erasure-coded) · High-throughput Ethernet · Scale-out cluster . The DRACO 10 PB Object AI Storage is a scale-out, S3-compatible object storage platform for the AI data lifecycle — 10 PB usable (erasure-coded) of durable capacity for datasets, model registries, checkpoint archives and warm/cold tiers. It gives AI teams a private, exabyte-scalable object store behind their firewall, in INR, on a GST invoice, so training data and model artefacts live in-house with cloud-like S3 access. Engineered as the capacity tier beneath the high-bandwidth NVMe parallel filesystem, it stores the bulk of AI data durably and cost-effectively with erasure coding, exposing the S3 API your pipelines and MLOps tools already use — delivered as one validated cluster with one warranty and one support contract. Key highlights 10 PB usable (erasure-coded) · S3-compatible — exabyte-scalable durable capacity with the S3 API your tools already speak. Erasure-coded durability — high data durability without full replication overhead. Hybrid NVMe + HDD, scale-out — hybrid NVMe + HDD scale-out for cost-effective capacity with fast metadata. High-throughput Ethernet — high-throughput access for many concurrent clients. Capacity tier for AI — pairs with the NVMe parallel-FS hot tier; stage hot data up, archive cold data down. On-prem data sovereignty — datasets and model artefacts stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Where it fits Dataset lake (primary): the durable, S3-accessible home for training datasets and raw data. Model registry & artefacts: versioned storage for model weights, checkpoints and experiment outputs. Warm/cold tier: the capacity tier beneath the NVMe hot tier; archive what isn’t being actively trained. Data sharing: S3 access for teams, pipelines and MLOps tooling across the org. How it works A scale-out object cluster stores data as S3 objects with erasure coding for durability, exposing the S3 API over High-throughput Ethernet. Capacity and durability scale by adding nodes. It pairs with the NVMe parallel-FS hot tier: stage active datasets up for high-bandwidth GPU feeding, keep the bulk durably here. Honest note: object storage is" }, { "type": "product", "title": "DRACO 500 TB Parallel-FS NVMe AI Storage", "url": "https://rdp.in/gpu-mart/product/draco-500-tb-parallel-fs-nvme-ai-storage/", "sku": "511566", "text": "DRACO 500 TB Parallel-FS NVMe AI Storage. SKU 511566. 500 TB usable (NVMe) · 320 GB/s read · Parallel FS (Lustre/GPFS-class) · 8× 200G InfiniBand/Ethernet · 4U (2-node) . The DRACO 500 TB Parallel-FS NVMe AI Storage is a scale-out parallel-filesystem NVMe storage system built to feed entire GPU clusters during large-scale AI training. It delivers 500 TB usable (NVMe) at 320 GB/s read with GPUDirect Storage across a clustered namespace, so datasets, checkpoints and weights stream to many GPU nodes in parallel without the storage becoming the bottleneck — on-premises, in INR, on a GST invoice. Engineered for cluster-scale AI/HPC data pipelines, it presents a single parallel namespace over high-speed networking and scales capacity and bandwidth together by adding nodes — delivered racked, configured and validated as one system with one warranty and one support contract. Key highlights 500 TB usable (NVMe) · 320 GB/s read — cluster-scale bandwidth sized to feed many GPU nodes during training. Parallel filesystem + GPUDirect Storage — a single namespace; data streams from NVMe straight to GPU memory across the cluster. Parallel FS (Lustre/GPFS-class) + NFS/S3, GPUDirect Storage — parallel and standard protocols so existing pipelines and schedulers just work. 48× 15.36 TB NVMe (2 nodes) — dense enterprise NVMe with end-to-end data integrity, scaling across nodes. 8× 200G InfiniBand/Ethernet — high-bandwidth networking to the GPU fabric; bandwidth grows with capacity. 20M random read — high aggregate random-read IOPS for metadata- and small-file-heavy AI datasets. On-prem data sovereignty — datasets and weights stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Where it fits Cluster training data lake (primary): the high-bandwidth tier that streams datasets to a GPU cluster in parallel without starving any node. Checkpoints & weights: fast parallel write/read of large checkpoints during long multi-node runs. RAG & vector stores: low-latency storage for large embeddings, indexes and retrieval corpora. HPC scratch: high-throughput scratch for simulation alongside AI. How it works A clustered parallel filesystem stripes data across NVMe nodes and presents one namespace over 8× 200G InfiniBand/Ethernet. With GPUDirect Storage, reads bypass the CPU and land direct" }, { "type": "product", "title": "QUASAR 100 TB All-Flash NVMe AI Storage", "url": "https://rdp.in/gpu-mart/product/quasar-100-tb-all-flash-nvme-ai-storage/", "sku": "645587", "text": "QUASAR 100 TB All-Flash NVMe AI Storage. SKU 645587. 100 TB usable (NVMe) · 80 GB/s read · Parallel FS + NFS/S3, GPUDirect Storage · 2× 200G InfiniBand/Ethernet · 2U . The QUASAR 100 TB All-Flash NVMe AI Storage is an all-flash NVMe storage system built to keep GPUs fed during AI training and inference. It delivers 100 TB usable (NVMe) at 80 GB/s read with GPUDirect Storage, so training data, checkpoints and model weights stream to the GPUs without the storage becoming the bottleneck — on-premises, in INR, on a GST invoice. Engineered for AI/ML data pipelines, it pairs dense NVMe with a parallel fs and high-speed networking, delivered racked, configured and validated as a single system with one warranty and one support contract. Key highlights 100 TB usable (NVMe) · 80 GB/s read — high-bandwidth flash sized to feed GPU clusters during training. GPUDirect Storage — data streams from NVMe straight to GPU memory, bypassing the CPU bounce for maximum throughput. Parallel FS + NFS/S3, GPUDirect Storage — parallel/standard protocols so existing pipelines and frameworks just work. 24× 7.68 TB NVMe — dense, enterprise NVMe with end-to-end data integrity. 2× 200G InfiniBand/Ethernet — high-speed networking to the GPU fabric; no I/O wall. 5M random read — high random-read IOPS for many small files and metadata-heavy AI datasets. On-prem data sovereignty — datasets and weights stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Where it fits Training data lake (primary): the high-bandwidth tier that streams datasets to GPU servers and clusters without starving them. Checkpoints & weights: fast write/read of large checkpoints during long training runs. RAG & vector stores: low-latency storage for embeddings, indexes and retrieval corpora. Inference assets: model weights and caches served at line rate to inference nodes. How it works An all-flash NVMe array exposes a Parallel FS + NFS/S3, GPUDirect Storage namespace over 2× 200G InfiniBand/Ethernet. With GPUDirect Storage, reads bypass the CPU and land directly in GPU memory, so the GPUs spend time computing, not waiting on I/O. The system scales by adding nodes; capacity and bandwidth grow together. Honest note: real throughput depends on dataset shape, file sizes and the client fabric — we validate it on your data" }, { "type": "product", "title": "QUASAR 2U Virtualization Server", "url": "https://rdp.in/gpu-mart/product/quasar-2u-virtualization-server/", "sku": "307907", "text": "QUASAR 2U Virtualization Server. SKU 307907. 2× AMD EPYC 9005 (Turin) or 2× Intel Xeon 6 · up to 6 TB DDR5-6000 ECC RDIMM (24 DIMM) · up to 24× 2.5″ NVMe hot-swap (all-flash) · 2U rack . The QUASAR 2U Virtualization Server is a dual-socket 2U virtualization and private-cloud host — 2× AMD EPYC 9005 (Turin) or 2× Intel Xeon 6, up to 6 TB DDR5-6000 ECC RDIMM (24 DIMM), up to 24× 2.5″ NVMe hot-swap (all-flash) — built in India by RDP for virtualization, VDI and private-cloud consolidation. It is the dependable enterprise compute that runs the rest of the datacentre around your AI: virtualization, databases, control planes, storage front-ends and line-of-business workloads, on a GST invoice in INR. Engineered with current-generation AMD EPYC / Intel Xeon 6 silicon, all-NVMe options and lights-out management, it is delivered racked, burned-in and validated, with RDP as your single support contact pan-India. Key highlights Processor: 2× AMD EPYC 9005 (Turin) or 2× Intel Xeon 6 — up to 384 cores (2× 192C). Memory: up to 6 TB DDR5-6000 ECC RDIMM (24 DIMM). Storage: up to 24× 2.5″ NVMe hot-swap (all-flash). Networking: 2× 25GbE LOM + dual-100GbE OCP 3.0 option. Form factor: 2U rack, air-cooled with optional liquid-assist, N+1 hot-swap PSUs. GPU option: up to 2× NVIDIA L40S (optional, for VDI/inference). Management: dedicated BMC / IPMI with redfish, remote KVM and out-of-band update. Make-in-India OEM — INR pricing, GST tax invoice, pan-India onsite support, GeM-procurable. What it runs Virtualization & VDI host — high VM/desktop density per rack-U. Databases & OLTP — NVMe-backed SQL/NoSQL with low-latency storage. Control-plane & infrastructure services — Kubernetes control nodes, AD/DNS/DHCP, backup, monitoring. Line-of-business apps — ERP, file/print, web/app tiers. Configuration & scale Dual EPYC 9005 or Xeon 6, up to 6 TB DDR5 and 24 NVMe bays for all-flash consolidation. Specify CPU SKU, memory, drives and NICs at quote; we ship it configured, not a bare chassis. Honest note: exact maximums depend on the CPU SKU and DIMM/drive population chosen — confirmed on your quote. Industry use cases Government & PSU — on-prem virtualization and databases, GeM-procurable. BFSI — OLTP, core-banking adjuncts and DR with input-credit-eligible billing. Healthcare — HIS/LIS/PACS back-ends under data-residency rules. Manufacturing & ITES — ERP, MES, VDI and pr" }, { "type": "product", "title": "CARINA Tower Server", "url": "https://rdp.in/gpu-mart/product/carina-tower-server/", "sku": "409650", "text": "CARINA Tower Server. SKU 409650. 1× Intel Xeon 6 (6500-series) or single AMD EPYC 8004 · up to 1 TB DDR5-5600 ECC · up to 8× 3.5″/2.5″ hot-swap (NVMe/SATA) · 4U-convertible tower (pedestal) . The CARINA Tower Server is a quiet pedestal tower server — 1× Intel Xeon 6 (6500-series) or single AMD EPYC 8004, up to 1 TB DDR5-5600 ECC, up to 8× 3.5″/2.5″ hot-swap (NVMe/SATA) — built in India by RDP for SMBs, branch offices and departmental IT without a server room. It is the dependable enterprise compute that runs the rest of the datacentre around your AI: virtualization, databases, control planes, storage front-ends and line-of-business workloads, on a GST invoice in INR. Engineered with current-generation Intel Xeon 6 / AMD EPYC silicon, all-NVMe options and lights-out management, it is delivered racked, burned-in and validated, with RDP as your single support contact pan-India. Key highlights Processor: 1× Intel Xeon 6 (6500-series) or single AMD EPYC 8004 — up to 64 cores. Memory: up to 1 TB DDR5-5600 ECC. Storage: up to 8× 3.5″/2.5″ hot-swap (NVMe/SATA). Networking: 2× 1/10GbE LOM. Form factor: 4U-convertible tower (pedestal), air-cooled, acoustically optimised for office use. GPU option: up to 1× NVIDIA L40S (optional). Management: dedicated BMC / IPMI with redfish, remote KVM and out-of-band update. Make-in-India OEM — INR pricing, GST tax invoice, pan-India onsite support, GeM-procurable. What it runs File, AD & departmental apps — AD/DNS/DHCP, file/print, backup in a quiet box. Databases & OLTP — NVMe-backed SQL/NoSQL with low-latency storage. Control-plane & infrastructure services — Kubernetes control nodes, AD/DNS/DHCP, backup, monitoring. Line-of-business apps — ERP, file/print, web/app tiers. Configuration & scale Single-socket with up to 1 TB DDR5 and eight large-form drive bays; runs at office noise levels. Specify CPU SKU, memory, drives and NICs at quote; we ship it configured, not a bare chassis. Honest note: exact maximums depend on the CPU SKU and DIMM/drive population chosen — confirmed on your quote. Industry use cases Government & PSU — on-prem virtualization and databases, GeM-procurable. BFSI — OLTP, core-banking adjuncts and DR with input-credit-eligible billing. Healthcare — HIS/LIS/PACS back-ends under data-residency rules. Manufacturing & ITES — ERP, MES, VDI and private-cloud hosts. Education & res" }, { "type": "product", "title": "CARINA 1U Rack Server", "url": "https://rdp.in/gpu-mart/product/carina-1u-rack-server/", "sku": "283738", "text": "CARINA 1U Rack Server. SKU 283738. 1–2× Intel Xeon 6 (6700-series) · up to 2 TB DDR5-6400 ECC RDIMM (16 DIMM) · up to 10× 2.5″ NVMe/SATA hot-swap · 1U rack . The CARINA 1U Rack Server is a compact 1U dual-socket rack server — 1–2× Intel Xeon 6 (6700-series), up to 2 TB DDR5-6400 ECC RDIMM (16 DIMM), up to 10× 2.5″ NVMe/SATA hot-swap — built in India by RDP for general-purpose datacentre and rack-dense deployments. It is the dependable enterprise compute that runs the rest of the datacentre around your AI: virtualization, databases, control planes, storage front-ends and line-of-business workloads, on a GST invoice in INR. Engineered with current-generation Intel Xeon 6 silicon, all-NVMe options and lights-out management, it is delivered racked, burned-in and validated, with RDP as your single support contact pan-India. Key highlights Processor: 1–2× Intel Xeon 6 (6700-series) — up to 172 cores (2× 86C). Memory: up to 2 TB DDR5-6400 ECC RDIMM (16 DIMM). Storage: up to 10× 2.5″ NVMe/SATA hot-swap. Networking: 2× 10/25GbE LOM + OCP 3.0 slot. Form factor: 1U rack, air-cooled, N+1 hot-swap PSUs. GPU option: up to 1× NVIDIA L4 / L40S (optional, low-profile). Management: dedicated BMC / IPMI with redfish, remote KVM and out-of-band update. Make-in-India OEM — INR pricing, GST tax invoice, pan-India onsite support, GeM-procurable. What it runs Virtualization & private cloud — dense VM consolidation in 1U. Databases & OLTP — NVMe-backed SQL/NoSQL with low-latency storage. Control-plane & infrastructure services — Kubernetes control nodes, AD/DNS/DHCP, backup, monitoring. Line-of-business apps — ERP, file/print, web/app tiers. Configuration & scale Single or dual Xeon 6, up to 2 TB DDR5 and ten NVMe bays in 1U. Specify CPU SKU, memory, drives and NICs at quote; we ship it configured, not a bare chassis. Honest note: exact maximums depend on the CPU SKU and DIMM/drive population chosen — confirmed on your quote. Industry use cases Government & PSU — on-prem virtualization and databases, GeM-procurable. BFSI — OLTP, core-banking adjuncts and DR with input-credit-eligible billing. Healthcare — HIS/LIS/PACS back-ends under data-residency rules. Manufacturing & ITES — ERP, MES, VDI and private-cloud hosts. Education & research — shared virtualization and storage front-ends. Performance & how to be sure Sized for consolidation density and steady-state thro" }, { "type": "product", "title": "QUASAR Spectrum-X 800G Ethernet AI Fabric Kit", "url": "https://rdp.in/gpu-mart/product/quasar-spectrum-x-800g-ethernet-ai-fabric-kit/", "sku": "437685", "text": "QUASAR Spectrum-X 800G Ethernet AI Fabric Kit. SKU 437685. 32× 800G + BlueField-3 DPUs · 25.6 Tb/s · Spectrum-X Ethernet (RoCE) + BlueField-3 DPU · Low-latency RoCE · Switch + DPU kit . The QUASAR Spectrum-X 800G Ethernet AI Fabric Kit is a turnkey Ethernet AI fabric kit — a high-bandwidth Spectrum-X switch plus BlueField-3 DPUs, providing 32× 800G + BlueField-3 DPUs at 25.6 Tb/s over Spectrum-X Ethernet (RoCE) + BlueField-3 DPU, with Low-latency RoCE. It is the interconnect that turns GPU servers into a cluster, carrying the collective (all-reduce) traffic that dominates multi-node AI training — on-premises, in INR, on a GST invoice. Engineered as the fabric layer of an RDP AI cluster, it is delivered configured, cabled and validated alongside the compute and storage it connects, with DPUs that offload networking, storage and security from the host CPUs. Key highlights 32× 800G + BlueField-3 DPUs · 25.6 Tb/s — high-bandwidth switching plus DPUs to wire a GPU cluster at full bandwidth. Spectrum-X Ethernet (RoCE) + BlueField-3 DPU — RoCE with adaptive routing and congestion control, plus DPU offload for networking/storage/security. Low-latency RoCE — low latency so distributed training scales with near-linear efficiency. 800G / 400G per port — matched to your GPU NICs/DPUs. DPU-accelerated — BlueField-3 offloads host CPUs and isolates tenants. Validated with RDP compute & storage — part of a tested cluster. On-prem sovereignty — your fabric, your data path; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8517), pan-India onsite support, GeM-procurable. Where it fits GPU cluster fabric (primary): the interconnect that carries distributed-training collectives between GPU servers. Storage fabric: high-bandwidth path between GPU nodes and the NVMe parallel-FS (GPUDirect). Multi-tenant isolation: DPUs isolate and secure tenants on a shared fabric. Ethernet-standardised AI: for teams standardising on Ethernet/RoCE. How it works The Spectrum-X switch runs RoCE over Ethernet with adaptive routing and congestion control, while BlueField-3 DPUs in each host offload networking, storage and security — keeping the fabric lossless and the host CPUs free — so all-reduce traffic, which dominates multi-node training, completes fast. RDP sizes the topology (oversubscription, spine count, DPU count) to your cluster. Honest note: re" }, { "type": "product", "title": "QUASAR 32-Node InfiniBand NDR Fabric", "url": "https://rdp.in/gpu-mart/product/quasar-32-node-infiniband-ndr-fabric/", "sku": "292309", "text": "QUASAR 32-Node InfiniBand NDR Fabric. SKU 292309. 32 nodes · 128× 400G · 51.2 Tb/s aggregate · InfiniBand NDR (Quantum-2) · Sub-600 ns · Leaf-spine fabric (2U) . The QUASAR 32-Node InfiniBand NDR Fabric is a turnkey InfiniBand fabric that wires a GPU cluster end-to-end — switches, the subnet manager and the topology, providing 32 nodes · 128× 400G at 51.2 Tb/s aggregate over InfiniBand NDR (Quantum-2), with Sub-600 ns. It is the interconnect that turns a set of GPU servers into a cluster, carrying the collective (all-reduce) traffic that dominates multi-node AI training — on-premises, in INR, on a GST invoice. Engineered as the fabric layer of an RDP AI cluster, it is delivered configured, cabled and validated alongside the compute and storage it connects. Key highlights 32 nodes · 128× 400G · 51.2 Tb/s aggregate — a complete non-blocking fabric to wire a GPU cluster at full bandwidth. InfiniBand NDR (Quantum-2) — RDMA, lossless, in-network compute (SHARP) for fast collectives. Sub-600 ns — low latency so distributed training scales with near-linear efficiency. 400G per port — matched to your GPU NICs/DPUs. Turnkey, validated fabric — delivered cabled and tested as one system, not loose boxes. Validated with RDP compute & storage — part of a tested cluster. On-prem sovereignty — your fabric, your data path; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8517), pan-India onsite support, GeM-procurable. Where it fits GPU cluster fabric (primary): the interconnect that carries distributed-training collectives between GPU servers. Storage fabric: high-bandwidth path between GPU nodes and the NVMe parallel-FS (GPUDirect). Scale-out spine: a leaf/spine building block for larger clusters. HPC interconnect: tightly-coupled MPI and AI collectives. How it works The fabric forms a leaf/spine topology with RDMA over InfiniBand; the subnet manager programs routes, in-network compute (SHARP) offloads reductions, and adaptive routing avoids hotspots — so all-reduce traffic, which dominates multi-node training, completes fast. RDP sizes the topology (oversubscription, spine count, DPU count) to your cluster. Honest note: real scaling efficiency depends on topology, collective library and model — we validate it on your cluster, not just a peak number. Industry use cases AI/ML & foundation-model teams — the fabric that lets trai" }, { "type": "product", "title": "QUASAR 64-Port 400G InfiniBand Switch", "url": "https://rdp.in/gpu-mart/product/quasar-64-port-400g-infiniband-switch/", "sku": "609704", "text": "QUASAR 64-Port 400G InfiniBand Switch. SKU 609704. 64× 400G OSFP (NDR) · 51.2 Tb/s switching · InfiniBand NDR (Quantum-2 class) · <600 ns port-to-port · 1U . The QUASAR 64-Port 400G InfiniBand Switch is the high-bandwidth interconnect that turns a pile of GPU servers into a cluster. It provides 64× 400G OSFP (NDR) at 51.2 Tb/s of non-blocking switching over InfiniBand NDR (Quantum-2 class), with <600 ns port-to-port — the low-latency, lossless fabric that lets distributed AI training scale across nodes without the network becoming the bottleneck. On-premises, in INR, on a GST invoice. Engineered as the fabric layer of an RDP AI cluster, it carries the collective (all-reduce) traffic that dominates multi-node training, and is delivered configured, cabled and validated alongside the compute and storage it connects. Key highlights 64× 400G OSFP (NDR) · 51.2 Tb/s — non-blocking switching to wire a GPU cluster at full bandwidth. InfiniBand NDR (Quantum-2 class) — RDMA, lossless, in-network compute (SHARP) for fast collectives. <600 ns port-to-port — low latency so distributed training scales with near-linear efficiency. 400G / 200G per port — flexible speeds to match your GPU NICs/DPUs. Spine-leaf ready — combine switches into a non-blocking fabric for hundreds to thousands of GPUs. Validated with RDP compute — delivered as part of a tested cluster, not a loose box. On-prem sovereignty — your fabric, your data path; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8517), pan-India onsite support, GeM-procurable. Where it fits GPU cluster fabric (primary): the interconnect between GPU servers that carries distributed-training collectives. Storage fabric: high-bandwidth path between GPU nodes and the NVMe parallel-FS (GPUDirect). Scale-out spine: a leaf or spine in a non-blocking topology for large clusters. HPC interconnect: tightly-coupled MPI and AI collectives. How it works The switch forms a leaf/spine fabric with RDMA over InfiniBand; GPU NICs/DPUs connect at 400G / 200G. In-network compute (SHARP) offloads reductions, and adaptive routing avoids hotspots — so all-reduce traffic, which dominates multi-node training, completes fast. RDP sizes the topology (oversubscription, spine count) to your cluster. Honest note: real scaling efficiency depends on topology, collective library and model — we validate it on your c" }, { "type": "product", "title": "CARINA 1× RTX PRO 4500 Blackwell Agentic AI PC", "url": "https://rdp.in/gpu-mart/product/carina-1x-rtx-pro-4500-blackwell-agentic-ai-pc/", "sku": "402034", "text": "CARINA 1× RTX PRO 4500 Blackwell Agentic AI PC. SKU 402034. Intel Xeon W-2500 · 128 GB DDR5 ECC · 4 TB NVMe · 32 GB GDDR7 · Tower . The CARINA 1× RTX PRO 4500 Blackwell Agentic AI PC runs AI agents locally — a tower workstation with 1× NVIDIA RTX PRO 4500 Blackwell (32 GB GDDR7) built to run private LLM agents, RAG and automation on your own hardware, offline if needed. It puts agentic AI on the desk without sending prompts or data to the cloud — in INR, on a GST invoice. Engineered for developers, prosumers and teams adopting local agentic AI, it pairs a modern Intel Xeon W-2500 with on-chip NPU and the Blackwell GPU, plus fast memory and NVMe, so local models and agent workflows respond instantly and keep data in-house. Key highlights 1× RTX PRO 4500 Blackwell · 32 GB GDDR7 — run quantised local LLMs (13B–34B) and agent workflows on-device. Blackwell GPU + on-chip NPU — accelerated local inference with an AI-PC NPU for always-on agents. Intel Xeon W-2500 + 128 GB DDR5 ECC — responsive orchestration for multi-step agents and RAG. 4 TB NVMe NVMe — local model store, vector DB and document corpus; no egress. Tower, 10 GbE — quiet desk-side footprint. Private & offline-capable — prompts, data and models stay on-device; air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Upgrade path — step up to higher-memory RTX PRO Blackwell agentic PCs, or an agentic inference server for many concurrent agents. AI workload fit (what it actually runs — honestly) Local agents (primary): run quantised 13B–34B LLMs for private agentic workflows — tool use, RAG, automation and copilots. RAG & document AI: on-device retrieval over your local corpus and vector DB. Light fine-tuning, vision & speech: QLoRA on small models, local CV, speech-to-text and multimodal inference. Engineering note: with 32 GB GDDR7 of GPU memory this runs quantised models up to ~34B comfortably; for larger models or many concurrent agents, step up to a higher-memory PC or an agentic inference server. It is built for responsive local agents, not large-model training. AI workload positioning This sits at the local-agent stage: the machine that runs your AI agents privately, on the desk. With 32 GB GDDR7 and a GPU plus NPU, it is sized to sustain responsive local inference and agent loops — where sending every prompt to a cloud API i" }, { "type": "product", "title": "CARINA Jetson AGX Thor Edge AI Node", "url": "https://rdp.in/gpu-mart/product/carina-jetson-agx-thor-edge-ai-node/", "sku": "330714", "text": "CARINA Jetson AGX Thor Edge AI Node. SKU 330714. Integrated Arm (Jetson SoC) · Unified (shared with GPU) · 2 TB NVMe · 128 GB unified LPDDR5X · Embedded / DIN-rail . The CARINA Jetson AGX Thor Jetson Edge AI Node runs AI agents locally — a embedded / din-rail system with an NVIDIA Jetson AGX Thor SoC (128 GB unified LPDDR5X) built to run private LLM agents, RAG and automation on your own hardware, offline if needed. It puts agentic AI on the desk or at the edge without sending prompts or data to the cloud — in INR, on a GST invoice. Engineered for developers, prosumers and edge deployments adopting local agentic AI, it pairs the Jetson SoC with fast memory and NVMe so local models and agent workflows respond instantly and keep data in-house. Key highlights 128 GB unified LPDDR5X unified memory — run quantised local LLMs (7B–34B) and agent workflows on-device. Jetson AGX Thor SoC — integrated Arm CPU + Blackwell GPU for efficient edge AI. Integrated Arm (Jetson SoC) + Unified (shared with GPU) — responsive orchestration for multi-step agents and RAG. 2 TB NVMe NVMe — local model store, vector DB and document corpus; no egress. Embedded / DIN-rail, 2.5 GbE — rugged, DIN-rail/embedded mounting for the edge. Private & offline-capable — prompts, data and models stay on-device; air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Upgrade path — step up to higher-memory RTX PRO Blackwell agentic PCs, or an agentic inference server for many concurrent agents. AI workload fit (what it actually runs — honestly) Local agents (primary): run quantised 7B–34B LLMs for private agentic workflows — tool use, RAG, automation and copilots. RAG & document AI: on-device retrieval over your local corpus and vector DB. Vision & speech: local CV, speech-to-text and multimodal inference on camera/sensor feeds. Engineering note: the Jetson AGX Thor shares 128 GB unified LPDDR5X between CPU and GPU — generous for the edge, and it runs the CUDA stack; it is sized for edge agents and vision, not data-centre training. AI workload positioning This sits at the local-agent stage: the device that runs your AI agents privately, on the desk or at the edge. With 128 GB unified LPDDR5X and an efficient SoC, it is sized to sustain responsive local inference and agent loops — where sending every prompt to a cloud API is sl" }, { "type": "product", "title": "CARINA RTX 2000 Ada Edge AI Mini PC", "url": "https://rdp.in/gpu-mart/product/carina-rtx-2000-ada-edge-ai-mini-pc/", "sku": "367778", "text": "CARINA RTX 2000 Ada Edge AI Mini PC. SKU 367778. Intel Core Ultra 7 (with NPU) · 64 GB DDR5 · 2 TB NVMe · 16 GB GDDR6 · Mini / SFF . The CARINA RTX 2000 Ada Edge AI Mini PC runs AI agents locally — a mini / sff system with 1× NVIDIA RTX 2000 Ada (16 GB GDDR6) built to run private LLM agents, RAG and automation on your own hardware, offline if needed. It puts agentic AI on the desk without sending prompts or data to the cloud — in INR, on a GST invoice. Engineered for developers, prosumers and teams adopting local agentic AI, it pairs a modern Intel Core Ultra 7 with on-chip NPU and the GPU with fast memory and NVMe so local models and agent workflows respond instantly and keep data in-house. Key highlights 1× RTX 2000 Ada · 16 GB GDDR6 — run quantised local LLMs (7B–14B) and agent workflows on-device. GPU + on-chip NPU — accelerated local inference with an AI-PC NPU for always-on agents. Intel Core Ultra 7 (with NPU) + 64 GB DDR5 — responsive orchestration for multi-step agents and RAG. 2 TB NVMe NVMe — local model store, vector DB and document corpus; no egress. Mini / SFF, 2.5 GbE + Wi-Fi 6E — compact desk-side or edge footprint. Private & offline-capable — prompts, data and models stay on-device; air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Upgrade path — step up to higher-memory RTX PRO Blackwell agentic PCs, or an agentic inference server for many concurrent agents. AI workload fit (what it actually runs — honestly) Local agents (primary): run quantised 7B–14B LLMs for private agentic workflows — tool use, RAG, automation and copilots. RAG & document AI: on-device retrieval over your local corpus and vector DB. Vision & speech: local CV, speech-to-text and multimodal inference. Engineering note: with 16 GB GDDR6 of GPU memory this runs quantised models up to ~14B comfortably; for larger models or many concurrent agents, step up to a higher-memory PC or an agentic inference server. It is built for responsive local agents, not large-model training. AI workload positioning This sits at the local-agent stage: the device that runs your AI agents privately, on the desk. With 16 GB GDDR6 and a GPU plus NPU, it is sized to sustain responsive local inference and agent loops — where sending every prompt to a cloud API is slow, costly or non-compliant. Industry use cases Software &" }, { "type": "product", "title": "QUASAR 2× RTX PRO 4500 Blackwell AI Workstation", "url": "https://rdp.in/gpu-mart/product/quasar-2x-rtx-pro-4500-blackwell-ai-workstation/", "sku": "321248", "text": "QUASAR 2× RTX PRO 4500 Blackwell AI Workstation. SKU 321248. Intel Xeon W-2500 · 128 GB DDR5 ECC · 4 TB NVMe · Dual-GPU tower . The QUASAR 2× RTX PRO 4500 Blackwell AI Workstation is RDP’s performance-tier desk-side machine — two NVIDIA RTX PRO 4500 Blackwell GPUs and 64 GB of next-generation GDDR7 GPU memory in a single quiet tower, built for teams that have outgrown a single-GPU developer box and want to fine-tune and serve real models on-premises. It gives AI/ML engineers a private, fixed-cost alternative to renting two cloud GPUs: your models and data stay in the building, billing is in INR, and the system is productive on day one. Engineered for product-engineering groups, research labs and applied-AI teams standardising on a repeatable local-AI platform, it balances 64 GB of aggregate Blackwell GPU memory, an Intel Xeon W-2500 data-prep engine, 128 GB of ECC system memory and 4 TB of NVMe — so the GPUs stay fed and the box sustains real training and serving, not just benchmarks. Key highlights 64 GB of GPU memory across 2× RTX PRO 4500 Blackwell — fine-tune mid-size models and serve several models concurrently without queueing for shared cloud capacity. Blackwell-generation architecture with FP4 support — next-gen inference efficiency and accuracy, ECC throughout for long, stable fine-tune runs. Intel Xeon W-2500 + 128 GB DDR5 ECC — a serious tokenisation, data-prep and orchestration engine so the GPUs are never starved. 4 TB NVMe — fast local datasets, checkpoints and weights; no egress fees, no network bottleneck. Quiet dual-GPU tower — sized for an office, not a server room. On-prem data sovereignty — IP and customer data stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Upgrade path — step up within QUASAR to RTX PRO 5000/6000 Blackwell, or to a DRACO 4-GPU flagship when you outgrow two cards. AI workload fit (what it actually runs — honestly) Inference: serve quantised models up to ~70B (4-bit ≈ 40 GB fits across the two cards) and run multiple quantised 7B–34B models concurrently. Fine-tuning: QLoRA / LoRA up to ~34B, and full fine-tuning of 7B-class models, data-parallel across both GPUs. Vision, multimodal, RAG & agentic: train/serve vision and multimodal models, build RAG pipelines on the 4 TB NVMe, and run multi-agent workflows l" }, { "type": "product", "title": "CARINA 1× RTX PRO 5000 Blackwell AI Workstation", "url": "https://rdp.in/gpu-mart/product/carina-1x-rtx-pro-5000-blackwell-ai-workstation/", "sku": "192950", "text": "CARINA 1× RTX PRO 5000 Blackwell AI Workstation. SKU 192950. Intel Xeon W-2500 · 128 GB DDR5 ECC · 2 TB NVMe · Tower . The CARINA 1× RTX PRO 5000 Blackwell AI Workstation is RDP’s upper-entry, single-GPU AI machine on NVIDIA’s current Blackwell generation — one RTX PRO 5000 Blackwell with 48 GB of GDDR7 in a quiet, air-cooled desk-side tower. It gives a developer or small team a private, on-premises workstation with the memory headroom to fine-tune and serve genuinely useful models — with Blackwell FP4 for efficient inference, data kept in-house, INR pricing, and day-one readiness. A workstation-class Intel Xeon W-2500 with ECC memory, 128 GB DDR5 and 2 TB NVMe keep the GPU fed for sustained iteration — the strongest single-GPU rung of CARINA before stepping into 96 GB or multi-GPU. Key highlights Current-gen RTX PRO 5000 Blackwell (48 GB GDDR7) — Blackwell with FP4 ; ECC GPU memory; a large single-card pool. Intel Xeon W-2500 + 128 GB DDR5 ECC — error-correcting workstation platform for stable long runs. 2 TB NVMe — fast local datasets, checkpoints and weights; no egress fees. Quiet, air-cooled tower — office-friendly. On-prem data sovereignty — IP and data stay in-house; DPDP-friendly. Make-in-India OEM — INR pricing, GST invoice (HSN 8471), pan-India onsite support, GeM-procurable. Upgrade path — step up to RTX PRO 6000 Blackwell (96 GB) or to 2×/4× (QUASAR/DRACO). AI workload fit Inference: serve quantised models up to ~ 34B (4-bit) on the 48 GB card; FP4 boosts throughput. Fine-tuning: QLoRA / LoRA up to ~ 20B ; full fine-tuning of 7B-class models. Build & prototype: vision, NLP and RAG pipelines on the 2 TB NVMe; agentic-app development — locally. Engineering note: a single 48 GB card keeps the setup simple. For models or batches beyond 48 GB, step up within the line. AI workload positioning This sits at the develop-and-fine-tune stage: a single-engineer workstation with enough memory to fine-tune mid-size models and serve them on-desk, on current-generation hardware — far cheaper to own than continuous cloud rental, and private by design. Industry use cases Software & AI teams — local model development, eval and agentic prototyping. Research & higher-ed — NLP, vision and speech work. Startups — a private fine-tuning box avoiding per-" }, { "type": "product", "title": "CARINA 1× RTX PRO 4500 Blackwell AI Workstation", "url": "https://rdp.in/gpu-mart/product/carina-1x-rtx-pro-4500-blackwell-ai-workstation/", "sku": "620688", "text": "CARINA 1× RTX PRO 4500 Blackwell AI Workstation. SKU 620688. Intel Xeon W-2500 · 64 GB DDR5 ECC · 2 TB NVMe · Tower . The CARINA 1× RTX PRO 4500 Blackwell AI Workstation is RDP’s entry-tier, single-GPU AI machine on NVIDIA’s current Blackwell generation — one RTX PRO 4500 Blackwell with 32 GB of GDDR7 in a quiet, air-cooled desk-side tower. It gives a developer or small team a private, on-premises workstation to build, fine-tune and run modern AI models — with Blackwell’s FP4 acceleration for efficient inference, your data kept in-house, costs fixed in INR, and day-one readiness. A workstation-class Intel Xeon W-2500 with ECC memory, 64 GB DDR5 and 2 TB NVMe keep the GPU fed for real iteration — the entry rung of the CARINA → QUASAR → DRACO ladder, on this year’s silicon rather than last year’s. Key highlights Current-gen RTX PRO 4500 Blackwell (32 GB GDDR7) — Blackwell architecture with FP4 for efficient modern-model inference; ECC GPU memory. Workstation-class Intel Xeon W-2500 + 64 GB DDR5 ECC — error-correcting platform for stable long runs (not a consumer board). 2 TB NVMe — fast local datasets, checkpoints and weights; no egress fees. Quiet, air-cooled tower — office-friendly; no server room. On-prem data sovereignty — IP and data stay in-house; DPDP-friendly. Make-in-India OEM — INR pricing, GST invoice (HSN 8471), pan-India onsite support, GeM-procurable. Upgrade path — step up to the RTX PRO 5000 / 6000 Blackwell or to 2×/4× (QUASAR/DRACO). AI workload fit Inference: serve quantised models up to ~ 30–34B (4-bit) on the 32 GB card; FP4 boosts throughput on supported runtimes. Fine-tuning: QLoRA / LoRA of 7B–13B models; full fine-tuning of small models. Build & prototype: vision, NLP, RAG pipelines on the 2 TB NVMe and agentic-app development — locally, no cloud bill. Engineering note: a single 32 GB card keeps the setup simple — no multi-GPU partitioning. For larger models or batches, step up within the line. AI workload positioning This sits at the develop-and-prototype stage: a single-engineer workstation for building and fine-tuning small-to-mid models and running on-desk inference on current-generation hardware — far cheaper to own than continuous cloud rental, and private by design. Industry use case" }, { "type": "product", "title": "DRACO 8192× MI300A AI Supercomputer", "url": "https://rdp.in/gpu-mart/product/draco-8192x-mi300a-ai-supercomputer/", "sku": "622605", "text": "DRACO 8192× MI300A AI Supercomputer. SKU 622605. 8192× MI300A · Integrated AMD Zen4 (APU, per node) · Unified APU memory (HBM3) · 128 PB parallel NVMe · Data hall · liquid-cooled . The DRACO 8192× MI300A AI Supercomputer is a turnkey, liquid-cooled exascale-class HPC + AI supercomputer built on 8192 AMD Instinct MI300A APUs — the same accelerator architecture behind the world’s leadership-class FP64 systems. It delivers ~1.0 PB unified HBM3 of unified accelerator memory across a data hall with a non-blocking InfiniBand spine, fusing scientific simulation and frontier AI in one machine — on-premises, in INR, on a GST invoice. Delivered as a single national-scale engagement, RDP co-designs the reference architecture, integrates, cools and burns it in, and hands over one validated supercomputer with one warranty and one support contract. Its defining strength: FP64 HPC leadership and AI fused in one APU with unified CPU-GPU memory, removing host-device copies. Key highlights 8192× MI300A · ~1.0 PB unified HBM3 aggregate — exascale-class accelerator memory for the largest simulations and frontier AI. Infinity Fabric + non-blocking InfiniBand — AMD Infinity Fabric across the APUs and a non-blocking InfiniBand spine between nodes. Unified CPU-GPU APU memory — Zen4 CPU and CDNA GPU share one HBM3 pool, eliminating host-device transfers for HPC + AI. FP64 HPC leadership — the architecture of the world’s top FP64 supercomputers, with mixed-precision AI on the same nodes. 128 PB parallel NVMe parallel filesystem — exascale-grade storage for datasets, checkpoints and simulation output. Data hall, liquid-cooled, turnkey — delivered, integrated and validated; one engagement, one warranty. On-prem data sovereignty — data, models and codes stay in-country; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. AI workload fit (what it actually runs — honestly) HPC + simulation: leadership-class FP64 scientific computing (CFD, climate, molecular dynamics, finite-element) at national scale. Frontier AI training: distributed training of the largest models across the 8192 APUs with 3D parallelism. Large-scale inference & fine-tuning: serve and fine-tune many large models in parallel. Engineering note: this is an AMD Instinct system — it runs the open ROCm/HIP software stack, no" }, { "type": "product", "title": "DRACO 4096× MI300A AI Supercomputer", "url": "https://rdp.in/gpu-mart/product/draco-4096x-mi300a-ai-supercomputer/", "sku": "142805", "text": "DRACO 4096× MI300A AI Supercomputer. SKU 142805. 4096× MI300A · Integrated AMD Zen4 (APU, per node) · Unified APU memory (HBM3) · 64 PB parallel NVMe · Multi-Rack data hall · liquid-cooled . The DRACO 4096× MI300A AI Supercomputer is a turnkey, liquid-cooled exascale-class HPC + AI supercomputer built on 4096 AMD Instinct MI300A APUs — the same accelerator architecture behind the world’s leadership-class FP64 systems. It delivers ~524 TB unified HBM3 of unified accelerator memory across a multi-rack data hall with a non-blocking InfiniBand spine, fusing scientific simulation and frontier AI in one machine — on-premises, in INR, on a GST invoice. Delivered as a single national-scale engagement, RDP co-designs the reference architecture, integrates, cools and burns it in, and hands over one validated supercomputer with one warranty and one support contract. Its defining strength: FP64 HPC leadership and AI fused in one APU with unified CPU-GPU memory, removing host-device copies. Key highlights 4096× MI300A · ~524 TB unified HBM3 aggregate — exascale-class accelerator memory for the largest simulations and frontier AI. Infinity Fabric + non-blocking InfiniBand — AMD Infinity Fabric across the APUs and a non-blocking InfiniBand spine between nodes. Unified CPU-GPU APU memory — Zen4 CPU and CDNA GPU share one HBM3 pool, eliminating host-device transfers for HPC + AI. FP64 HPC leadership — the architecture of the world’s top FP64 supercomputers, with mixed-precision AI on the same nodes. 64 PB parallel NVMe parallel filesystem — exascale-grade storage for datasets, checkpoints and simulation output. Multi-Rack data hall, liquid-cooled, turnkey — delivered, integrated and validated; one engagement, one warranty. On-prem data sovereignty — data, models and codes stay in-country; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. AI workload fit (what it actually runs — honestly) HPC + simulation: leadership-class FP64 scientific computing (CFD, climate, molecular dynamics, finite-element) at national scale. Frontier AI training: distributed training of the largest models across the 4096 APUs with 3D parallelism. Large-scale inference & fine-tuning: serve and fine-tune many large models in parallel. Engineering note: this is an AMD Instinct system — it runs the o" }, { "type": "product", "title": "DRACO 256× GH200 AI Supercomputer", "url": "https://rdp.in/gpu-mart/product/draco-256x-gh200-ai-supercomputer/", "sku": "493633", "text": "DRACO 256× GH200 AI Supercomputer. SKU 493633. 256× GH200 · 256× Grace (ARM, 1 per superchip) · Grace LPDDR5X coherent memory · 4 PB parallel NVMe · Multi-Rack · liquid-cooled . The DRACO 256× GH200 AI Supercomputer is a turnkey, liquid-cooled HPC + AI supercomputer built on 256 NVIDIA GH200 Grace-Hopper accelerators, delivering ~37 TB HBM3e of aggregate accelerator memory across a multi-rack system with a non-blocking InfiniBand spine. It is engineered for organisations that need both traditional HPC (simulation, FP64) and frontier AI on one machine — on-premises, in INR, on a GST invoice. Delivered as a single engagement, RDP designs the reference architecture, integrates, cools and burns it in, and hands over one validated supercomputer with one warranty and one support contract — removing multi-vendor integration risk. Its defining strength: tightly-coupled Grace CPU + Hopper GPU with coherent memory for HPC + AI. Key highlights 256× GH200 · ~37 TB HBM3e aggregate — accelerator memory for large simulations and frontier AI. NVLink-C2C + non-blocking InfiniBand — NVLink-C2C coherent CPU-GPU links and a non-blocking InfiniBand spine between superchips. HPC + AI convergence — strong FP64/HPC throughput alongside mixed-precision AI on one system. 256× Grace (ARM, 1 per superchip) + Grace LPDDR5X coherent memory — CPU and memory matched to 256 accelerators. 4 PB parallel NVMe parallel filesystem — high-throughput storage for datasets, checkpoints and simulation output. Multi-Rack, liquid-cooled, turnkey — delivered, integrated and validated; one engagement, one warranty. On-prem data sovereignty — data and models stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. AI workload fit (what it actually runs — honestly) HPC + simulation: FP64 scientific computing (CFD, weather, molecular dynamics, finite-element) alongside AI. Frontier AI training: distributed training of large models across the 256 accelerators with 3D parallelism. Large-scale inference & fine-tuning: serve and fine-tune many large models in parallel. Engineering note: this is an NVIDIA Grace-Hopper system on the CUDA software stack. At this scale the network and parallelism strategy decide real performance; we run a scaling test on your codes and models rather than quoting a peak number. AI w" }, { "type": "product", "title": "DRACO 128-Node H200 HPC Cluster", "url": "https://rdp.in/gpu-mart/product/draco-128-node-h200-hpc-cluster/", "sku": "708502", "text": "DRACO 128-Node H200 HPC Cluster. SKU 708502. 128 nodes · 256× AMD EPYC 9005 (24,576 cores) · 128 TB DDR5 ECC · 512× H200 · 8 PB NVMe · InfiniBand · liquid-cooled . The DRACO 128-Node H200 HPC Cluster is a turnkey 128-node HPC cluster pairing massive CPU-forward compute with large-scale GPU acceleration — 24576 AMD EPYC cores across 128 nodes plus 512× H200 accelerators (72,192 GB HBM3e HBM3e, NVLink in-node), wired with a non-blocking InfiniBand fabric. It runs traditional FP64/MPI HPC and large-model AI on one cluster, on-premises, in INR, on a GST invoice. Engineered for organisations whose workload spans serious simulation and serious AI, it is delivered racked, cabled, scheduled and validated as a single system — RDP sizes the nodes, fabric, parallel storage, scheduler and cooling, with one warranty and one support contract. Key highlights 24576 EPYC cores across 128 nodes — large-scale CPU throughput for FP64, MPI and memory-bound HPC. 512× H200 · 72,192 GB HBM3e — large-scale GPU acceleration for model training and high-throughput inference alongside HPC. Non-blocking InfiniBand NDR fabric — full-bisection bandwidth for tightly-coupled MPI jobs and distributed training. 128 TB DDR5 ECC + 8 PB NVMe parallel NVMe — large memory and a high-throughput parallel filesystem at cluster scale. Scheduler-ready, turnkey — delivered with Slurm/Kubernetes, validated; one SKU, one warranty. On-prem data sovereignty — codes, data and models stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Scale path — grow node count toward supercomputer scale, or specialise into GPU-dense rack-scale systems. AI workload fit (what it actually runs — honestly) HPC + simulation (primary): large FP64/MPI workloads — CFD, FEA, molecular dynamics, EDA, risk and Monte-Carlo — across 24576 cores. AI training & inference: train and fine-tune large models across the NVLink-connected H200 GPUs and serve them at high throughput. RAG & agentic: production AI services co-located with HPC for engineering and research teams. Engineering note: each node’s H200 GPUs are NVLink-connected for efficient in-node tensor parallelism, and nodes scale over a non-blocking InfiniBand spine — this cluster trains and serves large models alongside FP64 HPC. The CPU cores carry the simulation/MPI sid" }, { "type": "product", "title": "DRACO 16-Node L40S HPC Cluster", "url": "https://rdp.in/gpu-mart/product/draco-16-node-l40s-hpc-cluster/", "sku": "474216", "text": "DRACO 16-Node L40S HPC Cluster. SKU 474216. 16 nodes · 32× AMD EPYC 9005 (3,072 cores) · 12 TB DDR5 ECC · 64× L40S · 480 TB NVMe · InfiniBand · liquid/air . The DRACO 16-Node L40S HPC Cluster is a turnkey 16-node HPC cluster that pairs CPU-forward compute with GPU acceleration — 3072 AMD EPYC cores across 16 nodes plus 64× L40S accelerators (3,072 GB GDDR6), wired with a low-latency InfiniBand fabric. It runs traditional FP64/MPI HPC and mixed AI on one cluster, on-premises, in INR, on a GST invoice. Engineered for engineering, research and analytics teams that need real HPC throughput with AI on the side, it is delivered racked, cabled, scheduled and validated as a single system — RDP sizes the nodes, fabric, parallel storage, scheduler and cooling, with one warranty and one support contract. Key highlights 3072 EPYC cores across 16 nodes — serious CPU throughput for FP64, MPI and memory-bound HPC. 64× L40S · 3,072 GB GDDR6 — GPU acceleration for AI inference, training and visualisation alongside HPC. InfiniBand NDR fabric — low-latency, high-bandwidth interconnect for tightly-coupled MPI jobs and collectives. 12 TB DDR5 ECC + 480 TB NVMe parallel NVMe — large memory and a high-throughput parallel filesystem for datasets and scratch. Scheduler-ready, turnkey — delivered with Slurm/Kubernetes, validated; one SKU, one warranty. On-prem data sovereignty — codes, data and models stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Scale path — grow node count and step up the accelerator (H200) as workloads demand. AI workload fit (what it actually runs — honestly) HPC + simulation (primary): FP64/MPI workloads — CFD, FEA, molecular dynamics, EDA, risk and Monte-Carlo — across 3072 cores. AI inference & visualisation: the L40S is an Ada-generation accelerator strong at inference, rendering and mixed-precision AI; serve and fine-tune mid-size models alongside HPC jobs. RAG & agentic: production AI services co-located with HPC for engineering and research teams. Engineering note: the L40S (48 GB, no NVLink) is built for inference, visualisation and mid-size AI — not large-model pre-training. For heavy training, choose the H200 node variant or a GPU Server/SuperCluster. This cluster’s strength is balanced CPU-HPC + accelerated AI. AI workload positioning" }, { "type": "product", "title": "DRACO 4-Node L40S HPC Cluster", "url": "https://rdp.in/gpu-mart/product/draco-4-node-l40s-hpc-cluster/", "sku": "910574", "text": "DRACO 4-Node L40S HPC Cluster. SKU 910574. 4 nodes · 8× AMD EPYC 9005 (768 cores) · 3 TB DDR5 ECC · 16× L40S · 120 TB NVMe · InfiniBand · liquid/air . The DRACO 4-Node L40S HPC Cluster is a turnkey 4-node HPC cluster that pairs CPU-forward compute with GPU acceleration — 768 AMD EPYC cores across 4 nodes plus 16× L40S accelerators (768 GB GDDR6), wired with a low-latency InfiniBand fabric. It runs traditional FP64/MPI HPC and mixed AI on one cluster, on-premises, in INR, on a GST invoice. Engineered for engineering, research and analytics teams that need real HPC throughput with AI on the side, it is delivered racked, cabled, scheduled and validated as a single system — RDP sizes the nodes, fabric, parallel storage, scheduler and cooling, with one warranty and one support contract. Key highlights 768 EPYC cores across 4 nodes — serious CPU throughput for FP64, MPI and memory-bound HPC. 16× L40S · 768 GB GDDR6 — GPU acceleration for AI inference, training and visualisation alongside HPC. InfiniBand NDR fabric — low-latency, high-bandwidth interconnect for tightly-coupled MPI jobs and collectives. 3 TB DDR5 ECC + 120 TB NVMe parallel NVMe — large memory and a high-throughput parallel filesystem for datasets and scratch. Scheduler-ready, turnkey — delivered with Slurm/Kubernetes, validated; one SKU, one warranty. On-prem data sovereignty — codes, data and models stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Scale path — grow node count and step up the accelerator (H200) as workloads demand. AI workload fit (what it actually runs — honestly) HPC + simulation (primary): FP64/MPI workloads — CFD, FEA, molecular dynamics, EDA, risk and Monte-Carlo — across 768 cores. AI inference & visualisation: the L40S is an Ada-generation accelerator strong at inference, rendering and mixed-precision AI; serve and fine-tune mid-size models alongside HPC jobs. RAG & agentic: production AI services co-located with HPC for engineering and research teams. Engineering note: the L40S (48 GB, no NVLink) is built for inference, visualisation and mid-size AI — not large-model pre-training. For heavy training, choose the H200 node variant or a GPU Server/SuperCluster. This cluster’s strength is balanced CPU-HPC + accelerated AI. AI workload positioning This sits at the H" }, { "type": "product", "title": "DRACO 8× H200 SXM GPU Server", "url": "https://rdp.in/gpu-mart/product/draco-8x-h200-sxm-gpu-server/", "sku": "504910", "text": "DRACO 8× H200 SXM GPU Server. SKU 504910. 2× Intel Xeon 6 · 2 TB DDR5 ECC · 60 TB NVMe · 8U rack . The DRACO 8× H200 SXM GPU Server is a Rack 8U rack server built to bring training and high-throughput inference of the largest models into your own data centre. Eight NVIDIA H200 SXM5 (HGX H200) GPUs on a single HGX baseboard deliver 1,128 GB HBM3e of HBM3e, linked by NVLink and NVSwitch into one tightly-coupled accelerator — sized to train and serve up to 405B-class models, behind your firewall, in INR, on a GST invoice. Engineered for AI platform teams bringing large-model training in-house, it pairs the eight GPUs with a 2× Intel Xeon 6 host, 2 TB DDR5 ECC and 60 TB NVMe, with 8× 400G InfiniBand for scale-out, redundant power and full BMC/IPMI — a data-centre training node that racks and runs. Key highlights 1,128 GB HBM3e of HBM3e across 8× H200 SXM — train and serve up to 405B-class models on a single node. NVLink + NVSwitch fabric — full all-to-all GPU bandwidth for efficient tensor-parallel training, the defining advantage of an HGX node. 2× Intel Xeon 6 + 2 TB DDR5 ECC — high core count and memory bandwidth to feed eight data-centre GPUs. Rack 8U, liquid-cooled, redundant PSU, BMC/IPMI — sustained all-GPU clocks, hot-swap drives, lights-out management. 60 TB NVMe + 8× InfiniBand NDR 400G — large local dataset/checkpoint capacity with a high-bandwidth scale-out fabric; no egress fees. On-prem data sovereignty — training data and weights stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Scale path — multiple HGX nodes scale out over InfiniBand into RDP rack-scale systems and superclusters. AI workload fit (what it actually runs — honestly) Training & fine-tuning: full pre-training/fine-tuning and parameter-efficient (QLoRA/LoRA) training of 405B-class models, tensor- and pipeline-parallel across the eight NVSwitch-linked GPUs. Inference: serve 405B-class models at high throughput, or host several large models concurrently. RAG, vision, multimodal & agentic: production pipelines on the 60 TB NVMe and multi-agent back-ends. Engineering note: the 8 SXM GPUs sit on an HGX baseboard with NVLink + NVSwitch — full all-to-all GPU bandwidth for efficient tensor-parallel training of the largest models, exactly what frontier-scale training needs. AI workload" }, { "type": "product", "title": "DRACO 4× H200 NVL GPU Server", "url": "https://rdp.in/gpu-mart/product/draco-4x-h200-nvl-gpu-server/", "sku": "637488", "text": "DRACO 4× H200 NVL GPU Server. SKU 637488. 2× AMD EPYC 9005 · 1 TB DDR5 ECC · 16 TB NVMe · 4U rack . The DRACO 4× H200 NVL GPU Server is a Rack 4U rack server built to bring training and high-throughput inference into your own data centre. 4 NVIDIA H200 NVL GPUs deliver 564 GB HBM3e of high-bandwidth GPU memory in a dense, serviceable chassis — sized to train and serve 70B–180B-class models, behind your firewall, in INR, on a GST invoice. Engineered for AI platform and MLOps teams standardising training and large-model serving on owned infrastructure, it pairs the GPUs with a 2× AMD EPYC 9005 host, 1 TB DDR5 ECC and 16 TB NVMe, with redundant power and full BMC/IPMI remote management — a production node that racks and runs, not a repurposed desktop. Key highlights 564 GB HBM3e of GPU memory across 4× H200 NVL — train and serve 70B–180B-class models on-prem. NVLink-bridged GPUs — fast GPU-to-GPU transfer for efficient tensor parallelism, ECC throughout. 2× AMD EPYC 9005 + 1 TB DDR5 ECC — high core count and memory bandwidth to feed 4 data-centre GPUs. Rack 4U, redundant PSU, BMC/IPMI — hot-swap drives, tool-less service, lights-out management. 16 TB NVMe + 2× 25 GbE — fast dataset, checkpoint and weight storage with high-throughput networking; no egress fees. On-prem data sovereignty — data and weights stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Scale path — grow within the DRACO server line and out to RDP rack-scale systems as demand rises. AI workload fit (what it actually runs — honestly) Training & fine-tuning: full and parameter-efficient (QLoRA/LoRA) fine-tuning and training of 70B–180B-class models, with tensor- and data-parallelism across the GPUs. Inference: serve 70B–180B-class models at high throughput, or host several large models concurrently. RAG, vision, multimodal & agentic: production RAG endpoints, vision/multimodal inference and multi-agent back-ends on the 16 TB NVMe. Engineering note: the H200 NVL uses NVLink bridges between cards — much faster GPU-to-GPU than plain PCIe, though not the full all-to-all NVSwitch fabric of an SXM HGX node. For the densest tensor-parallel models, the SXM/HGX nodes are the step up. AI workload positioning This sits at the train-and-serve stage of the AI lifecycle. With 564 GB HBM3e of GPU memory," }, { "type": "product", "title": "QUASAR 2× RTX PRO 6000 Blackwell GPU Server", "url": "https://rdp.in/gpu-mart/product/quasar-2x-rtx-pro-6000-blackwell-gpu-server/", "sku": "620866", "text": "QUASAR 2× RTX PRO 6000 Blackwell GPU Server. SKU 620866. 2× Intel Xeon 6 · 512 GB DDR5 ECC · 8 TB NVMe · 2U rack . The QUASAR 2× RTX PRO 6000 Blackwell GPU Server is a Rack 2U rack server built to bring inference into your own data centre. 2 RTX PRO 6000 Blackwell Server Edition GPUs deliver 192 GB GDDR7 of high-bandwidth GPU memory in a dense, serviceable chassis — sized to serve 70B-class models and host many models at once, behind your firewall, in INR, on a GST invoice. Engineered for AI platform and MLOps teams standardising production inference on owned infrastructure, it pairs the GPUs with a 2× Intel Xeon 6 host, 512 GB DDR5 ECC and 8 TB NVMe, with redundant power and full BMC/IPMI remote management — a production node that racks and runs, not a repurposed desktop. Key highlights 192 GB GDDR7 of GPU memory across 2× RTX PRO 6000 Blackwell — serve 70B-class models or host many smaller models concurrently. Blackwell architecture with FP4 — next-generation inference efficiency and accuracy, ECC throughout. 2× Intel Xeon 6 + 512 GB DDR5 ECC — high core count and memory bandwidth to feed 2 data-centre GPUs. Rack 2U, redundant PSU, BMC/IPMI — hot-swap drives, tool-less service, lights-out management. 8 TB NVMe + 2× 25 GbE — fast dataset, checkpoint and weight storage with high-throughput networking; no egress fees. On-prem data sovereignty — data and weights stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Scale path — grow within the QUASAR server line and out to RDP rack-scale systems as demand rises. AI workload fit (what it actually runs — honestly) Inference (primary): serve 70B-class models, or host multiple 7B–34B models concurrently for high aggregate throughput. Fine-tuning: QLoRA / LoRA up to ~70B and full fine-tuning of 7B-class models, data-parallel across the GPUs. RAG, vision, multimodal & agentic: production RAG endpoints, vision/multimodal inference and multi-agent back-ends on the 8 TB NVMe. Engineering note: the RTX PRO 6000 Blackwell Server Edition is a PCIe card with no NVLink — the 2 GPUs are ideal for data-parallel serving and multi-instance hosting; for a single model larger than 96 GB, use tensor parallelism across cards, or step up to an SXM/NVLink node. A production serving workhorse, not a large-scale training fabric. AI" }, { "type": "product", "title": "DRACO 64× H200 SXM Rack-Scale AI System", "url": "https://rdp.in/gpu-mart/product/draco-64x-h200-sxm-rack-scale-ai-system/", "sku": "949018", "text": "DRACO 64× H200 SXM Rack-Scale AI System. SKU 949018. 8-node HGX H200 · 16× Intel Xeon 6 · 16 TB DDR5 ECC · 480 TB NVMe · Full-Rack · liquid-cooled . The DRACO 64× H200 SXM Rack-Scale AI System is a turnkey, liquid-cooled full-rack AI training cluster — 64 NVIDIA H200 SXM GPUs across 8 HGX nodes, wired into one system with NVLink inside each node and a 400G InfiniBand spine between them. It delivers 9,024 GB HBM3e of aggregate HBM3e and arrives racked, cabled, cooled and tested, ready to train and serve the largest models on-premises — in INR, on a GST invoice. Engineered for organisations building serious in-house AI capacity, it removes the integration risk of assembling a cluster yourself: RDP sizes the nodes, fabric, storage, power and cooling as one validated system and delivers it as a single SKU with one warranty and one support contract. Key highlights 64× H200 SXM · 9,024 GB HBM3e aggregate HBM3e — cluster-scale GPU memory for trillion-token training and large-model serving. NVLink + NVSwitch in each node, 400G InfiniBand spine — full intra-node bandwidth and low-latency inter-node collectives for near-linear scaling. 16× Intel Xeon 6 + 16 TB DDR5 ECC — host compute and memory matched to 64 data-centre GPUs. 480 TB NVMe NVMe + parallel-FS ready — high-throughput data and checkpoint storage across the cluster. Full-Rack, liquid-cooled, turnkey — delivered racked, cabled, cooled and burned-in; one SKU, one warranty. On-prem data sovereignty — training data and weights stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Scale path — grow to larger rack-scale systems and multi-rack AI SuperClusters on the same fabric. AI workload fit (what it actually runs — honestly) Distributed training: data-, tensor- and pipeline-parallel training of Trillion-scale-class models across the 64 GPUs. Large-scale inference: serve many large models, or shard the largest models across nodes for high throughput. RAG, multimodal & agentic at scale: production AI platforms on the cluster’s storage and fabric. Engineering note: within each HGX node the eight GPUs share an NVLink+NVSwitch fabric; across nodes, a 400G InfiniBand spine carries the collective (all-reduce) traffic. Real-world scaling efficiency depends on model and parallelism strategy — we validate it f" }, { "type": "product", "title": "DRACO GB300 NVL72 Rack-Scale AI System", "url": "https://rdp.in/gpu-mart/product/draco-gb300-nvl72-rack-scale-ai-system/", "sku": "584582", "text": "DRACO GB300 NVL72 Rack-Scale AI System. SKU 584582. GB300 NVL72 · 36× NVIDIA Grace (ARM) · Grace LPDDR5X coherent memory · 480 TB NVMe · Single-Rack (NVLink domain) · liquid-cooled . The DRACO GB300 NVL72 Rack-Scale AI System is a turnkey, liquid-cooled rack-scale AI system built on NVIDIA’s GB300 NVL72 platform — 72 Grace-Blackwell Ultra GPUs joined in a single NVLink domain with 20,736 GB HBM3e of aggregate HBM3e. The whole rack behaves as one enormous accelerator, sized to train and serve frontier-scale models on-premises — in INR, on a GST invoice. Engineered for national programmes, neoclouds and large enterprises building foundation-model capability in-house, it arrives racked, cabled, liquid-cooled and validated as a single SKU with one warranty and one support contract — RDP scopes the NVLink domain, InfiniBand spine, storage, power and cooling as one system so you don’t carry the integration risk. Key highlights GB300 NVL72 · 20,736 GB HBM3e aggregate HBM3e — one unified NVLink domain of 72 Grace-Blackwell Ultra GPUs for frontier-scale training. Unified NVLink/NVSwitch domain — all GPUs in a rack act as a single accelerator; coherent Grace CPUs over NVLink-C2C; 400G+ InfiniBand spine for scale-out. 36× NVIDIA Grace (ARM) — Grace CPUs coherently attached to the Blackwell Ultra GPUs. 480 TB NVMe NVMe + parallel-FS ready — high-throughput data and checkpoint storage at frontier scale. Single-Rack (NVLink domain), liquid-cooled, turnkey — delivered racked, cabled, cooled and burned-in; one SKU, one warranty. On-prem data sovereignty — training data and weights stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Scale path — interconnect multiple systems into a multi-rack RDP AI SuperCluster. AI workload fit (what it actually runs — honestly) Frontier training: pre-train and fine-tune the largest (multi-hundred-billion to trillion-parameter) models, tensor-/pipeline-/data-parallel across the NVLink domain. Large-scale inference: serve the very largest models with the whole rack as one memory pool, or many large models concurrently. RAG, multimodal & agentic at scale: the most demanding production AI platforms. Engineering note: the defining feature of an NVL system is the unified NVLink domain — 72 GPUs addressed as one accelerator with" }, { "type": "product", "title": "DRACO 16× H200 SXM Rack-Scale AI System", "url": "https://rdp.in/gpu-mart/product/draco-16x-h200-sxm-rack-scale-ai-system/", "sku": "458671", "text": "DRACO 16× H200 SXM Rack-Scale AI System. SKU 458671. 2-node HGX H200 · 4× Intel Xeon 6 · 4 TB DDR5 ECC · 120 TB NVMe · Quarter-Rack · liquid-cooled . The DRACO 16× H200 SXM Rack-Scale AI System is a turnkey, liquid-cooled quarter-rack AI training cluster — 16 NVIDIA H200 SXM GPUs across 2 HGX nodes, wired into one system with NVLink inside each node and a 400G InfiniBand spine between them. It delivers 2,256 GB HBM3e of aggregate HBM3e and arrives racked, cabled, cooled and tested, ready to train and serve the largest models on-premises — in INR, on a GST invoice. Engineered for organisations building serious in-house AI capacity, it removes the integration risk of assembling a cluster yourself: RDP sizes the nodes, fabric, storage, power and cooling as one validated system and delivers it as a single SKU with one warranty and one support contract. Key highlights 16× H200 SXM · 2,256 GB HBM3e aggregate HBM3e — cluster-scale GPU memory for trillion-token training and large-model serving. NVLink + NVSwitch in each node, 400G InfiniBand spine — full intra-node bandwidth and low-latency inter-node collectives for near-linear scaling. 4× Intel Xeon 6 + 4 TB DDR5 ECC — host compute and memory matched to 16 data-centre GPUs. 120 TB NVMe NVMe + parallel-FS ready — high-throughput data and checkpoint storage across the cluster. Quarter-Rack, liquid-cooled, turnkey — delivered racked, cabled, cooled and burned-in; one SKU, one warranty. On-prem data sovereignty — training data and weights stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Scale path — grow to larger rack-scale systems and multi-rack AI SuperClusters on the same fabric. AI workload fit (what it actually runs — honestly) Distributed training: data-, tensor- and pipeline-parallel training of 405B+-class models across the 16 GPUs. Large-scale inference: serve many large models, or shard the largest models across nodes for high throughput. RAG, multimodal & agentic at scale: production AI platforms on the cluster’s storage and fabric. Engineering note: within each HGX node the eight GPUs share an NVLink+NVSwitch fabric; across nodes, a 400G InfiniBand spine carries the collective (all-reduce) traffic. Real-world scaling efficiency depends on model and parallelism strategy — we validate it for y" }, { "type": "product", "title": "DRACO 32× GB300 NVL72 AI SuperCluster", "url": "https://rdp.in/gpu-mart/product/draco-32x-gb300-nvl72-ai-supercluster/", "sku": "903223", "text": "DRACO 32× GB300 NVL72 AI SuperCluster. SKU 903223. 32× GB300 NVL72 · 1,152× NVIDIA Grace (ARM) · Grace LPDDR5X coherent memory · 32 PB parallel NVMe · Multi-Rack data hall · liquid-cooled . The DRACO 32× GB300 NVL72 AI SuperCluster is a turnkey, liquid-cooled GB300 NVL72 SuperPOD — 2304 Grace-Blackwell Ultra GPUs across 32 unified NVLink-domain racks, joined by a non-blocking spine-leaf InfiniBand fabric, delivering ~664 TB HBM3e of aggregate GPU memory. It arrives as a complete, validated AI factory — power, cooling, fabric, storage and software — ready to train frontier models on-premises, in INR, on a GST invoice. Engineered for sovereign-AI programmes, neoclouds and national-scale enterprises, it is delivered as a single engagement: RDP designs the reference architecture, integrates and burns it in, and hands over one validated SuperPOD with one warranty and one support contract — removing multi-vendor integration risk at frontier scale. Key highlights 32× GB300 NVL72 · ~664 TB HBM3e aggregate — 2304 Grace-Blackwell Ultra GPUs for the largest foundation-model training. Unified NVLink domains + non-blocking InfiniBand spine — each NVL72 rack is one 72-GPU accelerator; the racks scale over a full-bisection fabric. 1,152× NVIDIA Grace (ARM) (coherent) + Grace LPDDR5X coherent memory — Grace CPUs coherently attached to the Blackwell Ultra GPUs. 32 PB parallel NVMe parallel filesystem — high-throughput training data and checkpoint storage at SuperPOD scale. Multi-Rack data hall, liquid-cooled, turnkey — delivered racked, cabled, cooled, validated; one SKU, one warranty. On-prem data sovereignty — training data and weights stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Scale path — extend the fabric to multi-pod data halls. AI workload fit (what it actually runs — honestly) Frontier training: distributed pre-training of the largest foundation models across 2304 GPUs with 3D parallelism. Large-scale fine-tuning & serving: fine-tune and serve many large models in parallel, or shard the very largest across NVLink domains. RAG, multimodal & agentic platforms: national- or organisation-wide production AI on the SuperPOD’s storage and fabric. Engineering note: a GB300 SuperPOD combines unified NVLink domains (72 Blackwell Ultra GPUs each, 288 GB per" }, { "type": "product", "title": "DRACO 8× GB200 NVL72 AI SuperCluster", "url": "https://rdp.in/gpu-mart/product/draco-8x-gb200-nvl72-ai-supercluster/", "sku": "377772", "text": "DRACO 8× GB200 NVL72 AI SuperCluster. SKU 377772. 8× GB200 NVL72 · 288× NVIDIA Grace (ARM) · Grace LPDDR5X coherent memory · 8 PB parallel NVMe · 8-Rack SuperPOD · liquid-cooled . The DRACO 8× GB200 NVL72 AI SuperCluster is a turnkey, liquid-cooled NVL72 SuperPOD delivering ~110 TB HBM3e of aggregate GPU memory across 8× NVL72 racks. It arrives as a complete, validated system — power, cooling, fabric, storage and software — ready to train frontier models on-premises, in INR, on a GST invoice. Engineered for sovereign-AI programmes, neoclouds and large enterprises building data-hall-scale capacity, it is delivered as a single engagement: RDP designs the reference architecture, integrates and burns it in, and hands over one validated SuperPOD with one warranty and one support contract — removing multi-vendor integration risk. Key highlights 8× GB200 NVL72 · ~110 TB HBM3e aggregate — data-hall-scale GPU memory for training and serving the largest models. Unified NVLink domains + non-blocking InfiniBand spine — each NVL72 rack is a unified NVLink domain of 72 Grace-Blackwell GPUs; the 8× racks are joined by a non-blocking spine-leaf InfiniBand fabric. 288× NVIDIA Grace (ARM) (coherent) + Grace LPDDR5X coherent memory — host/CPU compute matched to 576 Blackwell GPUs. 8 PB parallel NVMe parallel filesystem — high-throughput training data and checkpoint storage at cluster scale. 8-Rack SuperPOD, liquid-cooled, turnkey — delivered racked, cabled, cooled, validated; one SKU, one warranty. On-prem data sovereignty — training data and weights stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. Scale path — extend the fabric to larger SuperPODs and multi-pod data halls. AI workload fit (what it actually runs — honestly) Frontier training: distributed pre-training of large foundation models across the 576 GPUs with 3D parallelism. Large-scale fine-tuning & serving: fine-tune and serve many large models in parallel, or shard the very largest across the NVLink domains. RAG, multimodal & agentic platforms: organisation-wide production AI on the cluster’s storage and fabric. Engineering note: an NVL SuperPOD combines several unified NVLink domains (72 GPUs each) over a non-blocking InfiniBand spine — within a rack the GPUs act as one accelerator, across racks the" }, { "type": "product", "title": "DRACO 256× H200 SXM AI SuperCluster", "url": "https://rdp.in/gpu-mart/product/draco-256x-h200-sxm-ai-supercluster/", "sku": "791976", "text": "DRACO 256× H200 SXM AI SuperCluster. SKU 791976. 32× HGX H200 nodes · 64× Intel Xeon 6 (32 nodes) · 64 TB DDR5 ECC · 4 PB parallel NVMe · 4-Rack pod · liquid-cooled . The DRACO 256× H200 SXM AI SuperCluster is a turnkey, liquid-cooled multi-rack AI supercluster — 256 NVIDIA H200 SXM GPUs across 32 HGX nodes in a 4-rack pod, wired with a non-blocking spine-leaf InfiniBand fabric. It delivers ~36 TB HBM3e of aggregate GPU memory and arrives as a complete, validated system — power, cooling, fabric, storage and software — ready to train frontier models on-premises, in INR, on a GST invoice. Engineered for sovereign-AI programmes, neoclouds and large enterprises building data-hall-scale capacity, it is delivered as a single engagement: RDP designs the reference architecture, integrates and burns it in, and hands over one validated supercluster with one warranty and one support contract — removing the multi-vendor integration risk of building it yourself. Key highlights 256× H200 SXM · ~36 TB HBM3e aggregate — data-hall-scale GPU memory for training and serving the largest models. Non-blocking spine-leaf InfiniBand (NDR/XDR) — full-bisection bandwidth for near-linear scaling across all 32 nodes. NVLink + NVSwitch within each node — full intra-node bandwidth, complemented by the InfiniBand spine between nodes. 64× Intel Xeon 6 (32 nodes) + 64 TB DDR5 ECC — host compute and memory matched to 256 data-centre GPUs. 4 PB parallel NVMe parallel filesystem — high-throughput training data and checkpoint storage at cluster scale. 4-Rack pod, liquid-cooled, turnkey — delivered racked, cabled, cooled, validated; one SKU, one warranty. On-prem data sovereignty — training data and weights stay in-house; DPDP-friendly, air-gappable. Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable. AI workload fit (what it actually runs — honestly) Frontier training: distributed pre-training of large foundation models across the 256 GPUs with 3D parallelism (data, tensor, pipeline). Large-scale fine-tuning & serving: fine-tune and serve many large models in parallel, or shard the very largest across nodes. RAG, multimodal & agentic platforms: production AI platforms for an entire organisation on the cluster’s storage and fabric. Engineering note: at supercluster scale the limiting factor is the network, not a single GPU — th" }, { "type": "knowledge-base", "title": "Conversational Commerce in Indian Languages: GPU Sizing for Voice Retail", "url": "https://rdp.in/gpu-mart/knowledge-base/conversational-commerce-indian-languages-gpu-sizing-voice-retail/", "sku": "", "text": "Voice and chat commerce in Indian languages runs a three-model pipeline per turn: speech recognition, language model, speech synthesis. Latency is the product requirement, and code-mixed Indian speech is where accuracy and GPU cost both suffer. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for Agentic RAG: Caching and Cost Control Training Reference Archi" }, { "type": "knowledge-base", "title": "Context Engineering for Agentic RAG: Caching and Cost Control", "url": "https://rdp.in/gpu-mart/knowledge-base/context-engineering-agentic-rag-caching-cost-control/", "sku": "", "text": "An agentic RAG system retrieves repeatedly and carries results forward, so context grows across a trajectory and dominates cost. Prefix caching, compaction and retrieval budgets are what keep a deployment affordable at scale. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for Agentic RAG: Caching and Cost Control Training Reference Architecture: 8× H200 On" }, { "type": "knowledge-base", "title": "Multimodal RAG: GPU Planning for Document, Image and Video Retrieval", "url": "https://rdp.in/gpu-mart/knowledge-base/multimodal-rag-gpu-planning-document-image-video-retrieval/", "sku": "", "text": "Most enterprise knowledge is in scanned documents, diagrams, screenshots and recordings, not clean prose. Multimodal RAG indexes those directly, and the GPU cost sits overwhelmingly in ingestion rather than in query serving. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for Agentic RAG: Caching and Cost Control Training Reference Architecture: 8× H200 On-" }, { "type": "knowledge-base", "title": "PCIe Gen6 and 800G SuperNICs: What the 2026 Server Refresh Changes", "url": "https://rdp.in/gpu-mart/knowledge-base/pcie-gen6-800g-supernics-2026-server-refresh-changes/", "sku": "", "text": "ConnectX-8 combines an 800G NIC with an integrated PCIe Gen6 switch in one device, exposing 48 Gen6 lanes from an x16 connector. That consolidation removes components from AI server designs and changes what to check on a 2026 specification. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for Agentic RAG: Caching and Cost Control Training Reference Architect" }, { "type": "knowledge-base", "title": "Workstation Thermals and Power in Indian Offices: Planning for 600 W Cards", "url": "https://rdp.in/gpu-mart/knowledge-base/workstation-thermals-power-indian-offices-600w-cards/", "sku": "", "text": "A modern AI workstation can draw over a kilowatt at the wall and runs at that level for hours, not seconds. In an Indian office that is a thermal and electrical planning problem, and thermal throttling silently costs the performance you paid for. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for Agentic RAG: Caching and Cost Control Training Reference Arc" }, { "type": "knowledge-base", "title": "Local RAG on a Mid-Tier Workstation: Index Size and Honest Limits", "url": "https://rdp.in/gpu-mart/knowledge-base/local-rag-mid-tier-workstation-index-size-honest-limits/", "sku": "", "text": "A mid-tier workstation can host a genuinely useful private RAG system over a few hundred thousand documents. This sets out where the memory goes between generation model, embeddings and index, and where the workstation approach stops being viable. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for Agentic RAG: Caching and Cost Control Training Reference Ar" }, { "type": "knowledge-base", "title": "Long Context vs RAG in 2026: Where Retrieval Still Wins", "url": "https://rdp.in/gpu-mart/knowledge-base/long-context-vs-rag-2026-where-retrieval-wins/", "sku": "", "text": "Million-token windows did not make retrieval obsolete. Published comparisons put long-context serving at orders of magnitude more cost per query than a RAG pipeline, and multi-fact recall degrades in the middle of long prompts. Routing beats choosing. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for Agentic RAG: Caching and Cost Control Training Referenc" }, { "type": "knowledge-base", "title": "The Multi-Agent Developer Desk: Sizing a Mid-Tier Workstation", "url": "https://rdp.in/gpu-mart/knowledge-base/multi-agent-developer-desk-mid-tier-workstation-sizing/", "sku": "", "text": "Developers now run several concurrent agent sessions rather than one chat. Concurrency multiplies KV cache rather than weights, which is why a 96 GB mid-tier workstation behaves very differently from two 48 GB ones for this workload. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for Agentic RAG: Caching and Cost Control Training Reference Architecture: 8×" }, { "type": "knowledge-base", "title": "Scale-Up Domains and the Fabric Boundary: Designing Past One Rack", "url": "https://rdp.in/gpu-mart/knowledge-base/scale-up-domains-fabric-boundary-designing-past-one-rack/", "sku": "", "text": "Every rack-scale system has a boundary where fast NVLink ends and slower scale-out networking begins. Where you place that boundary relative to your model’s parallelism determines achieved throughput more than the accelerator generation does. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for Agentic RAG: Caching and Cost Control Training Reference A" }, { "type": "knowledge-base", "title": "Liquid Cooling for Flagship Racks in India: CDUs and Water Quality", "url": "https://rdp.in/gpu-mart/knowledge-base/liquid-cooling-flagship-racks-india-cdus-water-quality/", "sku": "", "text": "Direct liquid cooling is mandatory above roughly 50 kW per rack, and the part Indian operators underestimate is water chemistry: deionised or RO water with conductivity typically held below 5-10 microsiemens per centimetre, maintained for years. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for Agentic RAG: Caching and Cost Control Training Reference Arch" }, { "type": "knowledge-base", "title": "Rubin Ultra and Kyber NVL576: Planning the 2027 Flagship Rack", "url": "https://rdp.in/gpu-mart/knowledge-base/rubin-ultra-kyber-nvl576-planning-2027-flagship-rack/", "sku": "", "text": "Kyber is expected to house 576 Rubin Ultra GPUs per rack at 600 kW to 1 MW, with 800 VDC distribution arriving alongside it in 2027. Any hall commissioned in 2026 that cannot reach those figures will need a retrofit inside its first refresh cycle. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for Agentic RAG: Caching and Cost Control Training Reference Ar" }, { "type": "knowledge-base", "title": "Continual Pre-Training: When Fine-Tuning Is Not Enough", "url": "https://rdp.in/gpu-mart/knowledge-base/continual-pre-training-when-fine-tuning-not-enough/", "sku": "", "text": "Fine-tuning teaches behaviour; continual pre-training teaches a language or a domain’s underlying distribution. It costs orders of magnitude more and risks catastrophic forgetting. This sets out when it is genuinely warranted and how to size it. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for Agentic RAG: Caching and Cost Control Training Referenc" }, { "type": "knowledge-base", "title": "Indian-Language Adaptation: Tokenizers, Data and GPU Planning", "url": "https://rdp.in/gpu-mart/knowledge-base/indian-language-adaptation-tokenizers-data-gpu-planning/", "sku": "", "text": "Sovereign Indian models from Sarvam, BharatGen and Gnani now cover 22 languages, and IndiaAI has commissioned over 36,000 GPUs heading toward 100,000. This covers tokenizer efficiency, data strategy and how to size an Indian-language adaptation. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for Agentic RAG: Caching and Cost Control Training Reference Arch" }, { "type": "knowledge-base", "title": "Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split", "url": "https://rdp.in/gpu-mart/knowledge-base/sizing-rl-fine-tuning-loop-rollouts-verifiers-gpu-split/", "sku": "", "text": "Reinforcement learning with verifiable rewards is now standard post-training, and it inverts the usual sizing assumption: most of the GPU budget goes to generating rollouts, not to gradient steps. That changes how a fine-tuning cluster should be built. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for Agentic RAG: Caching and Cost Control Training Referen" }, { "type": "knowledge-base", "title": "Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities", "url": "https://rdp.in/gpu-mart/knowledge-base/fine-tuning-mixture-of-experts-memory-routing-realities/", "sku": "", "text": "MoE models activate few parameters but must hold all experts in memory. A widely cited example needs roughly 94 GB at FP16 for inference alone, and fine-tuning adds optimiser state on top. This sets out the memory maths and the practical paths. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for Agentic RAG: Caching and Cost Control Training Reference Archi" }, { "type": "knowledge-base", "title": "Digital Pathology at Scale: Whole-Slide Image AI GPU Planning", "url": "https://rdp.in/gpu-mart/knowledge-base/digital-pathology-whole-slide-image-ai-gpu-planning/", "sku": "", "text": "A whole-slide image is gigapixels, not megapixels, so pathology AI is a tiling and throughput problem before it is a model problem. Storage and scanning capacity usually constrain an Indian deployment long before GPU capacity does. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for Agentic RAG: Caching and Cost Control Training Reference Architecture: 8× H" }, { "type": "knowledge-base", "title": "AI Drug Discovery: GPU Planning for Protein and Molecular Models", "url": "https://rdp.in/gpu-mart/knowledge-base/ai-drug-discovery-gpu-planning-protein-molecular-models/", "sku": "", "text": "Structure prediction, docking and molecular dynamics have very different GPU profiles, and Indian pharma teams frequently size for the wrong one. This sets out where the compute actually goes across a discovery pipeline and how to build capacity around it. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for Agentic RAG: Caching and Cost Control Training Ref" }, { "type": "knowledge-base", "title": "Federated Learning Across Hospitals: GPU and Network Planning", "url": "https://rdp.in/gpu-mart/knowledge-base/federated-learning-hospitals-gpu-network-planning/", "sku": "", "text": "Federated learning trains a shared model without pooling patient data, which is why it appeals to Indian hospital networks under DPDP. The infrastructure cost is real: every participating site needs GPU capacity, and the slowest site sets the pace. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for Agentic RAG: Caching and Cost Control Training Reference A" }, { "type": "knowledge-base", "title": "Imaging Foundation Models: GPU Sizing for Radiology in 2026", "url": "https://rdp.in/gpu-mart/knowledge-base/imaging-foundation-models-gpu-sizing-radiology-2026/", "sku": "", "text": "Radiology moved from single-finding algorithms to foundation models covering many conditions in one pass, with the first such device cleared in January 2026. One model replacing fourteen changes both the GPU sizing and the deployment architecture. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for Agentic RAG: Caching and Cost Control Training Reference Ar" }, { "type": "knowledge-base", "title": "Content Provenance and Deepfake Detection: GPU Planning for Broadcast", "url": "https://rdp.in/gpu-mart/knowledge-base/content-provenance-deepfake-detection-gpu-planning-broadcast/", "sku": "", "text": "Provenance signing is cheap and reliable; deepfake detection is expensive and unreliable. Broadcasters should invest in C2PA-style credentials for their own output and treat detection as a triage aid, not a verdict. This sets out the GPU implications of both. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for Agentic RAG: Caching and Cost Control Training" }, { "type": "knowledge-base", "title": "AI Restoration at Archive Scale: GPU Throughput Planning", "url": "https://rdp.in/gpu-mart/knowledge-base/ai-restoration-archive-scale-gpu-throughput-planning/", "sku": "", "text": "Restoring a film archive is a throughput problem measured in frames, not files. A two-hour feature is around 172,800 frames, and a thousand-title library is billions. This shows how to size GPU capacity and where the pipeline actually stalls. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for Agentic RAG: Caching and Cost Control Training Reference Archite" }, { "type": "knowledge-base", "title": "Gaussian Splatting in Studio Pipelines: What It Changes for GPU Fleets", "url": "https://rdp.in/gpu-mart/knowledge-base/gaussian-splatting-studio-pipelines-gpu-fleet-impact/", "sku": "", "text": "3D Gaussian splatting reached production tooling in 2026 with native support in Nuke 17, Houdini 21, OpenUSD 26.03 and V-Ray 7. It renders orders of magnitude faster than NeRF, which shifts studio GPU demand from rendering toward capture and training. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for Agentic RAG: Caching and Cost Control Training Referenc" }, { "type": "knowledge-base", "title": "Virtual Production and LED Volumes: Real-Time GPU Sizing", "url": "https://rdp.in/gpu-mart/knowledge-base/virtual-production-led-volumes-real-time-gpu-sizing/", "sku": "", "text": "An LED volume is a hard real-time system: the wall must render camera-correct perspective every frame or the illusion breaks. This sets out how to size render nodes from wall pixel count, frame rate and scene complexity, plus the Indian stage realities. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for Agentic RAG: Caching and Cost Control Training Refere" }, { "type": "knowledge-base", "title": "Text-to-Video in Production: GPU Planning for Content Pipelines", "url": "https://rdp.in/gpu-mart/knowledge-base/text-to-video-production-gpu-planning-content-pipelines/", "sku": "", "text": "Studios in 2026 route between video models by scene type rather than standardising on one. Per-second API pricing spans roughly $0.05 to $0.75, and iteration multiplies it. That economics decides when owned GPU capacity beats renting. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for Agentic RAG: Caching and Cost Control Training Reference Architecture: 8" }, { "type": "knowledge-base", "title": "Engineering Copilots and PLM: On-Prem GPU Planning for Design Data", "url": "https://rdp.in/gpu-mart/knowledge-base/engineering-copilots-plm-on-prem-gpu-planning-design-data/", "sku": "", "text": "Engineering knowledge sits in CAD, PLM records, drawings and standards, not in prose. Building a copilot over it is a multimodal retrieval problem with a hard confidentiality constraint, which is why it usually lands on owned GPU infrastructure. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for Agentic RAG: Caching and Cost Control Training Reference Arch" }, { "type": "knowledge-base", "title": "Quality Inspection at Line Rate: Latency Budgets and Edge GPU Choice", "url": "https://rdp.in/gpu-mart/knowledge-base/quality-inspection-line-rate-latency-budgets-edge-gpu/", "sku": "", "text": "Line-rate inspection is a deadline problem, not a throughput problem. Parts per minute sets a hard cycle time, and every stage from trigger to reject actuator must fit inside it. This shows how to build the budget and choose hardware against it. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for Agentic RAG: Caching and Cost Control Training Reference Arch" }, { "type": "knowledge-base", "title": "Synthetic Data for Industrial Vision: GPU Budgets and Sim-to-Real", "url": "https://rdp.in/gpu-mart/knowledge-base/synthetic-data-industrial-vision-gpu-budgets-sim-to-real/", "sku": "", "text": "Defect detection fails on rare defects because you cannot photograph what has not happened yet. Synthetic generation renders the defect classes you lack, but the GPU budget sits in rendering, not training, and domain gap is the real risk. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for Agentic RAG: Caching and Cost Control Training Reference Architectur" }, { "type": "knowledge-base", "title": "Time-Series Foundation Models for Predictive Maintenance: Sizing the Stack", "url": "https://rdp.in/gpu-mart/knowledge-base/time-series-foundation-models-predictive-maintenance-sizing/", "sku": "", "text": "Pretrained time-series models now forecast machine behaviour zero-shot, with reported throughput above 300 forecasts per second on a single GPU. That removes the per-asset training burden that stalled most Indian predictive maintenance programmes. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for Agentic RAG: Caching and Cost Control Training Reference Ar" }, { "type": "knowledge-base", "title": "Physical AI in Indian Factories: GPU Planning for Robotics Pilots", "url": "https://rdp.in/gpu-mart/knowledge-base/physical-ai-indian-factories-gpu-planning-robotics-pilots/", "sku": "", "text": "Physical AI needs three distinct compute tiers: simulation for training policies, a training cluster for the models, and edge inference on the robot. Indian manufacturers including Ola Electric and Wipro PARI are building exactly this stack. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for Agentic RAG: Caching and Cost Control Training Reference Architec" }, { "type": "knowledge-base", "title": "Entry Workstation Refresh Cycles: When to Replace and When to Wait", "url": "https://rdp.in/gpu-mart/knowledge-base/entry-workstation-refresh-cycles-replace-or-wait-2026/", "sku": "", "text": "The refresh question in 2026 is not raw speed but VRAM and FP4 support. A card that cannot hold the models your team now uses is obsolete regardless of its FLOPS. This gives a decision rule, plus the India-specific cost factors. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for Agentic RAG: Caching and Cost Control Training Reference Architecture: 8× H200" }, { "type": "knowledge-base", "title": "Running Local Agents on Entry Hardware: Limits and Workarounds", "url": "https://rdp.in/gpu-mart/knowledge-base/local-agents-entry-hardware-limits-workarounds-2026/", "sku": "", "text": "Agentic workflows multiply model calls and grow context with every step, which punishes small VRAM budgets harder than chat does. This sets out what genuinely runs on a 24-32 GB entry workstation and the routing patterns that make it viable. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for Agentic RAG: Caching and Cost Control Training Reference Architec" }, { "type": "knowledge-base", "title": "Entry AI Workstations for Indian Colleges and Research Labs (2026)", "url": "https://rdp.in/gpu-mart/knowledge-base/entry-ai-workstations-indian-colleges-research-labs-2026/", "sku": "", "text": "Academic AI labs in 2026 face a specific squeeze: memory prices up sharply, curricula demanding hands-on GPU work, and subsidised national compute available for bursts. This sets out how to configure entry workstations that stay useful for four years. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for Agentic RAG: Caching and Cost Control Training Referenc" }, { "type": "knowledge-base", "title": "Vision AI on a Single 32 GB Card: What an Entry Workstation Handles", "url": "https://rdp.in/gpu-mart/knowledge-base/vision-ai-single-32gb-card-entry-workstation-capability/", "sku": "", "text": "A 32 GB Blackwell-class workstation card runs detection, segmentation, OCR and mid-size vision-language models comfortably. This sets out realistic throughput expectations, where 32 GB stops being enough, and how to plan a vision project on entry hardware. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for Agentic RAG: Caching and Cost Control Training Ref" }, { "type": "knowledge-base", "title": "Desk-Side Mini AI Boxes in 2026: Where Unified Memory Fits", "url": "https://rdp.in/gpu-mart/knowledge-base/desk-side-mini-ai-boxes-2026-unified-memory-fit/", "sku": "", "text": "Mini AI boxes with large unified memory pools load models a discrete GPU cannot hold, but at a fraction of the memory bandwidth. That trade decides what they are good for: model bring-up and batch work, not interactive serving of large models. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for Agentic RAG: Caching and Cost Control Training Reference Archit" }, { "type": "knowledge-base", "title": "Insurance Claims Automation: GPU Planning for Document AI at Scale", "url": "https://rdp.in/gpu-mart/knowledge-base/insurance-claims-automation-gpu-planning-document-ai/", "sku": "", "text": "Claims automation is a document AI problem before it is an LLM problem. Vision-language models now read scanned forms, prescriptions and estimates end-to-end, which changes GPU sizing: throughput is governed by pages per hour, not queries per second. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for Agentic RAG: Caching and Cost Control Training Reference" }, { "type": "knowledge-base", "title": "Where BFSI AI Compute Must Sit: RBI Localisation Meets DPDP", "url": "https://rdp.in/gpu-mart/knowledge-base/bfsi-ai-compute-location-rbi-localisation-dpdp/", "sku": "", "text": "DPDP takes a permissive line on cross-border transfer with no restricted-country list notified as of mid-2026, but RBI’s payment-data mandate is stricter and still binds. For BFSI AI infrastructure, the sectoral rule, not DPDP, usually decides where the GPUs go. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for Agentic RAG: Caching and Cost Control" }, { "type": "knowledge-base", "title": "Confidential Computing on GPUs: Trusted Execution for Regulated AI", "url": "https://rdp.in/gpu-mart/knowledge-base/confidential-computing-gpus-trusted-execution-regulated-ai/", "sku": "", "text": "GPU confidential computing encrypts model weights and data in VRAM and produces a hardware-signed attestation. NVIDIA reports near-parity throughput on Blackwell. For Indian regulated workloads that is the difference between a policy argument and a cryptographic one. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for Agentic RAG: Caching and Cost Control T" }, { "type": "knowledge-base", "title": "Fraud Detection at UPI Scale: GPU Sizing for Sub-100 ms Decisions", "url": "https://rdp.in/gpu-mart/knowledge-base/fraud-detection-upi-scale-gpu-sizing-sub-100ms/", "sku": "", "text": "UPI processed 23.2 billion transactions in a single month of 2026, over 66 crore a day. Scoring that volume with deep models inside a sub-100 ms budget is a throughput and tail-latency problem, and PCIe transfer is often the hidden cost. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for Agentic RAG: Caching and Cost Control Training Reference Architecture" }, { "type": "knowledge-base", "title": "Agentic AI in Banking: GPU Infrastructure Under FREE-AI", "url": "https://rdp.in/gpu-mart/knowledge-base/agentic-ai-banking-gpu-infrastructure-free-ai-2026/", "sku": "", "text": "Agentic AI in banking multiplies inference per business action and adds an audit obligation for every step. Under RBI’s FREE-AI framework, that combination pushes Indian banks toward owned, in-country GPU capacity with per-step logging built into the architecture. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for Agentic RAG: Caching and Cost Contro" }, { "type": "knowledge-base", "title": "Compute Budgeting After the Pre-Training Plateau", "url": "https://rdp.in/gpu-mart/knowledge-base/compute-budgeting-after-pre-training-plateau-2026/", "sku": "", "text": "Frontier compute is shifting from pre-training toward post-training and inference-time reasoning. That changes how an enterprise budgets GPU capacity: fewer giant runs, more RL loops and evaluation, and a different balance between training and serving hardware. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for Agentic RAG: Caching and Cost Control Trainin" }, { "type": "knowledge-base", "title": "Training Goodput at 10,000 GPUs: Failures, MFU and Honest Throughput", "url": "https://rdp.in/gpu-mart/knowledge-base/training-goodput-10000-gpus-failures-mfu-throughput/", "sku": "", "text": "Llama 3 pre-training on 16,384 GPUs saw 466 interruptions in 54 days. At that failure rate, the number that matters is goodput, not peak FLOPS. This explains MFU, failure modes, stragglers and how to specify throughput you will actually get. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for Agentic RAG: Caching and Cost Control Training Reference Architec" }, { "type": "knowledge-base", "title": "The 2026 Memory and NAND Squeeze: Procuring AI Storage Under Allocation", "url": "https://rdp.in/gpu-mart/knowledge-base/2026-memory-nand-squeeze-procuring-ai-storage-allocation/", "sku": "", "text": "NAND contract prices were reported rising 70-75 percent quarter-on-quarter in Q2 2026 as fabs shifted capacity to HBM. With new fab output unlikely before late 2027, AI storage procurement in India needs allocation-aware design, not just a capacity number. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for Agentic RAG: Caching and Cost Control Training Ref" }, { "type": "knowledge-base", "title": "Checkpoint Storage at Frontier Scale: Sizing for 2026-2028", "url": "https://rdp.in/gpu-mart/knowledge-base/checkpoint-storage-frontier-scale-sizing-2026-2028/", "sku": "", "text": "Published work puts checkpoint overhead at 12-43 percent of total training time, with a 16,000-accelerator cluster taking roughly 155 checkpoints a day. This explains how to size checkpoint capacity, bandwidth and retention so the storage tier stops stealing training throughput. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for Agentic RAG: Caching and Co" }, { "type": "knowledge-base", "title": "Vector Index Sizing: From 10 Million to 1 Billion Embeddings", "url": "https://rdp.in/gpu-mart/knowledge-base/vector-index-sizing-10-million-to-1-billion-embeddings/", "sku": "", "text": "A billion 1536-dimension vectors in a plain HNSW index needs terabytes of RAM. Quantization cuts that by 4x to 32x, and disk-based indexes move the graph to NVMe. This is how to size memory, storage and GPUs across three corpus scales. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for Agentic RAG: Caching and Cost Control Training Reference Architecture:" }, { "type": "knowledge-base", "title": "GPUDirect Storage and DPU Offload: Designing the AI Data Path", "url": "https://rdp.in/gpu-mart/knowledge-base/gpudirect-storage-dpu-offload-ai-data-path-design/", "sku": "", "text": "GPUDirect Storage moves data between NVMe and GPU memory without a host bounce buffer; DPU offload removes the storage host from the path entirely. Together they define the 2026 AI data path. This is what to specify, and where the benefit is real. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for Agentic RAG: Caching and Cost Control Training Reference Ar" }, { "type": "knowledge-base", "title": "Object Storage Enters the Training Loop: S3-over-RDMA in 2026", "url": "https://rdp.in/gpu-mart/knowledge-base/object-storage-s3-over-rdma-ai-training-loop-2026/", "sku": "", "text": "Object storage used to be the cold tier behind a parallel filesystem. In 2026, S3-over-RDMA and DPU-resident object stores put it directly in the GPU data path, which changes how AI storage tiers are designed and what an on-prem cluster actually needs. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for Agentic RAG: Caching and Cost Control Training Referen" }, { "type": "knowledge-base", "title": "800 VDC Power: Preparing Training Halls for Megawatt AI Racks", "url": "https://rdp.in/gpu-mart/knowledge-base/800-vdc-power-architecture-megawatt-ai-training-halls/", "sku": "", "text": "Rack power went from about 40 kW in the Hopper era to roughly 120 kW with Blackwell, and 800 VDC distribution arrives with megawatt racks from 2027. This explains what changes electrically, what it saves, and what Indian facility teams should decide now. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for Agentic RAG: Caching and Cost Control Training Refer" }, { "type": "knowledge-base", "title": "HBM4 and the Memory Wall: What It Means for 2027 Training Clusters", "url": "https://rdp.in/gpu-mart/knowledge-base/hbm4-memory-wall-2027-training-cluster-planning/", "sku": "", "text": "HBM4 doubles the memory interface to 2048 bits and entered mass production in early 2026. Because large-model training is bandwidth-bound more often than FLOPS-bound, that step decides achieved utilisation, cluster size and, through supply constraints, GPU pricing through 2027. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for Agentic RAG: Caching and Cos" }, { "type": "knowledge-base", "title": "Vera Rubin NVL144: What the 2026 Training Platform Changes for Cluster Design", "url": "https://rdp.in/gpu-mart/knowledge-base/vera-rubin-nvl144-2026-training-platform-cluster-design/", "sku": "", "text": "Vera Rubin NVL144 keeps the rack as the scale-up domain but raises memory, interconnect and power together. HBM4, NVLink 6 and ConnectX-9 change how many racks a training run needs, and the power step decides what your facility must support before the first rack lands. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for Agentic RAG: Caching and Cost Control" }, { "type": "knowledge-base", "title": "GPU RDP Buyer Search Guide for Indian AI Teams", "url": "https://rdp.in/gpu-mart/knowledge-base/gpu-rdp-buyer-search-guide-for-indian-ai-teams/", "sku": "", "text": "Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training […] . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image" }, { "type": "knowledge-base", "title": "GPU-Accelerated Genomics: Sizing Secondary Analysis for Clinical Labs in 2026", "url": "https://rdp.in/gpu-mart/knowledge-base/gpu-accelerated-genomics-secondary-analysis-sizing-2026/", "sku": "", "text": "Turning raw sequencer reads into variants is now GPU-bound work. NVIDIA Parabricks 4.6 with DeepVariant runs short-read whole-genome secondary analysis up to ~100x faster than CPU pipelines. How to size on-prem GPU capacity for a clinical genomics lab, and why genome data residency points on-prem. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for Agentic" }, { "type": "knowledge-base", "title": "Media GenAI Workstation Sizing Guide for India", "url": "https://rdp.in/gpu-mart/knowledge-base/media-genai-workstation-sizing-guide-for-india/", "sku": "", "text": "Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training […] . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image" }, { "type": "knowledge-base", "title": "Manufacturing Vision AI Edge GPU Deployment Playbook", "url": "https://rdp.in/gpu-mart/knowledge-base/manufacturing-vision-ai-edge-gpu-deployment-playbook/", "sku": "", "text": "Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training […] . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image" }, { "type": "knowledge-base", "title": "AI Dubbing at OTT Scale: GPU Pipelines for Indian-Language Localisation", "url": "https://rdp.in/gpu-mart/knowledge-base/ai-dubbing-ott-scale-gpu-pipelines-indian-languages/", "sku": "", "text": "AI dubbing runs five GPU stages – ASR, translation, voice synthesis, lip-sync rendering and QC – cutting localisation cost up to 10x as regional languages pass 60% of Indian OTT viewing. Validate per-language phonetics, hold vendors to 1.5-frame sync bars, log voice-cloning consent, and own the pipeline at catalog volume. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retri" }, { "type": "knowledge-base", "title": "Shop-Floor Copilots: On-Prem RAG for Maintenance and SOP Knowledge", "url": "https://rdp.in/gpu-mart/knowledge-base/shop-floor-copilots-on-prem-rag-maintenance-sop/", "sku": "", "text": "An industrial copilot is domain RAG over SOPs, manuals and maintenance history with voice and multilingual support for the floor. A 2-4 GPU per-plant server carries the load; the real work is cleaning jargon-dense logs into a dictionary and problem-fix knowledge base, with citations mandatory on every answer. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering" }, { "type": "knowledge-base", "title": "Disaggregated Inference: Splitting Prefill and Decode in 2026", "url": "https://rdp.in/gpu-mart/knowledge-base/disaggregated-inference-prefill-decode-2026/", "sku": "", "text": "Prefill is compute-bound, decode is memory-bound, and 2026 serving stacks split them onto dedicated GPU pools with KV cache shipped between – worth 2-3x throughput at node scale and far more on NVLink domains. Below about 8 GPUs per model, chunked prefill and good batching capture most of the win. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for Ag" }, { "type": "knowledge-base", "title": "The Air-Cooled Middle: RTX PRO Servers Between Workstation and HGX", "url": "https://rdp.in/gpu-mart/knowledge-base/rtx-pro-servers-air-cooled-middle-enterprise-ai/", "sku": "", "text": "MGX-based RTX PRO servers pack up to eight 96 GB GDDR7 GPUs – 768 GB aggregate – into standard air-cooled racks, serving multiple 70B-class replicas plus rendering and vGPU duty at a fraction of HGX cost and facility burden. The limits: no NVLink, so training and trillion-class serving stay on flagship nodes. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context" }, { "type": "knowledge-base", "title": "Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers", "url": "https://rdp.in/gpu-mart/knowledge-base/adaptive-rag-2026-hybrid-graph-agentic-tiers/", "sku": "", "text": "Enterprise RAG in 2026 is a routed portfolio: hybrid retrieval absorbs most lookups, GraphRAG handles cross-document reasoning at heavy index-time cost, and agentic loops multiply tokens 5-20x per hard question. Size serving for the multiplier, enforce iteration budgets, and give agents only the querying user permissions. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context" }, { "type": "knowledge-base", "title": "Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure", "url": "https://rdp.in/gpu-mart/knowledge-base/beyond-sft-sizing-dpo-rlvr-post-training-infrastructure/", "sku": "", "text": "The 2026 post-training recipe is SFT, then DPO, then RL with verifiable rewards. DPO doubles resident model copies; GRPO halved RL memory by dropping the critic, putting 7-32B reasoning training on one to two big cards. Production RL splits into a trainer plus a rollout farm – spec the rollouts like an inference fleet. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Cont" }, { "type": "knowledge-base", "title": "FP8 to FP4: How Low-Precision Training Reshapes Cluster Sizing", "url": "https://rdp.in/gpu-mart/knowledge-base/fp8-fp4-low-precision-training-cluster-sizing/", "sku": "", "text": "FP8 pretraining is the 2026 default and NVFP4 4-bit recipes are validated to 120B scale with FP8-matching accuracy, doubling arithmetic and halving memory on Blackwell-class silicon. Size clusters in tokens-per-day at your real precision and measured MFU – and treat native FP4 support as a depreciation hedge. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engine" }, { "type": "knowledge-base", "title": "KV Cache Offloading: The New Storage Tier in AI Inference Servers", "url": "https://rdp.in/gpu-mart/knowledge-base/kv-cache-offloading-new-storage-tier-ai-inference/", "sku": "", "text": "Long-context and agentic inference made the KV cache a storage problem: about 300-350 KB per token on 70B-class models spills from VRAM to DRAM, NVMe and shared tiers, with LMCache-class layers reporting 3-10x latency gains on hits. Spec 1-2 TB RAM and high-endurance NVMe on 2026 inference nodes. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for Agentic R" }, { "type": "knowledge-base", "title": "FREE-AI and Model Risk Rules: Infrastructure Consequences for Banks", "url": "https://rdp.in/gpu-mart/knowledge-base/free-ai-model-risk-rules-infrastructure-banks/", "sku": "", "text": "RBI FREE-AI (2025) and the draft 2026 Model Risk Management guidance make Indian bank AI examinable: inventoried models, validation environments, challenger serving, full logging and rollback. Plan 1.3-1.6x naive serving capacity, keep customer-data inference in-country, and climb from augmentation to decisioning. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Enginee" }, { "type": "knowledge-base", "title": "Ambient Clinical AI Scribes: On-Prem GPU Planning for Indian Hospitals", "url": "https://rdp.in/gpu-mart/knowledge-base/ambient-clinical-ai-scribes-on-prem-gpu-indian-hospitals/", "sku": "", "text": "An ambient scribe is three GPU workloads – streaming ASR, clinical extraction, LLM note drafting – and a 2-4 GPU server covers a large Indian OPD. Western benchmarks fail on code-switched speech (15-25% WER reported), so demand local-audio evidence, fine-tune on-site, keep processing in-country and let the clinician sign. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retri" }, { "type": "knowledge-base", "title": "Generative AI in the VFX Pipeline: GPU Planning for Studios", "url": "https://rdp.in/gpu-mart/knowledge-base/generative-ai-vfx-pipeline-gpu-planning-studios/", "sku": "", "text": "Generative stages now sit inside the VFX pipeline: diffusion previs on 24-48 GB artist seats, roto and upscale batches on farm nodes, video generation on 80 GB-class hardware. Indian studios under client security audits favour on-prem open stacks – plates never leave the facility – and one converged GPU estate. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Contex" }, { "type": "knowledge-base", "title": "Digital Twins and Physical AI: GPU Planning for Indian Factories", "url": "https://rdp.in/gpu-mart/knowledge-base/digital-twins-physical-ai-gpu-planning-indian-factories/", "sku": "", "text": "A digital-twin programme is three GPU estates: RTX workstations for authoring, batch servers for synthetic data and robot-policy training, and ruggedised edge inference on the line. Indian lighthouse projects validate the stack, but the honest entry is one workstation, one cell and rented simulation compute. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering f" }, { "type": "knowledge-base", "title": "Self-Hosted Coding Assistants: Running Coder LLMs on Entry Workstations", "url": "https://rdp.in/gpu-mart/knowledge-base/self-hosted-coding-assistants-entry-workstations/", "sku": "", "text": "Open 24-32B coder models now benchmark near commercial APIs and run on a 24-32 GB entry workstation with 30-60 ms local completion latency cloud endpoints cannot match. For Indian services firms, NDA and DPDP compliance – client code never leaving the building – is the deciding argument; one card can serve several developers. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video R" }, { "type": "knowledge-base", "title": "Entry AI Workstations in 2026: What 16, 24 and 32 GB Really Run", "url": "https://rdp.in/gpu-mart/knowledge-base/entry-ai-workstations-2026-16-24-32gb-vram-guide/", "sku": "", "text": "At the entry tier, VRAM decides everything: 16 GB is a learning machine, 24 GB a value point for 7-13B work, and 32 GB comfortably serves quantised 30B models and QLoRA-fine-tunes 13B. Consumer flagships win on speed, professional cards on ECC and support; 64-128 GB RAM and NVMe keep the GPU fed. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for Agentic R" }, { "type": "knowledge-base", "title": "Day-2 Operations for Rack-Scale AI: Failures, Monitoring and Service", "url": "https://rdp.in/gpu-mart/knowledge-base/day-2-operations-rack-scale-ai-failures-monitoring-service/", "sku": "", "text": "Dense GPU systems fail as routine – Meta logged 419 interruptions in 54 days at 16k-GPU scale – so rack-scale readiness means DCGM-based trend monitoring, 30-60 minute checkpoint cadence, trained tray-swap service with in-country spares, and staged firmware. Contract the operating model with the hardware. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engi" }, { "type": "knowledge-base", "title": "Token Economics for Rack-Scale AI: Cost per Million Tokens, Honestly", "url": "https://rdp.in/gpu-mart/knowledge-base/token-economics-rack-scale-ai-cost-per-million-tokens/", "sku": "", "text": "Owned token cost is amortised capex, power, facility and ops divided by tokens actually served – utilisation dominates. Vendor multipliers like 35x vs Hopper assume saturated FP4 reasoning workloads; benchmark your own mix at 30-70% utilisation, where owned racks still undercut API pricing by orders of magnitude. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context En" }, { "type": "knowledge-base", "title": "Sovereign AI Pods: Rack-Scale Planning for India-Controlled Compute", "url": "https://rdp.in/gpu-mart/knowledge-base/sovereign-ai-pods-rack-scale-planning-india/", "sku": "", "text": "A sovereign AI pod is 1-4 racks of compute, storage and fabric operated under Indian jurisdiction: local keys, cleared admin access, contained telemetry and in-country logs. IndiaAI public capacity near $1/GPU-hour covers development; pods carry regulated, classified and always-on workloads the shared pool cannot. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Enginee" }, { "type": "knowledge-base", "title": "Buy Blackwell Ultra or Wait for Rubin? Flagship Timing for 2026-27", "url": "https://rdp.in/gpu-mart/knowledge-base/buy-blackwell-ultra-or-wait-for-rubin-flagship-timing/", "sku": "", "text": "Vera Rubin is in production with cloud shipments from H2 2026, but enterprise racks realistically land in 2027. Deployed GB300-class output for 12-18 months usually beats the successor delta; wait only when facility or budget gates already force a 2027 start, and then reserve Rubin allocation early. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for Agenti" }, { "type": "knowledge-base", "title": "One Rack or Nine Nodes: The Rack-Scale vs Scale-Out Decision", "url": "https://rdp.in/gpu-mart/knowledge-base/rack-scale-vs-scale-out-nvl72-vs-8-gpu-nodes/", "sku": "", "text": "The flagship-tier choice is unit of scale: nine HGX B300-class nodes or one GB300 NVL72 rack fusing 72 GPUs and about 21 TB of HBM into a single 130 TB/s NVLink domain. Rack-scale wins for trillion-class serving and long-context reasoning; discrete nodes win on granularity, blast radius and facility flexibility. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineeri" }, { "type": "knowledge-base", "title": "Hosting 100 kW Racks in India: Facility Readiness for Rack-Scale AI", "url": "https://rdp.in/gpu-mart/knowledge-base/hosting-100kw-racks-india-facility-readiness-rack-scale-ai/", "sku": "", "text": "A 120 kW NVL72-class rack exceeds most legacy Indian hall designs, so facility readiness is the long pole: direct-to-chip liquid cooling, 415 V high-amperage feeds, 2-tonne floor loading and contracted PUE. AI-ready capacity is concentrated in new-build campuses – verify the hall, not the brand, and reserve early. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context E" }, { "type": "knowledge-base", "title": "AI Workstation TCO in India: Duties, GST and the Cloud Crossover", "url": "https://rdp.in/gpu-mart/knowledge-base/ai-workstation-tco-india-duties-gst-cloud-crossover/", "sku": "", "text": "GPU hardware enters India at 0% basic duty under ITA-1, and the 18% IGST is input-creditable, so the buy-vs-rent question is pure utilisation arithmetic. Against $2-3/GPU-hour cloud rates, a daily-driver workstation pays back in 12-24 months; bursty training keeps renting, ideally in-country. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for Agentic RAG:" }, { "type": "knowledge-base", "title": "From Desk to Server Room: When a Team Outgrows AI Workstations", "url": "https://rdp.in/gpu-mart/knowledge-base/when-team-outgrows-ai-workstations-graduation-path/", "sku": "", "text": "Four signals say a team has outgrown workstations: GPU queueing, duplicated model weights, uptime needs and VRAM ceilings. Measure two weeks of utilisation, then buy a boring first server – 4-8 GPUs, NVMe, a Slurm-class queue – and keep workstations as the interactive development tier. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for Agentic" }, { "type": "knowledge-base", "title": "One Card, Two Pipelines: Hybrid Rendering and AI Workstations in 2026", "url": "https://rdp.in/gpu-mart/knowledge-base/hybrid-rendering-ai-workstation-planning-2026/", "sku": "", "text": "Rendering and AI converged on the same silicon: 96 GB Blackwell workstation cards run V-Ray by day and diffusion or 70B inference overnight, while DLSS 4 and neural texture compression rewrite VRAM budgets. Duty-cycle the machine, keep big scenes and big models in separate sessions, and exit hybrid when either load turns continuous. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrie" }, { "type": "knowledge-base", "title": "Fine-Tuning LLMs on a Workstation: LoRA and QLoRA Memory Math", "url": "https://rdp.in/gpu-mart/knowledge-base/fine-tuning-llms-workstation-lora-qlora-memory-math/", "sku": "", "text": "Fine-tuning memory is weights plus gradients, optimiser states and activations. QLoRA needs about 12 GB for 7B, 44 GB for 32B and 88 GB for 70B, so a 96 GB workstation card covers 70B QLoRA. Full fine-tuning beyond 7B, long-context runs and team-scale throughput still belong on multi-GPU servers. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for Agentic R" }, { "type": "knowledge-base", "title": "Dual-GPU AI Workstations Without NVLink: Planning a 192 GB Tower", "url": "https://rdp.in/gpu-mart/knowledge-base/dual-gpu-ai-workstation-planning-192gb-no-nvlink/", "sku": "", "text": "Workstation Blackwell cards have no NVLink, so a dual 96 GB tower pools 192 GB over PCIe 5.0. Choose 300 W Max-Q cards for multi-GPU builds, favour pipeline parallelism and per-GPU jobs over tensor parallelism, and spec a 128-lane platform with a 1,600 W-class PSU from day one. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for Agentic RAG: Caching and Cos" }, { "type": "knowledge-base", "title": "The 96 GB Desk-Side Tier: What a Mid-Range AI Workstation Runs in 2026", "url": "https://rdp.in/gpu-mart/knowledge-base/96gb-mid-tier-ai-workstation-what-it-runs-2026/", "sku": "", "text": "A 96 GB-class workstation card (RTX PRO 6000 Blackwell: 24,064 CUDA cores, ECC GDDR7 at ~1.8 TB/s) runs quantised 70B inference and 7-32B fine-tuning on a desk. The ceiling: unquantised 100B+ models, multi-day training and SLO-bound serving stay on servers. Payback vs cloud lands in 12-24 months at daily use. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering" }, { "type": "knowledge-base", "title": "Festive-Peak AI Capacity Planning for Indian E-commerce", "url": "https://rdp.in/gpu-mart/knowledge-base/festive-peak-ai-capacity-planning-indian-ecommerce/", "sku": "", "text": "Festive events run about 3.5x business-as-usual GMV and multiply AI serving load further. The workable pattern: own a GPU baseline sized near 1.5x BAU, rent in-country burst for the peak window, pre-plan a model degradation waterfall, and fence off fraud scoring and checkout ranking from any degradation. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for A" }, { "type": "knowledge-base", "title": "Hybrid Product Search in 2026: GPU Planning for Semantic and Visual Search", "url": "https://rdp.in/gpu-mart/knowledge-base/hybrid-product-search-gpu-planning-semantic-visual-search/", "sku": "", "text": "Hybrid product search fuses BM25, vector retrieval and a GPU cross-encoder reranker inside a 50-200 ms budget. One L4/L40S-class GPU covers embedding and reranking for mid-market storefronts; vector memory (about 6 KB per unquantised vector) is the real scaling cost, and visual search joins the same pool. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for" }, { "type": "knowledge-base", "title": "Demand Forecasting GPUs: Sizing for Retail and Quick Commerce", "url": "https://rdp.in/gpu-mart/knowledge-base/demand-forecasting-gpu-sizing-retail-quick-commerce/", "sku": "", "text": "Demand forecasting is retrain-dominated: size GPUs for the nightly training window across millions of SKU-location series, not for serving. CPUs suffice below a million series; quick commerce forces 4-8 GPU nodes for intra-day hyper-local refresh, and India-specific signals beat model upgrades on accuracy. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for" }, { "type": "knowledge-base", "title": "Catalog Content Generation at Scale: GPU Planning for Retail GenAI", "url": "https://rdp.in/gpu-mart/knowledge-base/catalog-content-generation-gpu-planning-retail-genai/", "sku": "", "text": "Catalog enrichment is now a batch GPU workload chaining LLM copy, VLM tagging and diffusion imagery. Owned GPUs beat generation APIs once utilisation passes 50-70%; a 1-4 GPU server covers most Indian catalogs, with multilingual listing refresh at near-zero marginal cost and risk-tiered human review. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for Agent" }, { "type": "knowledge-base", "title": "In-Store Vision AI: Edge GPU Planning for Retail Chains", "url": "https://rdp.in/gpu-mart/knowledge-base/in-store-vision-ai-edge-gpu-planning-retail-chains/", "sku": "", "text": "In-store vision AI runs as a hybrid: edge GPU nodes handle 8-30 camera streams each for real-time theft and shelf alerts, while a central 2-8 GPU server retrains models and aggregates analytics. Size by measured streams-per-GPU, keep footage in-country, and underwrite 6-12 month payback conservatively. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for Age" }, { "type": "knowledge-base", "title": "Agentic Commerce Infrastructure: GPU Planning for AI Shopping Agents", "url": "https://rdp.in/gpu-mart/knowledge-base/agentic-commerce-gpu-infrastructure-ai-shopping-agents/", "sku": "", "text": "AI shopping agents turn retail inference into sustained, machine-speed API traffic. Merchants need a 7-13B tool-calling LLM tier on L40S/H100-class inference GPUs beside existing ranking, structured feeds first, and India-hosted endpoints for ONDC and WhatsApp-led buying flows under the DPDP Act. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for Agentic R" }, { "type": "knowledge-base", "title": "GPU Sizing for E-commerce Recommendation and Personalization (2026)", "url": "https://rdp.in/gpu-mart/knowledge-base/gpu-sizing-ecommerce-recommendation-personalization-2026/", "sku": "", "text": "E-commerce recommendation sizing in 2026 hinges on peak requests per second, a sub-100 ms latency budget, and embedding-table memory. Most Indian retailers need one L4/L40S-class inference server to a small 4-8 GPU pool, with batch pre-compute covering cold surfaces and DPDP compliance favouring India-hosted serving. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engi" }, { "type": "knowledge-base", "title": "Small Language Models and the NPU Myth: What Actually Runs Locally in 2026", "url": "https://rdp.in/gpu-mart/knowledge-base/small-language-models-npu-myth-what-runs-locally-2026/", "sku": "", "text": "A 3–9B model now carries most of an agentic loop locally, faster and more privately than a cloud API. But the NPU is not what runs it: Ollama, llama.cpp and LM Studio don’t route to the NPU at all, and no NPU runs a 70B model. Buy VRAM, not TOPS. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for Agentic RAG: Caching and Cost Control Training Referen" }, { "type": "knowledge-base", "title": "Local AI Workstations in 2026: Running 70B Models at Your Desk", "url": "https://rdp.in/gpu-mart/knowledge-base/local-ai-workstations-2026-running-70b-models-at-your-desk/", "sku": "", "text": "With 96 GB of GDDR7 on a single RTX PRO 6000 Blackwell card, a desk-side workstation can now hold a 70B model at Q8 — and two Max-Q cards pool to 192 GB for unquantised 70B inference and fine-tuning. What local AI workstations own in 2026, and where they stop. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for Agentic RAG: Caching and Cost Control Training" }, { "type": "knowledge-base", "title": "Blackwell Ultra to Vera Rubin to Feynman: The 2026–2028 AI Training Cluster Roadmap", "url": "https://rdp.in/gpu-mart/knowledge-base/ai-training-cluster-roadmap-2026-2028-blackwell-ultra-vera-rubin-feynman/", "sku": "", "text": "NVIDIA now ships one AI architecture per year: Blackwell Ultra today, Vera Rubin from H2 2026, Rubin Ultra in 2027, Feynman in 2028. For most training clusters the deciding factor is no longer peak FLOPS but whether your site can power and cool the generation you pick. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for Agentic RAG: Caching and Cost Control" }, { "type": "knowledge-base", "title": "Healthcare Imaging GPU Server Planning in India", "url": "https://rdp.in/gpu-mart/knowledge-base/healthcare-imaging-gpu-server-planning-in-india/", "sku": "", "text": "Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training […] . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image" }, { "type": "knowledge-base", "title": "H200 vs H100 GPU Server Procurement in India", "url": "https://rdp.in/gpu-mart/knowledge-base/h200-vs-h100-gpu-server-procurement-in-india/", "sku": "", "text": "Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training […] . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image" }, { "type": "knowledge-base", "title": "GPU Storage Planning for LLM Checkpoints and RAG Indexes", "url": "https://rdp.in/gpu-mart/knowledge-base/gpu-storage-planning-for-llm-checkpoints-and-rag-indexes/", "sku": "", "text": "Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training […] . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image" }, { "type": "knowledge-base", "title": "GeM GPU Server Procurement Guide for Public Sector AI", "url": "https://rdp.in/gpu-mart/knowledge-base/gem-gpu-server-procurement-guide-for-public-sector-ai/", "sku": "", "text": "Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training […] . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image" }, { "type": "knowledge-base", "title": "DPDP-Ready AI Infrastructure Planning for GPU Mart Buyers", "url": "https://rdp.in/gpu-mart/knowledge-base/dpdp-ready-ai-infrastructure-planning-for-gpu-mart-buyers/", "sku": "", "text": "Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training […] . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image" }, { "type": "knowledge-base", "title": "AI-Citation-Ready GPU Server FAQ for RDP GPU Mart", "url": "https://rdp.in/gpu-mart/knowledge-base/ai-citation-ready-gpu-server-faq-for-rdp-gpu-mart/", "sku": "", "text": "Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training […] . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image" }, { "type": "knowledge-base", "title": "RAG GPU Server Reference Architecture for India", "url": "https://rdp.in/gpu-mart/knowledge-base/rag-gpu-server-reference-architecture-for-india/", "sku": "", "text": "Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training […] . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image" }, { "type": "knowledge-base", "title": "GPU Cluster Networking for Training and Fine-Tuning", "url": "https://rdp.in/gpu-mart/knowledge-base/gpu-cluster-networking-for-training-and-fine-tuning/", "sku": "", "text": "Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training […] . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image" }, { "type": "knowledge-base", "title": "NVIDIA GB300 NVL72 Supercluster: Inside the 8-Rack Containerised AI Factory Node", "url": "https://rdp.in/gpu-mart/knowledge-base/gb300-nvl72-supercluster-8-rack-containerised-ai-factory-node/", "sku": "", "text": "The NVIDIA GB300 NVL72 supercluster packs eight NVL72 racks — 576 Blackwell Ultra B300 GPUs and 288 Grace CPUs — into one containerised AI factory node delivering ~11.5 EFLOPS FP4, ~165.6 TB HBM3e and a 1,040 TB/s NVLink domain, cooled and powered as a single turnkey unit. . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image and Video Retrieval Context Engineering for Agentic RAG: Caching and Cost Con" }, { "type": "knowledge-base", "title": "BFSI Private AI GPU Server Controls and Auditability", "url": "https://rdp.in/gpu-mart/knowledge-base/bfsi-private-ai-gpu-server-controls-and-auditability/", "sku": "", "text": "Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training […] . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image" }, { "type": "knowledge-base", "title": "AI Workstation vs GPU Server: RDP Buyer Decision Guide", "url": "https://rdp.in/gpu-mart/knowledge-base/ai-workstation-vs-gpu-server-rdp-buyer-decision-guide/", "sku": "", "text": "Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training […] . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image" }, { "type": "knowledge-base", "title": "GPU RDP Workstation Buyers Guide for Indian AI Teams", "url": "https://rdp.in/gpu-mart/knowledge-base/gpu-rdp-workstation-buyers-guide-for-indian-ai-teams/", "sku": "", "text": "Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training […] . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image" }, { "type": "knowledge-base", "title": "GPU Mart Technical Guide: gpu server india", "url": "https://rdp.in/gpu-mart/knowledge-base/gpu-mart-technical-guide-gpu-server-india/", "sku": "", "text": "Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training […] . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image" }, { "type": "knowledge-base", "title": "GPU Server India Sizing Checklist for AI Inference", "url": "https://rdp.in/gpu-mart/knowledge-base/gpu-server-india-sizing-checklist-for-ai-inference/", "sku": "", "text": "Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training […] . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image" }, { "type": "knowledge-base", "title": "AI Factory Power and Cooling Checklist for GPU Clusters", "url": "https://rdp.in/gpu-mart/knowledge-base/ai-factory-power-and-cooling-checklist-for-gpu-clusters/", "sku": "", "text": "Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training […] . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image" }, { "type": "knowledge-base", "title": "Sovereign AI GPU Cluster Planning for India", "url": "https://rdp.in/gpu-mart/knowledge-base/sovereign-ai-gpu-cluster-planning-for-india/", "sku": "", "text": "Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training […] . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image" }, { "type": "knowledge-base", "title": "RAG Storage and Retrieval Sizing for Enterprise Search", "url": "https://rdp.in/gpu-mart/knowledge-base/rag-storage-and-retrieval-sizing-for-enterprise-search/", "sku": "", "text": "Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training […] . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image" }, { "type": "knowledge-base", "title": "Media Rendering and Generative AI Workstation Planning", "url": "https://rdp.in/gpu-mart/knowledge-base/media-rendering-and-generative-ai-workstation-planning/", "sku": "", "text": "Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training […] . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image" }, { "type": "knowledge-base", "title": "BFSI AI Risk and GPU Infrastructure Planning", "url": "https://rdp.in/gpu-mart/knowledge-base/bfsi-ai-risk-and-gpu-infrastructure-planning/", "sku": "", "text": "Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training […] . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image" }, { "type": "knowledge-base", "title": "Healthcare AI Infrastructure Readiness in India", "url": "https://rdp.in/gpu-mart/knowledge-base/healthcare-ai-infrastructure-readiness-in-india/", "sku": "", "text": "Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training […] . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image" }, { "type": "knowledge-base", "title": "Fine-Tuning GPU Server Sizing for Enterprise LLMs", "url": "https://rdp.in/gpu-mart/knowledge-base/fine-tuning-gpu-server-sizing-for-enterprise-llms/", "sku": "", "text": "Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training […] . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image" }, { "type": "knowledge-base", "title": "AI Factory Storage Planning for GPU Clusters", "url": "https://rdp.in/gpu-mart/knowledge-base/ai-factory-storage-planning-for-gpu-clusters/", "sku": "", "text": "Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training […] . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image" }, { "type": "knowledge-base", "title": "Manufacturing Vision AI GPU Server Playbook", "url": "https://rdp.in/gpu-mart/knowledge-base/manufacturing-vision-ai-gpu-server-playbook/", "sku": "", "text": "Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training […] . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image" }, { "type": "knowledge-base", "title": "GPU Workstations vs Servers for AI Teams in India", "url": "https://rdp.in/gpu-mart/knowledge-base/gpu-workstations-vs-servers-for-ai-teams-in-india/", "sku": "", "text": "Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training […] . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image" }, { "type": "knowledge-base", "title": "Reference Architecture for RAG on H200 GPU Servers", "url": "https://rdp.in/gpu-mart/knowledge-base/reference-architecture-for-rag-on-h200-gpu-servers/", "sku": "", "text": "Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training […] . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image" }, { "type": "knowledge-base", "title": "Sizing 70B LLM Inference on GPU Servers in India", "url": "https://rdp.in/gpu-mart/knowledge-base/sizing-70b-llm-inference-on-gpu-servers-in-india/", "sku": "", "text": "Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training […] . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image" }, { "type": "knowledge-base", "title": "H100 vs H200 vs B200: Which GPU for Your Workload?", "url": "https://rdp.in/gpu-mart/knowledge-base/h100-vs-h200-vs-b200-which-gpu-for-your-workload/", "sku": "", "text": "Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training […] . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image" }, { "type": "knowledge-base", "title": "Neocloud vs On-Prem: When to Build Your Own GPU Cloud", "url": "https://rdp.in/gpu-mart/knowledge-base/neocloud-vs-on-prem-when-to-build-your-own-gpu-cloud/", "sku": "", "text": "Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training […] . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image" }, { "type": "knowledge-base", "title": "Storage Architecture for AI Training: Why the Bottleneck Isn’t the GPU", "url": "https://rdp.in/gpu-mart/knowledge-base/storage-architecture-for-ai-training-why-the-bottleneck-isn-t-the-gpu/", "sku": "", "text": "Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training […] . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image" }, { "type": "knowledge-base", "title": "Best On-Prem Setup for a Startup Training Small LLMs (<13B)", "url": "https://rdp.in/gpu-mart/knowledge-base/best-on-prem-setup-for-a-startup-training-small-llms-13b/", "sku": "", "text": "Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training […] . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image" }, { "type": "knowledge-base", "title": "GPU Workstation or GPU Server? A Decision Guide", "url": "https://rdp.in/gpu-mart/knowledge-base/gpu-workstation-or-gpu-server-a-decision-guide/", "sku": "", "text": "Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training […] . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image" }, { "type": "knowledge-base", "title": "Media & Entertainment: GPU for Rendering + Generative AI (India)", "url": "https://rdp.in/gpu-mart/knowledge-base/media-and-entertainment-gpu-for-rendering-generative-ai-india/", "sku": "", "text": "Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training […] . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image" }, { "type": "knowledge-base", "title": "Government & PSU AI: Data-Residency-First GPU Infrastructure (India)", "url": "https://rdp.in/gpu-mart/knowledge-base/government-and-psu-ai-data-residency-first-gpu-infrastructure-india/", "sku": "", "text": "Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training […] . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image" }, { "type": "knowledge-base", "title": "AI Infrastructure for Manufacturing: Vision + Predictive Maintenance (India)", "url": "https://rdp.in/gpu-mart/knowledge-base/ai-infrastructure-for-manufacturing-vision-predictive-maintenance-india/", "sku": "", "text": "Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training […] . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image" }, { "type": "knowledge-base", "title": "On-Prem AI for BFSI: Running Fraud & Risk Models In-House (India)", "url": "https://rdp.in/gpu-mart/knowledge-base/on-prem-ai-for-bfsi-running-fraud-and-risk-models-in-house-india/", "sku": "", "text": "Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training […] . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image" }, { "type": "knowledge-base", "title": "On-Prem GPU for Healthcare AI & Medical Imaging (India)", "url": "https://rdp.in/gpu-mart/knowledge-base/on-prem-gpu-for-healthcare-ai-and-medical-imaging-india/", "sku": "", "text": "Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training […] . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image" }, { "type": "knowledge-base", "title": "GPU Sizing for Agentic AI Workloads (2026)", "url": "https://rdp.in/gpu-mart/knowledge-base/gpu-sizing-for-agentic-ai-workloads-2026/", "sku": "", "text": "Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training […] . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image" }, { "type": "knowledge-base", "title": "FP8 / FP4 Explained: Precision, Throughput & Cost Trade-offs", "url": "https://rdp.in/gpu-mart/knowledge-base/fp8-fp4-explained-precision-throughput-and-cost-trade-offs/", "sku": "", "text": "Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training […] . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image" }, { "type": "knowledge-base", "title": "HBM3e & GPU Memory: Why It Decides Your Model Size", "url": "https://rdp.in/gpu-mart/knowledge-base/hbm3e-and-gpu-memory-why-it-decides-your-model-size/", "sku": "", "text": "Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training […] . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image" }, { "type": "knowledge-base", "title": "InfiniBand vs Spectrum-X vs Ethernet for AI Clusters", "url": "https://rdp.in/gpu-mart/knowledge-base/infiniband-vs-spectrum-x-vs-ethernet-for-ai-clusters/", "sku": "", "text": "Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training […] . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image" }, { "type": "knowledge-base", "title": "Reference Architecture: Sovereign AI Cluster (Scalable Unit)", "url": "https://rdp.in/gpu-mart/knowledge-base/reference-architecture-sovereign-ai-cluster-scalable-unit/", "sku": "", "text": "Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training […] . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image" }, { "type": "knowledge-base", "title": "Air-Cooled vs Liquid-Cooled GPU Racks: When to Switch", "url": "https://rdp.in/gpu-mart/knowledge-base/air-cooled-vs-liquid-cooled-gpu-racks-when-to-switch/", "sku": "", "text": "Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training […] . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image" }, { "type": "knowledge-base", "title": "Reference Architecture: 8× H200 On-Prem AI Training Node", "url": "https://rdp.in/gpu-mart/knowledge-base/reference-architecture-8-h200-on-prem-ai-training-node/", "sku": "", "text": "Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training […] . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image" }, { "type": "knowledge-base", "title": "How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)?", "url": "https://rdp.in/gpu-mart/knowledge-base/how-many-gpus-do-you-need-for-a-100-user-private-chatgpt-on-prem/", "sku": "", "text": "Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training […] . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image" }, { "type": "knowledge-base", "title": "Sizing GPU Compute for Computer Vision / Video Analytics", "url": "https://rdp.in/gpu-mart/knowledge-base/sizing-gpu-compute-for-computer-vision-video-analytics/", "sku": "", "text": "Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training […] . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image" }, { "type": "knowledge-base", "title": "Right-Sizing a GPU Server for Enterprise RAG", "url": "https://rdp.in/gpu-mart/knowledge-base/right-sizing-a-gpu-server-for-enterprise-rag/", "sku": "", "text": "Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training […] . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image" }, { "type": "knowledge-base", "title": "What Is an AI Factory? Rack-Scale AI Explained for Buyers", "url": "https://rdp.in/gpu-mart/knowledge-base/what-is-an-ai-factory-rack-scale-ai-explained-for-buyers/", "sku": "", "text": "Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training […] . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image" }, { "type": "knowledge-base", "title": "How Much VRAM Does a 70B / 405B LLM Need for Inference?", "url": "https://rdp.in/gpu-mart/knowledge-base/how-much-vram-does-a-70b-405b-llm-need-for-inference/", "sku": "", "text": "Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training […] . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image" }, { "type": "knowledge-base", "title": "AI Infrastructure Buying Guide for CIOs (2026)", "url": "https://rdp.in/gpu-mart/knowledge-base/ai-infrastructure-buying-guide-for-cios-2026/", "sku": "", "text": "Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training […] . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image" }, { "type": "knowledge-base", "title": "Sovereign AI in India: What It Takes to Build In-Country GPU Infrastructure", "url": "https://rdp.in/gpu-mart/knowledge-base/sovereign-ai-in-india-what-it-takes-to-build-in-country-gpu-infrastructure/", "sku": "", "text": "Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training […] . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image" }, { "type": "knowledge-base", "title": "On-Prem vs Cloud GPU: What’s the True TCO for AI Training in India?", "url": "https://rdp.in/gpu-mart/knowledge-base/on-prem-vs-cloud-gpu-what-s-the-true-tco-for-ai-training-in-india/", "sku": "", "text": "Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training […] . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image" }, { "type": "knowledge-base", "title": "How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem?", "url": "https://rdp.in/gpu-mart/knowledge-base/how-many-gpus-do-you-need-to-fine-tune-a-70b-llm-on-prem/", "sku": "", "text": "Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training […] . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image" }, { "type": "knowledge-base", "title": "GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory", "url": "https://rdp.in/gpu-mart/knowledge-base/gb300-nvl72-anatomy-of-a-120-kw-rack-scale-ai-factory/", "sku": "", "text": "Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training […] . Skip to main content How Can We Help? Search AI Architectures Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing Checklist for AI Inference Disaggregated Inference: Splitting Prefill and Decode in 2026 RAG / Retrieval Right-Sizing a GPU Server for Enterprise RAG Reference Architecture for RAG on H200 GPU Servers RAG Storage and Retrieval Sizing for Enterprise Search RAG GPU Server Reference Architecture for India Adaptive RAG in 2026: Routing Between Hybrid, Graph and Agentic Tiers Long Context vs RAG in 2026: Where Retrieval Still Wins Multimodal RAG: GPU Planning for Document, Image" }, { "type": "gpu-mart-page", "title": "PLP card — tri-modal demo (tpl-plp-card-trimodal-html)", "url": "https://rdp.in/gpu-mart/tpl-plp-card-trimodal-html/", "sku": "", "text": "Master card v1.5m — calm-premium, engine-bound (Phase-1, GR3) Spec line = values only (engine pa_*), use-case line, one model-fit chip. Ink + grey; red only on the CTA. Toggle the dotted overlay to audit every engine binding. Show engine sources (dotted overlay) Source key: WOO — engine, per SKU FIXED — design string INTERIM — […] . Master card v1.5m — calm-premium, engine-bound (Phase-1, GR3) Spec line = values only (engine pa_* ), use-case line, one model-fit chip. Ink + grey; red only on the CTA. Toggle the dotted overlay to audit every engine binding. Show engine sources (dotted overlay) Source key: WOO — engine, per SKU FIXED — design string INTERIM — Phase-2 binds Buy now Compare CARINA 1× RTX PRO 4500 Blackwell AI Workstation SKU: 620688 32 GB GDDR7 · Xeon W-2500 · 64 GB DDR5 ECC · 2 TB NVMe · 10 GbE Entry fine-tune & inference Fits 13B–34B ₹3,89,000 + GST · In stock · Ships in 4 weeks Add to cart Configure Compare QUASAR 2× RTX PRO 4500 Blackwell AI Workstation SKU: 321248 64 GB GDDR7 (2× 32 GB) · Xeon W-2500 · 128 GB DDR5 ECC · 4 TB NVMe · 10 GbE Performance fine-tune & multi-model inference Fits 13B–34B From ₹9,20,000 Configure to order Configure & build Request quote Compare QUASAR 2× RTX PRO 6000 Blackwell AI Workstation SKU: 132355 192 GB GDDR7 (2× 96 GB) · Xeon W-3500 · 256 GB DDR5 ECC · 8 TB NVMe · 10 GbE High-capacity fine-tune & FP16 inference Fits 70B+ Contact for Price Made to order Request a Quote Buy → ₹ + GST · Add to cart (solid red) Configure → From ₹ (engine min) · Configure & build (solid red) Quote → Contact for Price · Request a Quote (outline → rdp.in/contact)" }, { "type": "gpu-mart-page", "title": "RDP GPU Mart · TEMPLATE · PLP · v1.5m · HTML", "url": "https://rdp.in/gpu-mart/tpl-plp-v1-5m-html/", "sku": "", "text": "Home / AI Workstations AI Workstations Desk-side RTX-class AI workstations for developers, researchers and data scientists. RDP-ValidatedMake in IndiaINR-transparent + GSTPan-India onsite SLAGeM-available Reference architecture GPUs: L40S · H100 · H200 Form factor: 2U / 4U / 5U HGX Fabric: NVLink · 400G RoCE / IB Fits: 7B → 405B models Choosing a system?CompareSizing guideTalk […] . Home / AI Workstations AI Workstations Desk-side RTX-class AI workstations for developers, researchers and data scientists. RDP-Validated Make in India INR-transparent + GST Pan-India onsite SLA GeM-available Reference architecture GPUs: L40S · H100 · H200 Form factor: 2U / 4U / 5U HGX Fabric: NVLink · 400G RoCE / IB Fits: 7B → 405B models Choosing a system? Compare Sizing guide Talk to an architect Datasheet pack Browse · AI Workstations 9 desk-side AI Workstations Filters Filters Clear all Sovereign-ready only Use case Agentic AI, Computer Vision, Inference, Model Fine-tuning, NLP & Speech, RAG 79 Agentic AI, Computer Vision, Inference, NLP & Speech, RAG 5 Inference 2 HPC & AI 2 GPU model None 62 NVIDIA H200 SXM5 17 RTX PRO 6000 Blackwell Server Edition 9 NVIDIA L40S 6 GPU count 0 43 1 12 8 8 Model size it fits Frontier multi-rack 11 HPC + frontier AI 10 Thermal for dense GPU 9 GPU-to-GPU fabric 9 Cooling Air 60 Liquid 52 Budget band ₹50Cr+ 22 ₹50L-1Cr 20 Under ₹3L 16 ₹1Cr+ 11 Buy mode Buy now 5 Configure 2 Request a quote 2 Showing 1–9 of 9 systems Default sorting Sort by popularity Sort by average rating Sort by latest Sort by price: low to high Sort by price: high to low Request quote Compare CARINA 1× RTX PRO 4500 Blackwell AI Workstation SKU: 620688 32 GB GDDR7 · Xeon W-2500 · 64 GB DDR5 ECC · 2 TB NVMe · 10 GbE Entry fine-tune & inference Fits 13B–34B Contact for Price M" }, { "type": "gpu-mart-page", "title": "Knowledge Base", "url": "https://rdp.in/gpu-mart/knowledge-base/", "sku": "", "text": ". How Can We Help? Search AI Architectures On-Prem vs Cloud GPU: What's the True TCO for AI Training in India? Sovereign AI in India: What It Takes to Build In-Country GPU Infrastructure AI Infrastructure Buying Guide for CIOs (2026) HBM3e & GPU Memory: Why It Decides Your Model Size FP8 / FP4 Explained: Precision, Throughput & Cost Trade-offs Neocloud vs On-Prem: When to Build Your Own GPU Cloud Sovereign AI GPU Cluster Planning for India AI Factory Power and Cooling Checklist for GPU Clusters GPU Mart Technical Guide: gpu server india AI-Citation-Ready GPU Server FAQ for RDP GPU Mart DPDP-Ready AI Infrastructure Planning for GPU Mart Buyers GeM GPU Server Procurement Guide for Public Sector AI H200 vs H100 GPU Server Procurement in India GPU RDP Buyer Search Guide for Indian AI Teams Show Remaining Articles ( 6 ) Collapse Articles Fine-tuning How Many GPUs Do You Need to Fine-Tune a 70B LLM On-Prem? Best On-Prem Setup for a Startup Training Small LLMs (<13B) Fine-Tuning GPU Server Sizing for Enterprise LLMs GPU Cluster Networking for Training and Fine-Tuning Beyond SFT: Sizing DPO and RLVR Post-Training Infrastructure Fine-Tuning Mixture-of-Experts Models: Memory and Routing Realities Sizing the RL Fine-Tuning Loop: Rollouts, Verifiers and GPU Split Indian-Language Adaptation: Tokenizers, Data and GPU Planning Continual Pre-Training: When Fine-Tuning Is Not Enough Show Remaining Articles ( 1 ) Collapse Articles Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory How Much VRAM Does a 70B / 405B LLM Need for Inference? Sizing GPU Compute for Computer Vision / Video Analytics How Many GPUs Do You Need for a 100-User Private ChatGPT (On-Prem)? GPU Sizing for Agentic AI Workloads (2026) Sizing 70B LLM Inference on GPU Servers in India GPU Server India Sizing C" }, { "type": "gpu-mart-page", "title": "RDP GPU Mart · TEMPLATE · KB Category · v1.0 · HTML", "url": "https://rdp.in/gpu-mart/tpl-kb-category-v1-0-html/", "sku": "", "text": "Knowledge Base›AI Architectures›Inference Inference Serving, KV-cache and cost-per-token optimisation for production LLM inference — from a single GPU to a full NVL72 rack. 1 article Browse topics Industries ManufacturingHealthcareBFSIMedia & EntertainmentRetail & E-commerce Products & Installation CARINA WorkstationsQUASAR WorkstationsDRACO WorkstationsGPU ServersStorage AI Architectures TrainingFine-tuningInferenceRAG / Retrieval Reference Architecture27 Jun 2026 GB300 NVL72: Anatomy of a […] . Knowledge Base › AI Architectures › Inference Inference Serving, KV-cache and cost-per-token optimisation for production LLM inference — from a single GPU to a full NVL72 rack. 1 article Browse topics Industries Manufacturing Healthcare BFSI Media & Entertainment Retail & E-commerce Products & Installation CARINA Workstations QUASAR Workstations DRACO Workstations GPU Servers Storage AI Architectures Training Fine-tuning Inference RAG / Retrieval Reference Architecture 27 Jun 2026 GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory The GB300 NVL72 turns a rack into a single accelerator — silicon, the NVLink domain, liquid cooling, a 16-week deployment blueprint and inference economics. 6 min read Read → Sizing Guide Draft Cutting cost-per-token: KV-cache and disaggregated serving How NVIDIA Dynamo, prefill/decode disaggregation and FP4 GEMM lower the cost of production inference. Coming soon Coming soon How-to Draft Right-sizing inference: from one H200 to a full NVL72 Match model size, latency target and QPS to the smallest system that meets your SLA. Coming soon Coming soon Need inference sizing for your models? Request a Quote ◧ Data sources" }, { "type": "gpu-mart-page", "title": "RDP GPU Mart · TEMPLATE · KB Article · v1.0 · HTML", "url": "https://rdp.in/gpu-mart/tpl-kb-article-v1-0-html/", "sku": "", "text": "Knowledge Base›AI Architectures›Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory Reference ArchitectureUpdated 27 Jun 2026·6 min read Overview The NVIDIA GB300 NVL72 (Blackwell Ultra) marks the point where the rack, not the GPU, becomes the unit of compute. Seventy-two Blackwell Ultra GPUs and 36 Grace CPUs operate as a single NVLink domain delivering […] . Knowledge Base › AI Architectures › Inference GB300 NVL72: Anatomy of a 120 kW Rack-Scale AI Factory Reference Architecture Updated 27 Jun 2026 · 6 min read Overview The NVIDIA GB300 NVL72 (Blackwell Ultra) marks the point where the rack, not the GPU, becomes the unit of compute. Seventy-two Blackwell Ultra GPUs and 36 Grace CPUs operate as a single NVLink domain delivering 1.08 ExaFLOPS of dense FP4, 20 TB of unified HBM3e memory, and roughly 50x the AI-factory output of a Hopper-generation system. Figure 1 — GB300 NVL72: 72-GPU NVLink rack (replace with product image) What you will learn: the B300 silicon step-up, how 72 GPUs act as one NVLink domain, why 1,400 W/chip forces direct-to-chip liquid cooling, a 16-week deployment blueprint, and the inference economics. Key takeaways 72 Blackwell Ultra GPUs + 36 Grace CPUs act as one NVLink domain — 1.08 ExaFLOPS FP4, 20 TB unified HBM3e. 1,400 W per chip makes direct-to-chip liquid cooling mandatory; budget a 150–200 kW in-rack CDU. A rack draws ~120 kW and weighs ~1.36 t — plan 480 V power and floor loading before delivery. Deploy in ~16 weeks; expect up to 25× tokens/s vs Hopper and up to 35× lower cost per token. The silicon: Blackwell Ultra (B300) 15 PFLOPS FP4 dense compute — a 66.7% lift over B200 for MoE inference. 288 GB HBM3e per GPU at 8 TB/s. 1,460 W TDP — sustains boost clocks through heavy GEMM phases. Generational step-function Spec" }, { "type": "gpu-mart-page", "title": "RDP GPU Mart · TEMPLATE · KB Main · v1.0 · HTML", "url": "https://rdp.in/gpu-mart/tpl-kb-main-v1-0-html/", "sku": "", "text": "GPU Mart Knowledge Base How can we help? Reference architectures, install guides and industry playbooks for buying and deploying AI infrastructure — from a single workstation to a 120 kW rack. Search Reference ArchitecturesInstall GuidesIndustry PlaybooksSizing Guides Industries ManufacturingPredictive maintenance, vision QA and digital twins, on-prem.● 0 articlesHealthcareImaging and clinical models that keep PHI in-country.● 0 […] . GPU Mart Knowledge Base How can we help? Reference architectures, install guides and industry playbooks for buying and deploying AI infrastructure — from a single workstation to a 120 kW rack. Search Reference Architectures Install Guides Industry Playbooks Sizing Guides Industries Manufacturing Predictive maintenance, vision QA and digital twins, on-prem. ● 0 articles Healthcare Imaging and clinical models that keep PHI in-country. ● 0 articles BFSI Fraud, risk and credit models under RBI data-residency. ● 0 articles Media & Entertainment Rendering, VFX and generative content pipelines. ● 0 articles Retail & E-commerce Recommendations, search and demand forecasting. ● 0 articles Products & Installation CARINA Workstations Entry AI workstations — setup and sizing. ● 0 articles QUASAR Workstations Mid-range multi-GPU workstation guides. ● 0 articles DRACO Workstations Flagship tower workstation deployment. ● 0 articles GPU Servers Rack GPU server install, power and cooling. ● 1 article Storage AI storage tiers, throughput and capacity planning. ● 0 articles AI Architectures Training Cluster sizing for 7B–70B+ model training. ● 0 articles Fine-tuning LoRA / QLoRA and full fine-tune reference setups. ● 0 articles Inference Serving, KV-cache and cost-per-token optimisation. ● 1 article RAG / Retrieval Private RAG over enterprise data, e" }, { "type": "gpu-mart-page", "title": "Shop by Use Case", "url": "https://rdp.in/gpu-mart/use-cases/", "sku": "", "text": ". Shop by use case Shop by Use Case Find systems by what you are building — training, inference, RAG, computer vision, HPC and AI, and sovereign AI. Systems for AI inference Right-sized GPUs for high-throughput, low-latency serving. View systems → 89 Systems for generative AI Train and serve image, video and content models — NVLink, fast NVMe, liquid-ready. View systems → 89 Systems for agentic AI Build and run autonomous AI agents — from edge AI PCs to GPU servers. View systems → 88 Systems for NLP & speech GPU systems for language models, ASR/TTS and real-time translation. View systems → 87 Systems for RAG & retrieval Balanced GPU + fast-NVMe for retrieval-augmented generation. View systems → 86 Systems for computer vision GPU systems to train and deploy vision models. View systems → 84 Systems for model fine-tuning Right-sized multi-GPU systems to adapt 7B–70B models to your data. View systems → 81 Systems for LLM training Multi-GPU and rack-scale systems for 7B–trillion-parameter training. View systems → 61 Systems for HPC & AI Converged HPC + AI clusters with high-bandwidth fabric. View systems → 51 Systems for sovereign AI AI factories on sovereign Indian infrastructure — DPDP, GeM. View systems → 31 Not sure which fits your workload? Talk to our solution architects for multi-node fabric design, financing & GPU-as-a-Service — or configure a build and get an instant indicative price. Talk to an architect Configure a build" }, { "type": "gpu-mart-page", "title": "Solutions by Industry", "url": "https://rdp.in/gpu-mart/solutions/", "sku": "", "text": ". Solutions by industry Solutions by Industry AI infrastructure matched to your industry — neocloud, sovereign and public sector, BFSI and HFT, enterprise and GCCs, and research. Sovereign AI for the public sector Sovereign, India-built AI — DPDP, MeitY and GeM-ready. View systems → 137 AI infrastructure for neoclouds Fleet-scale GPU systems for GPU-as-a-Service and AI-first clouds. View systems → 110 HPC & AI for research and higher education Supercomputing and GPU clusters for labs and universities. View systems → 92 Enterprise AI, Make-in-India Pilot-to-production AI for enterprises and global capability centres. View systems → 91 AI for healthcare & life sciences GPU systems for medical imaging, genomics and drug discovery — secure and DPDP-ready. View systems → 63 AI for defence & aerospace Sovereign, India-built AI for ISR, simulation and mission compute — DPDP, GeM. View systems → 55 AI for automotive & mobility ADAS training, autonomous simulation and in-vehicle inference at scale. View systems → 54 AI for telecom & 5G Edge and core GPU systems for RAN optimization, real-time inference and network AI. View systems → 46 AI for media, gaming & entertainment GPU systems for rendering, VFX and generative content at studio scale. View systems → 46 Low-latency AI for BFSI & HFT Low-latency GPU systems for risk, fraud, quant and trading. View systems → 45 AI for retail & e-commerce Recommendation, demand forecasting and in-store vision — from edge to cloud. View systems → 45 AI for manufacturing & Industry 4.0 Vision QC, predictive maintenance and digital twins — from the factory edge to the datacenter. View systems → 45 Not sure which fits your workload? Talk to our solution architects for multi-node fabric d" }, { "type": "gpu-mart-page", "title": "Compare", "url": "https://rdp.in/gpu-mart/compare/", "sku": "", "text": ". Home / AI Workstations / Compare Compare AI Workstations 0 of 4 systems Not sure which rung? Talk to a solution architect — we size the system to your models, budget and timeline. Talk to an architect Configure a custom build Add a system AI Workstations · compare like-for-like ×" }, { "type": "gpu-mart-page", "title": "Configure & Build Your GPU System | GPU Mart", "url": "https://rdp.in/gpu-mart/build/", "sku": "", "text": "Home / GPU Servers / Configure & build Configure your GPU system Build a configure-to-order AI server — pick the platform, GPUs and options; price, model-fit and power update live. Indicative estimates update live; every configuration routes to a fast quote. 1 Platform Chassis & GPU density. Sets your GPU count. 2U · 2-GPUAir, single-node […] . Home / GPU Servers / Configure & build Configure your GPU system Build a configure-to-order AI server — pick the platform, GPUs and options; price, model-fit and power update live. Indicative estimates update live; every configuration routes to a fast quote. 1 Platform Chassis & GPU density. Sets your GPU count. 2U · 2-GPU Air, single-node dev/inference Base ₹5,90,000 4U · 4-GPU Air or liquid, team training Base ₹9,90,000 8U HGX · 8-GPU NVLink, liquid, cluster node Base ₹24,90,000 2 GPU Per-GPU accelerator. SXM needs a 4U/8U platform. NVIDIA L40S 48GB Inference & mixed AI ₹3,80,000 /GPU H100 PCIe 80GB Training & HPC ₹16,50,000 /GPU H100 SXM 80GB NVLink, max throughput ₹22,00,000 /GPU 3 CPU Host processors. 2× Xeon Silver Balanced Included 2× Xeon Gold Higher core/clock +₹3,20,000 2× EPYC 9004 Max cores/PCIe +₹4,10,000 4 System memory DDR5 ECC. 512 GB Included 1 TB +₹2,40,000 2 TB +₹6,80,000 5 Storage NVMe local. 2× 1.92 TB NVMe Included 4× 3.84 TB NVMe +₹3,10,000 8× 7.68 TB NVMe +₹8,90,000 6 Networking Cluster fabric. 2× 25 GbE Single node Included 2× 100 GbE CX-6 Multi-node +₹2,60,000 400G InfiniBand Scale-out cluster +₹6,20,000 7 Cooling Liquid is required for 8-GPU / H100 SXM. Air-cooled Included Direct liquid (DLC) CDU + cold plates +₹4,50,000 8 Support Warranty & SLA. 3-yr onsite Pan-India" }, { "type": "gpu-mart-page", "title": "AI Infrastructure Categories — GPU Mart by RDP", "url": "https://rdp.in/gpu-mart/categories/", "sku": "", "text": "GPU Mart · Categories Shop AI infrastructure by category Browse RDP GPU Mart’s 16 categories — from GPU servers and AI workstations to networking, storage, cooling, racks and full superclusters. Make in India, GST invoicing, pan-India enterprise support. . GPU Mart · Categories Shop AI infrastructure by category Browse RDP GPU Mart’s 16 categories — from GPU servers and AI workstations to networking, storage, cooling, racks and full superclusters. Make in India, GST invoicing, pan-India enterprise support. AI SuperClusters Turnkey AI superclusters — hundreds to thousands of GPUs delivered and validated as one system, from GB300 to NVL72. Request a quote Supercomputers Turnkey supercomputer-class systems — designed, delivered, installed and supported as one make-in-India build. Request a quote Rack-Scale AI Systems Integrated NVL72-class GPU racks (GB300) delivered as one validated unit — stand up rack-scale AI in days, not months. From ₹42 Cr HPC Clusters HPC cluster building blocks — validated nodes and interconnect for simulation, modelling and scientific research. Request a quote GPU Servers Production GPU servers — L40S, H100/H200 and HGX — for AI training and high-throughput inference, air- or liquid-cooled. From ₹5.92 Cr Multi-Node & Blade High-density multi-node and blade platforms — maximum compute per rack for AI and HPC. Request a quote Enterprise Rack & Tower Servers Dependable enterprise rack and tower servers for compute, storage and virtualisation workloads. Request a quote AI Workstations Desk-side RTX PRO Blackwell workstations for developers and researchers — CUDA-ready AI compute under your desk. From ₹9.2 L Agentic AI PCs & Edge AI Agentic AI PCs and Jetson-class edge systems for on-prem and field inference — rugg" }, { "type": "gpu-mart-page", "title": "GPU Mart Policies", "url": "https://rdp.in/gpu-mart/policies/", "sku": "", "text": "GPU Mart · Policies Policy & legal centre Effective 17 June 2026 · Version 1.0 Every term that governs buying AI infrastructure on GPU Mart — sale, privacy, warranty, shipping, GST and grievance redressal — in one place. 01Terms & ConditionsSite use, eligibility, IP & liability.02Terms of SaleOrders, pricing, delivery & cancellation.03Privacy PolicyHow we collect, […] . GPU Mart · Policies Policy & legal centre Effective 17 June 2026 · Version 1.0 Every term that governs buying AI infrastructure on GPU Mart — sale, privacy, warranty, shipping, GST and grievance redressal — in one place. 01 Terms & Conditions Site use, eligibility, IP & liability. 02 Terms of Sale Orders, pricing, delivery & cancellation. 03 Privacy Policy How we collect, use & protect your data. 04 Cookie Policy Cookies & tracking on the site. 05 Shipping & Delivery Pan-India dispatch, lead times & install. 06 Returns, Refunds & Cancellations Returns, RMA & refund terms. 07 Warranty & Support Hardware warranty, SLA & onsite support. 08 Build-to-Order / Custom Config Configured & made-to-order terms. 09 Product & Technical Disclaimer Specs, performance & accuracy. 10 Compliance & Certifications Standards, certifications & audits. 11 Payment, Billing & GST Payment methods, invoicing & GST. 12 Installation & Commissioning Onsite install & handover. 13 Export & International Orders Export control & cross-border. 14 Service Level & Turnaround Response & turnaround commitments. 15 Preorder, Backorder & Allocation Preorder, backorder & GPU allocation. 16 Contact, Support & Grievance Reach us & grievance redressal. 17 Trademark & Copyright IP, trademarks & copyright notice." }, { "type": "gpu-mart-page", "title": "Trademark & Copyright Notice", "url": "https://rdp.in/gpu-mart/trademark-copyright/", "sku": "", "text": "GPU Mart · Policies Effective date: 17 June 2026 · Last updated: 17 June 2026 · Version 1.0 Ownership of GPU Mart brand and content, third-party trademark acknowledgements, and acceptable-use terms. 1. Our trademarks “GPU Mart”, “RDP”, the RDP and GPU Mart logos, and related names and slogans are trademarks of RDP Technologies Limited / […] . GPU Mart · Policies Effective date: 17 June 2026 · Last updated: 17 June 2026 · Version 1.0 Ownership of GPU Mart brand and content, third-party trademark acknowledgements, and acceptable-use terms. 1. Our trademarks “GPU Mart”, “RDP”, the RDP and GPU Mart logos, and related names and slogans are trademarks of RDP Technologies Limited / RDP Computers India Private Limited unless otherwise stated, protected under the Trade Marks Act, 1999. They may not be used without our prior written permission. 2. Copyright All content on this Site — text, graphics, layouts, images, documentation, and downloadable materials — is owned by RDP or its licensors and protected under the Copyright Act, 1957. You may view and print content for legitimate procurement purposes only. 3. Third-party trademarks Product names and marks such as NVIDIA, Intel, AMD, Dell, Supermicro, Mellanox, InfiniBand, and RoCE are the property of their respective owners. References are for identification only and do not imply endorsement, sponsorship, or partnership unless expressly stated. 4. Acceptable use You agree not to copy, scrape, reverse engineer, or redistribute Site content; misuse configurators or RFQ tools; or use our marks or content in a misleading way. Further restrictions are in the Terms & Conditions . 5. User-submitted content If you submit RFQ docu" }, { "type": "gpu-mart-page", "title": "Contact, Support & Grievance Redressal", "url": "https://rdp.in/gpu-mart/contact-grievance/", "sku": "", "text": "GPU Mart · Policies Effective date: 17 June 2026 · Last updated: 17 June 2026 · Version 1.0 How to reach GPU Mart for sales and support, and how to raise and escalate a grievance, including Grievance Officer details and consumer helpline. 1. Contact us Seller (legal entity) RDP Computers India Private Limited Brand RDP […] . GPU Mart · Policies Effective date: 17 June 2026 · Last updated: 17 June 2026 · Version 1.0 How to reach GPU Mart for sales and support, and how to raise and escalate a grievance, including Grievance Officer details and consumer helpline. 1. Contact us Seller (legal entity) RDP Computers India Private Limited Brand RDP Technologies Limited — GPU Mart storefront Operating address Survey No. 56, Plot Nos. 43 to 54, Tech Park (MTP) Nacharam, TSIIC-IALA Nacharam, Hyderabad – 500 076, Telangana, India GSTIN / CIN 36AALCR2482F1Z7 / U72900TG2021PTC154515 (RDP Computers India Private Limited) Sales sales@rdp.in · +91 766 717 8999 Support support@rdp.in · +91 720 794 8743 Working hours Monday to Saturday, 10:00 AM to 7:00 PM IST 2. Raising a complaint If something goes wrong, contact support first with your order/invoice number and details. Most issues are resolved at this stage. We acknowledge complaints within 48 hours and aim to resolve them within one month (30 days). 3. Grievance Officer If your complaint is unresolved, escalate to our Grievance Officer (appointed under the Consumer Protection (E-Commerce) Rules, 2020 and the IT Act framework): Name / designation Omprakash, GPU Mart Operations Manager Email grievance@rdp.in Phone +91 720 794 8743 Address RDP, #403, Ashoka Capitol, Road No. 2, Banjara Hills (Opp. KBR Park), Hyderabad – 500 034, Telangana, India 4. Consumer r" }, { "type": "gpu-mart-page", "title": "Preorder, Backorder & Allocation Policy", "url": "https://rdp.in/gpu-mart/preorder-allocation/", "sku": "", "text": "GPU Mart · Policies Effective date: 17 June 2026 · Last updated: 17 June 2026 · Version 1.0 How GPU Mart handles preorders, backorders, and allocation of constrained GPUs and imported systems, including ETA uncertainty. 1. Why allocation applies Certain GPUs, accelerators, networking, and imported systems are supply-constrained. Orders for these may be fulfilled on […] . GPU Mart · Policies Effective date: 17 June 2026 · Last updated: 17 June 2026 · Version 1.0 How GPU Mart handles preorders, backorders, and allocation of constrained GPUs and imported systems, including ETA uncertainty. 1. Why allocation applies Certain GPUs, accelerators, networking, and imported systems are supply-constrained. Orders for these may be fulfilled on a preorder, backorder, or allocation basis with ETAs that can change. 2. Preorders and backorders A preorder/backorder reserves your place in the queue; it is not a guarantee of a specific delivery date. We share best-estimate ETAs and update them as supply information changes. 3. Allocation and prioritisation Where demand exceeds supply, available units are allocated at RDP’s reasonable discretion, considering order confirmation, payment status, and commitments. We may fulfil partially or offer equivalent approved alternatives. 4. Pricing For constrained or imported items, pricing may be subject to vendor and foreign-exchange variation until order acceptance or dispatch, as stated in the quotation (see Terms of Sale ). 5. Deposits, changes and cancellation Preorders may require a deposit of 25%. Once components are allocated or procured, orders may be non-cancellable; cancellation, if accepted, may incur charges (see Build-to-Order and Returns & Cancellations ). 6. Communication We keep" }, { "type": "gpu-mart-page", "title": "Service Level & Turnaround Policy", "url": "https://rdp.in/gpu-mart/service-level/", "sku": "", "text": "GPU Mart · Policies Effective date: 17 June 2026 · Last updated: 17 June 2026 · Version 1.0 Coverage windows, response and restore targets, escalation, and exclusions for GPU Mart support and AMC services where purchased. 1. Applicability This policy applies where you have purchased a support plan or AMC. Without a plan, support is […] . GPU Mart · Policies Effective date: 17 June 2026 · Last updated: 17 June 2026 · Version 1.0 Coverage windows, response and restore targets, escalation, and exclusions for GPU Mart support and AMC services where purchased. 1. Applicability This policy applies where you have purchased a support plan or AMC. Without a plan, support is limited to warranty defect handling under the Warranty & Support Policy . 2. Coverage windows Standard Business hours, Monday to Saturday, 10:00 AM to 7:00 PM IST Enhanced Extended-hours / next-business-day on-site, where purchased Mission-critical 24×7 with priority parts, where a mission-critical AMC is purchased 3. Response and restore targets Severity 1 (system down) Response 4 business hours; restore target best-effort by next business day, or per the applicable AMC Severity 2 (degraded) Response 8 business hours Severity 3 (general) Response 2 business days Targets are commercially reasonable objectives, not guarantees, and depend on access, diagnosis, and OEM/parts availability. Where RDP publishes a separate Support SLA document, that document governs the specifics. 4. Escalation matrix Unresolved issues escalate through L1 support → L2 engineering → Account Manager / OEM. Contact details are on the Contact & Grievance page. 5. Exclusions and dependencies SLA targets exclude issues caused by site conditions (power, cooling, network), cus" }, { "type": "gpu-mart-page", "title": "Export & International Orders Policy", "url": "https://rdp.in/gpu-mart/export-international/", "sku": "", "text": "GPU Mart · Policies Effective date: 17 June 2026 · Last updated: 17 June 2026 · Version 1.0 Terms for international buyers: Incoterms, duties and taxes, export controls, sanctions, FEMA, and delivery for cross-border GPU Mart orders. 1. International availability International orders are accepted at RDP’s discretion and confirmed at quotation. Serviceability, lead times, and […] . GPU Mart · Policies Effective date: 17 June 2026 · Last updated: 17 June 2026 · Version 1.0 Terms for international buyers: Incoterms, duties and taxes, export controls, sanctions, FEMA, and delivery for cross-border GPU Mart orders. 1. International availability International orders are accepted at RDP’s discretion and confirmed at quotation. Serviceability, lead times, and support coverage vary by destination. 2. Incoterms, duties and taxes Cross-border shipments are supplied on agreed Incoterms (default: Ex-Works (EXW), RDP facility, Hyderabad, unless otherwise agreed in the quotation). Unless stated, import duties, destination taxes, customs clearance, and local charges are the buyer’s responsibility. Title and risk transfer per the agreed Incoterms and the Shipping & Delivery Policy . 3. Export controls and sanctions AI hardware may be subject to export-control and sanctions regimes. Exports from India are governed by the Foreign Trade (Development and Regulation) Act, 1992, the Foreign Trade Policy and DGFT regulations, and SCOMET controls where applicable. You agree not to export, re-export, or divert products in violation of applicable laws, and confirm that you and the end-use/end-user are not subject to restrictions. We may require end-use/end-user documentation and may decline or cancel orders where controls or licen" }, { "type": "gpu-mart-page", "title": "Installation & Commissioning Policy", "url": "https://rdp.in/gpu-mart/installation-commissioning/", "sku": "", "text": "GPU Mart · Policies Effective date: 17 June 2026 · Last updated: 17 June 2026 · Version 1.0 What on-site installation and commissioning includes and excludes, your site prerequisites, and acceptance for GPU Mart deployments. 1. Scope of installation Installation and commissioning are provided only where purchased and described in the quotation or statement of […] . GPU Mart · Policies Effective date: 17 June 2026 · Last updated: 17 June 2026 · Version 1.0 What on-site installation and commissioning includes and excludes, your site prerequisites, and acceptance for GPU Mart deployments. 1. Scope of installation Installation and commissioning are provided only where purchased and described in the quotation or statement of work. Typical scope may include physical placement, rack mounting, cabling, power-on, firmware/driver setup, basic configuration, and functional verification. 2. Customer prerequisites (site readiness) You are responsible for site readiness before scheduled installation, including: adequate, stable power and circuits, UPS/PDU, and earthing; sufficient cooling and airflow for the rated load; network connectivity, IP plan, and rack space/access; safe access, lifting/handling support for heavy units, and any permits. Delays or revisits caused by site non-readiness may incur additional charges. 3. Exclusions Unless stated, installation excludes electrical/civil work, structured cabling beyond the rack, OS/application deployment, data migration, security hardening, and integration with third-party systems. These can be quoted separately. 4. Scheduling Installation is scheduled by mutual agreement after delivery and confirmation of site readiness. Lead times depend on resource availability and location. 5. Accep" }, { "type": "gpu-mart-page", "title": "Payment, Billing & GST Policy", "url": "https://rdp.in/gpu-mart/payment-billing-gst/", "sku": "", "text": "GPU Mart · Policies Effective date: 17 June 2026 · Last updated: 17 June 2026 · Version 1.0 Accepted payment methods, GST invoicing, tax treatment, purchase-order workflow, and international billing for GPU Mart. 1. Accepted payment methods We accept NEFT, RTGS and IMPS bank transfer, UPI, corporate credit/debit cards, and approved purchase orders. High-value orders […] . GPU Mart · Policies Effective date: 17 June 2026 · Last updated: 17 June 2026 · Version 1.0 Accepted payment methods, GST invoicing, tax treatment, purchase-order workflow, and international billing for GPU Mart. 1. Accepted payment methods We accept NEFT, RTGS and IMPS bank transfer, UPI, corporate credit/debit cards, and approved purchase orders. High-value orders are typically settled by bank transfer against a proforma invoice. 2. Purchase orders and credit For enterprise and government buyers we accept purchase orders subject to credit approval. A binding contract forms on RDP’s order acceptance (see Terms of Sale ). PO terms that conflict with our contract apply only if expressly accepted in writing. 3. GST and tax invoicing Prices exclude GST unless stated. Valid tax invoices are issued under the CGST/IGST Acts by the GST-registered seller RDP Computers India Private Limited (GSTIN 36AALCR2482F1Z7), with your GSTIN where provided, enabling input-tax credit. Provide accurate billing name, address, and GSTIN before invoicing; corrections after issue may be limited by law. The place of supply determines whether CGST+SGST or IGST applies. 4. Taxes, duties and price variation Applicable taxes, levies, and — for imports — customs duties are charged as per law. For configured or imported systems, pricing may be subject to vendor and for" }, { "type": "gpu-mart-page", "title": "Compliance & Certifications", "url": "https://rdp.in/gpu-mart/compliance-certifications/", "sku": "", "text": "GPU Mart · Policies Effective date: 17 June 2026 · Last updated: 17 June 2026 · Version 1.0 GPU Mart’s approach to quality, certifications, authorisations, country-of-origin, and data-centre readiness. Only documented certifications are claimed. 1. Our commitment RDP designs, supplies, and supports computing and AI infrastructure with an emphasis on reliability and trust. We claim […] . GPU Mart · Policies Effective date: 17 June 2026 · Last updated: 17 June 2026 · Version 1.0 GPU Mart’s approach to quality, certifications, authorisations, country-of-origin, and data-centre readiness. Only documented certifications are claimed. 1. Our commitment RDP designs, supplies, and supports computing and AI infrastructure with an emphasis on reliability and trust. We claim only certifications and authorisations we actually hold or can document; please request current certificates relevant to your procurement. 2. Certifications and standards Quality management ISO 9001 Quality Management OEM authorisations OEM / partner authorizations as applicable (available on request) Product / regulatory Product certifications (e.g. BIS / WPC) vary by SKU and configuration; available on request Make in India Make in India OEM; PLI 2.0 selected; MeitY recognised Certification scope varies by model and destination; confirm applicable certifications in the final quotation (see the certification disclaimer ). 3. Sector and procurement readiness We support enterprise and public-sector procurement requirements including documentation, GST invoicing, and, where applicable, availability on government channels (GeM). Sector-specific statements are provided only where valid for your order. 4. Security and data protection Our handling of person" }, { "type": "gpu-mart-page", "title": "Product & Technical Disclaimer", "url": "https://rdp.in/gpu-mart/product-disclaimer/", "sku": "", "text": "GPU Mart · Policies Effective date: 17 June 2026 · Last updated: 17 June 2026 · Version 1.0 Important notices on images, specifications, performance, availability, compatibility, certifications, and third-party trademarks for GPU Mart products. 1. Images are illustrative Product images, renders, rack scenes, and installed visuals are representative only. The delivered unit may vary by […] . GPU Mart · Policies Effective date: 17 June 2026 · Last updated: 17 June 2026 · Version 1.0 Important notices on images, specifications, performance, availability, compatibility, certifications, and third-party trademarks for GPU Mart products. 1. Images are illustrative Product images, renders, rack scenes, and installed visuals are representative only. The delivered unit may vary by configuration, region, or revision. Chassis finish, bezels, LEDs, rails, and cabling may differ from visuals. 2. Specifications subject to change Manufacturers may change components, firmware, ports, dimensions, or part numbers without notice. The binding specification is the one stated in your accepted quotation or contract. 3. Performance disclaimer Benchmarks, throughput, training/inference times, thermals, and efficiency depend on model, workload, software stack, drivers, optimisation, ambient conditions, and your environment. Any figures shown are indicative and not guaranteed. Performance variation within specification is not a defect. 4. Availability and substitution GPUs, networking, and storage SKUs may be substituted with an equivalent approved option where the quotation or contract permits, or with your consent. 5. Software and compatibility Framework, driver, CUDA, OS, virtualisation, and orchestration compatibility may require separate valida" }, { "type": "gpu-mart-page", "title": "Build-to-Order / Custom Configuration Policy", "url": "https://rdp.in/gpu-mart/build-to-order/", "sku": "", "text": "GPU Mart · Policies Effective date: 17 June 2026 · Last updated: 17 June 2026 · Version 1.0 How configured (CTO) AI systems are quoted, built, changed, cancelled, and delivered, including lead-time and component-availability dependencies. 1. What build-to-order means Build-to-order (CTO) systems — AI workstations, GPU servers, racks, and pods — are assembled to your […] . GPU Mart · Policies Effective date: 17 June 2026 · Last updated: 17 June 2026 · Version 1.0 How configured (CTO) AI systems are quoted, built, changed, cancelled, and delivered, including lead-time and component-availability dependencies. 1. What build-to-order means Build-to-order (CTO) systems — AI workstations, GPU servers, racks, and pods — are assembled to your specification. They are not stock items and carry different lead-time, change, cancellation, and return rules from off-the-shelf products. 2. Configuration sign-off The configuration in the accepted quotation is binding. Please verify GPU count, CPU, memory, storage, networking, power, cooling, chassis/rack units, OS, and software before sign-off. Changes after sign-off may affect price and lead time and require re-quotation. 3. Lead times and component availability CTO lead times are estimates dependent on component availability and vendor allocation. Constrained parts (certain GPUs, networking, storage) may extend timelines. Where a component becomes unavailable, we may, with your permission or as the contract allows, substitute an equivalent approved part (see the availability disclaimer ). 4. Changes, cancellation and returns Once components are allocated or procured, CTO orders may be non-cancellable and non-returnable except for defects. Cancellation, if accepted" }, { "type": "gpu-mart-page", "title": "Warranty & Support Policy", "url": "https://rdp.in/gpu-mart/warranty-support/", "sku": "", "text": "GPU Mart · Policies Effective date: 17 June 2026 · Last updated: 17 June 2026 · Version 1.0 Warranty coverage, OEM vs reseller scope, support, DOA/RMA handling, and exclusions for GPU Mart products. 1. Warranty coverage Products are covered by warranty for the period stated on the invoice/quotation or by the relevant OEM, whichever applies, […] . GPU Mart · Policies Effective date: 17 June 2026 · Last updated: 17 June 2026 · Version 1.0 Warranty coverage, OEM vs reseller scope, support, DOA/RMA handling, and exclusions for GPU Mart products. 1. Warranty coverage Products are covered by warranty for the period stated on the invoice/quotation or by the relevant OEM, whichever applies, against manufacturing defects under normal use. Duration and terms vary by SKU and manufacturer. This is in addition to your statutory rights under the Consumer Protection Act, 2019. 2. OEM vs reseller warranty Many enterprise products carry the OEM’s warranty (e.g. NVIDIA, Intel, AMD, Dell, Supermicro), serviced under OEM terms; others are covered by RDP as reseller. The applicable path (OEM or RDP) is identified at sale and on RMA. 3. Dead-on-arrival (DOA) Units found non-functional on arrival must be reported within 7 days of delivery, with serial number and fault details. Verified DOA units are repaired or replaced subject to availability and OEM DOA rules. 4. RMA process Contact support@rdp.in with invoice, serial number(s), and a fault description. We issue an RMA number with return/diagnostic instructions. After diagnosis, eligible units are repaired, replaced, or credited per warranty terms. 5. Support tiers and AMC Standard support covers warranty defect handling. Enhanced support and Annual Maintenance Contracts (AMC), with def" }, { "type": "gpu-mart-page", "title": "Returns, Refunds & Cancellations Policy", "url": "https://rdp.in/gpu-mart/refund-cancellation/", "sku": "", "text": "GPU Mart · Policies Effective date: 17 June 2026 · Last updated: 17 June 2026 · Version 1.0 Eligibility, timelines, exclusions, and the process for cancellations, returns, and refunds on GPU Mart, alongside your statutory rights. 1. Scope and your statutory rights This policy covers cancellations, returns, and refunds for purchases from GPU Mart. Because […] . GPU Mart · Policies Effective date: 17 June 2026 · Last updated: 17 June 2026 · Version 1.0 Eligibility, timelines, exclusions, and the process for cancellations, returns, and refunds on GPU Mart, alongside your statutory rights. 1. Scope and your statutory rights This policy covers cancellations, returns, and refunds for purchases from GPU Mart. Because we sell high-value, often configured or imported hardware, terms differ from ordinary retail. Nothing in this policy limits your statutory rights for defective, deficient, or mis-described goods and services under the Consumer Protection Act, 2019. Defective/DOA handling (clause 4) is separate from the voluntary return window (clause 3). 2. Order cancellation Stocked, un-dispatched orders may be cancelled within 24 hours of order acceptance. Once dispatched, an order cannot be cancelled and is handled as a return. Configured (CTO), special-order, preorder, and imported items may be non-cancellable once components are allocated or procured — see the Build-to-Order and Preorder & Allocation policies. 3. Voluntary return eligibility (non-defective) To be eligible for a voluntary return, items must be: reported within 7 days of delivery; unused, in original condition, with all accessories, seals, and packaging; accompanied by the invoice and a Return Authorisation (RMA) number. 4. Defective and DOA items Items tha" }, { "type": "gpu-mart-page", "title": "Shipping & Delivery Policy", "url": "https://rdp.in/gpu-mart/shipping-delivery/", "sku": "", "text": "GPU Mart · Policies Effective date: 17 June 2026 · Last updated: 17 June 2026 · Version 1.0 How GPU Mart ships hardware, expected timelines, freight and risk, inspection, and how delays are handled. 1. Service regions We ship across India and, where agreed, internationally (see the Export & International Orders Policy). Serviceability for certain […] . GPU Mart · Policies Effective date: 17 June 2026 · Last updated: 17 June 2026 · Version 1.0 How GPU Mart ships hardware, expected timelines, freight and risk, inspection, and how delays are handled. 1. Service regions We ship across India and, where agreed, internationally (see the Export & International Orders Policy ). Serviceability for certain regions, heavy racks, and project deliveries is confirmed at quotation. 2. Lead times and dispatch Timelines are estimates dependent on stock, configuration, and logistics. In-stock items typically dispatch within 3 to 7 business days; configured, imported, or project orders follow the quotation timeline. Build-to-order systems are governed by the Build-to-Order Policy . Expected delivery timelines are disclosed before order confirmation as required under the Consumer Protection (E-Commerce) Rules, 2020. 3. Freight, packaging and charges Freight, insurance, and special handling may be charged separately unless the quotation states otherwise. Enterprise hardware is packaged for safe transit; heavy/rack shipments may require suitable receiving facilities (dock, access, manpower) at your site. 4. Title and passing of risk Unless agreed otherwise, risk passes to you on delivery to the nominated address or carrier, and title passes on full payment (Sale of Goods Act, 1930). For ex-works or buyer-collected orders, risk passes on handove" }, { "type": "gpu-mart-page", "title": "Cookie Policy", "url": "https://rdp.in/gpu-mart/cookie-policy/", "sku": "", "text": "GPU Mart · Policies Effective date: 17 June 2026 · Last updated: 17 June 2026 · Version 1.0 How GPU Mart uses cookies and similar technologies, the categories and purposes, and how you control consent. 1. What cookies are Cookies are small files stored on your device that help the Site function, remember preferences, and […] . GPU Mart · Policies Effective date: 17 June 2026 · Last updated: 17 June 2026 · Version 1.0 How GPU Mart uses cookies and similar technologies, the categories and purposes, and how you control consent. 1. What cookies are Cookies are small files stored on your device that help the Site function, remember preferences, and measure usage. We also use similar technologies such as pixels and local storage. This policy supplements our Privacy Policy . 2. Categories we use Strictly necessary Core functions: security, session, cart/quote, load balancing. Always on. Preferences Remember settings such as region, language, and display choices. Analytics Understand usage and improve the Site, via Google Analytics (via Google Tag Manager). Aggregated where possible. Marketing With consent, measure campaigns and show relevant content, via Meta (Facebook / Instagram) and LinkedIn. 3. Third-party cookies Some cookies are set by third parties (analytics, embedded media, advertising). Their processing is governed by their own privacy and cookie policies. 4. Consent and control On your first visit, you can accept or reject non-essential cookies via the cookie consent banner on this site, and change your choice at any time there or through your browser settings. We obtain consent for non-essential cookies consistent with the DPDP Act, 2023. Blocking some cookies may affect Site functionality. 5. More information Questi" }, { "type": "gpu-mart-page", "title": "Terms & Conditions", "url": "https://rdp.in/gpu-mart/terms-conditions/", "sku": "", "text": "GPU Mart · Policies Effective date: 17 June 2026 · Last updated: 17 June 2026 · Version 1.0 These Terms & Conditions are a legally binding agreement governing your access to and use of the GPU Mart website. By using the Site you accept them. 1. Parties and acceptance These Terms & Conditions (“Terms”) govern […] . GPU Mart · Policies Effective date: 17 June 2026 · Last updated: 17 June 2026 · Version 1.0 These Terms & Conditions are a legally binding agreement governing your access to and use of the GPU Mart website. By using the Site you accept them. 1. Parties and acceptance These Terms & Conditions (“Terms”) govern your access to and use of the GPU Mart website at https://rdp.in/gpu-mart (“Site”). The Site is operated by RDP Computers India Private Limited (“RDP”, “we”, “us”), and is marketed under the RDP Technologies Limited brand. By accessing or using the Site you agree to these Terms, our Privacy Policy and Cookie Policy ; purchases are additionally governed by our Terms of Sale . If you do not agree, do not use the Site. 2. Eligibility, account and authority The Site is intended for business, institutional, and enterprise buyers. By transacting you confirm you are at least 18 years old, competent to contract under the Indian Contract Act, 1872, and authorised to bind the organisation you represent. You are responsible for the confidentiality of your account credentials and for all activity under your account. 3. Permitted and prohibited use You may use the Site only for lawful procurement and information purposes. You must not: scrape, harvest, crawl, or systematically extract data, pricing, or configurator output; reverse engineer, copy, fra" }, { "type": "gpu-mart-page", "title": "Terms of Sale", "url": "https://rdp.in/gpu-mart/terms-of-sale/", "sku": "", "text": "GPU Mart · Policies Effective date: 17 June 2026 · Last updated: 17 June 2026 · Version 1.0 These Terms of Sale form the contract for the purchase of products and services from GPU Mart, between you and the seller, RDP Computers India Private Limited. 1. The contract and its order of precedence These Terms […] . GPU Mart · Policies Effective date: 17 June 2026 · Last updated: 17 June 2026 · Version 1.0 These Terms of Sale form the contract for the purchase of products and services from GPU Mart, between you and the seller, RDP Computers India Private Limited. 1. The contract and its order of precedence These Terms of Sale apply to every sale of hardware, systems, and related services through GPU Mart by the seller, RDP Computers India Private Limited . They are read together with the Terms & Conditions , the applicable quotation, and any signed agreement, which form the contract under the Indian Contract Act, 1872 and the Sale of Goods Act, 1930. In case of conflict, a signed agreement prevails, then the quotation, then these Terms of Sale. Your standard purchase-order terms apply only if expressly accepted by us in writing. 2. Quotations and order acceptance A quotation is an invitation to offer, valid for 15 days unless stated otherwise. An order placed online or by purchase order is your offer to buy. A binding contract is formed only when RDP issues written order acceptance or a proforma/tax invoice confirming the order. We may decline an order before acceptance. 3. Prices, taxes and price variation Prices are in Indian Rupees (INR, ₹) and, unless stated, exclude GST, other taxes, freight, insurance, and installation. For configured or imported systems, pricing may be subject to vendor and foreign-exchange varia" }, { "type": "gpu-mart-page", "title": "RDP GPU Mart", "url": "https://rdp.in/gpu-mart/", "sku": "", "text": "Buy AI infrastructure, HPC & supercomputers — online. India’s datacenter-grade GPU storefront for CIOs, CTOs and neocloud builders. Configure a multi-crore AI factory, or buy a workstation today — Make in India, INR-transparent, sovereign-ready. Browse all systemsRequest a cluster quote 16 datacenter categories144 systems live₹10–100 cr buildsBuy · Configure · Quote 14years building in India […] . Buy AI infrastructure, HPC & supercomputers — online. India’s datacenter-grade GPU storefront for CIOs, CTOs and neocloud builders. Configure a multi-crore AI factory, or buy a workstation today — Make in India, INR-transparent, sovereign-ready. Browse all systems Request a cluster quote 16 datacenter categories 144 systems live ₹10–100 cr builds Buy · Configure · Quote 14 years building in India 300,000+ devices shipped 1M+ end users 28,000 sq ft Hyderabad facility ISO 9001 · PLI 2.0 · MeitY · BIS · Make in India · GeM Deployed across BFSI, government, research & enterprise — pan-India onsite support. CHOOSE YOUR TIER One platform, three tiers across every category — entry to rack-scale. CARINA ENTRY Desk-side AI workstations → QUASAR PERFORMANCE Multi-GPU training & inference → DRACO FLAGSHIP Rack-scale AI & superclusters → ONE SERIES SYSTEM ACROSS EVERY CATEGORY — CARINA → QUASAR → DRACO Browse the catalogue 16 categories. Datacenter-grade only. All systems → AI SuperClusters Turnkey AI superclusters — hundreds to thousands of GPUs delivered and validated as one system, from GB300 to NVL72. Request a quote Supercomputers Turnkey supercomputer-class systems — designed, delivered, installed and supported as one make-in-India build. Request a quote Rack-Scale AI Systems Integrated NVL72-class GPU racks (GB300) delivered a" }, { "type": "gpu-mart-page", "title": "My account", "url": "https://rdp.in/gpu-mart/my-account/", "sku": "", "text": "." }, { "type": "gpu-mart-page", "title": "Checkout", "url": "https://rdp.in/gpu-mart/checkout/", "sku": "", "text": "." }, { "type": "gpu-mart-page", "title": "Cart", "url": "https://rdp.in/gpu-mart/cart/", "sku": "", "text": "." }, { "type": "gpu-mart-page", "title": "All Systems", "url": "https://rdp.in/gpu-mart/all-systems/", "sku": "", "text": "." }, { "type": "gpu-mart-page", "title": "Privacy Policy", "url": "https://rdp.in/gpu-mart/privacy-policy/", "sku": "", "text": "GPU Mart · Policies Effective date: 17 June 2026 · Last updated: 17 June 2026 · Version 1.0 This Privacy Policy explains how RDP Computers India Private Limited collects, uses, shares, and protects personal data through GPU Mart, and your rights under Indian data-protection law. 1. Data fiduciary RDP Computers India Private Limited operates GPU […] . GPU Mart · Policies Effective date: 17 June 2026 · Last updated: 17 June 2026 · Version 1.0 This Privacy Policy explains how RDP Computers India Private Limited collects, uses, shares, and protects personal data through GPU Mart, and your rights under Indian data-protection law. 1. Data fiduciary RDP Computers India Private Limited operates GPU Mart and is the data fiduciary for personal data processed through the Site, within the meaning of the Digital Personal Data Protection Act, 2023 (DPDP Act). This policy also reflects our obligations under the Information Technology Act, 2000 and the IT (Reasonable Security Practices and Procedures and Sensitive Personal Data or Information) Rules, 2011 (SPDI Rules). Data-protection contact: privacy@rdp.in. 2. Personal data we collect Identity & contact: name, business email, phone, company, designation, billing/shipping address. Transaction: orders, quotations, invoices, GSTIN, and payment references (we do not store full card numbers). Technical & usage: IP address, device/browser data, and cookies (see the Cookie Policy ). Communications: enquiries, RFQ documents, and support interactions. 3. Purposes and lawful basis We process personal data to provide quotations and fulfil orders, manage accounts and support, process payments and issue GST invoices, comply with legal obligations, prevent fraud and secure the Site, and — with" }, { "type": "rdp-page", "title": "RDP Servers, PCs & AI Workstations India | Make in India OEM", "url": "https://www.rdp.in/", "sku": "", "text": "Buy RDP servers, desktops, laptops and AI workstations from India's Make-in-India IT hardware OEM. Explore enterprise systems, GeM procurement and quotes.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status S" }, { "type": "rdp-page", "title": "About RDP Technologies | India Make in India IT Hardware OEM", "url": "https://www.rdp.in/about", "sku": "", "text": "RDP Technologies Limited: 14+ years designing & manufacturing IT hardware in India. ISO 9001, MeitY recognised, PLI 2.0 selected. 300K+ devices deployed.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service" }, { "type": "rdp-page", "title": "AI Computing Solutions India", "url": "https://www.rdp.in/ai", "sku": "", "text": "AI-ready PCs, GPU workstations & AI starter servers from RDP India. NVIDIA validated, Intel & AMD. For GenAI, LLM training & vision AI. Get AI compute specs.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. 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Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status S" }, { "type": "rdp-page", "title": "RDP AR Series | AMD Ryzen AI Agentic AI Edge PCs", "url": "https://www.rdp.in/ai/a-series/ar-series", "sku": "", "text": "RDP AR Series — AMD Ryzen / Ryzen AI Agentic AI Edge PCs. AR-500, AR-700, AR-900 & the halo AR-950 Ryzen AI Max with 128GB unified memory for local LLM & ISV appliances.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. 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Download SLA Commitment Get Help Contact Support Support & Warranty Check Warrant" }, { "type": "rdp-page", "title": "RDP AU Series | Intel Core Ultra Agentic AI Edge PCs", "url": "https://www.rdp.in/ai/a-series/au-series", "sku": "", "text": "RDP AU Series — Intel Core Ultra Agentic AI Edge PCs. AU-500, AU-700, AU-900 for office AI, local RAG, branch AI & edge inference. Intel Arc + NPU.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. 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Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warra" }, { "type": "rdp-page", "title": "AR-700 | Enterprise AMD Ryzen AI Agentic AI PC", "url": "https://www.rdp.in/ai/a-series/products/ar-700", "sku": "", "text": "RDP AR-700 — Enterprise AMD Ryzen AI 7 Agentic AI Edge PC with integrated NPU, Radeon 880M, 32GB DDR5 (64GB option) & dual M.2 NVMe. For secure assistants, dev teams, branch AI & ISV appliances.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. 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Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support" }, { "type": "rdp-page", "title": "AR-900 | Flagship AMD Ryzen AI Edge PC", "url": "https://www.rdp.in/ai/a-series/products/ar-900", "sku": "", "text": "RDP AR-900 — Flagship AMD Ryzen AI 9 Agentic AI Edge PC with integrated NPU, Radeon 890M, 64GB DDR5 & dual M.2 NVMe. For local LLM workflows, edge inference & multi-agent desktops.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Ch" }, { "type": "rdp-page", "title": "AR-950 | Halo Ryzen AI Max Compact AI Workstation", "url": "https://www.rdp.in/ai/a-series/products/ar-950", "sku": "", "text": "RDP AR-950 — Halo compact AI workstation on AMD Ryzen AI Max+ 395 with Radeon 8060S & 128GB unified LPDDR5X. For high-memory local AI, multimodal demos & private model appliances.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. 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Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Che" }, { "type": "rdp-page", "title": "AU-500 | Mainstream Intel Core Ultra Agentic AI PC", "url": "https://www.rdp.in/ai/a-series/products/au-500", "sku": "", "text": "RDP AU-500 — Mainstream Intel Core Ultra 5 Agentic AI Edge PC with integrated NPU, 16GB DDR5 (32GB option), dual M.2 NVMe & dual 2.5GbE. For AI-ready offices, meeting rooms, AI labs & local assistants.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support" }, { "type": "rdp-page", "title": "AU-700 | Enterprise Intel Core Ultra Agentic AI PC", "url": "https://www.rdp.in/ai/a-series/products/au-700", "sku": "", "text": "RDP AU-700 — Enterprise Intel Core Ultra 7 Agentic AI Edge PC with integrated NPU, 32GB DDR5 (64GB option), dual M.2 NVMe, USB4 & dual 2.5GbE. For department copilots, local RAG & branch AI.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & W" }, { "type": "rdp-page", "title": "AU-900 | Premium Intel Core Ultra Agentic AI Edge PC", "url": "https://www.rdp.in/ai/a-series/products/au-900", "sku": "", "text": "RDP AU-900 — Premium Intel Core Ultra 9 Agentic AI Edge PC with integrated NPU, 64GB DDR5, dual M.2 NVMe & USB4. For multi-agent workflows, edge inference & secure local model PCs.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. 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SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Ch" }, { "type": "rdp-page", "title": "AI Edge PCs India | Compact Edge AI Computers for Inference – RDP", "url": "https://www.rdp.in/ai/ai-edge-pcs", "sku": "", "text": "AI edge PCs for real-time inference, computer vision & IoT edge computing. Compact, rugged, NVIDIA-powered. Make in India by RDP. Get specs & pricing.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service Ce" }, { "type": "rdp-page", "title": "AI-Ready PCs India | NVIDIA GPU Desktops for AI & ML – RDP", "url": "https://www.rdp.in/ai/ai-ready-pcs", "sku": "", "text": "AI-ready desktop PCs with NVIDIA GPUs for machine learning, AI inference & edge computing. Make in India. Dell & HP alternative. Get specs & pricing from RDP.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Se" }, { "type": "rdp-page", "title": "AI Starter Servers India | Entry-Level GPU Servers for AI – RDP", "url": "https://www.rdp.in/ai/ai-starter-servers", "sku": "", "text": "AI starter servers with NVIDIA GPUs for small-scale AI training, inference & deep learning. Affordable entry point to AI infrastructure. Make in India by RDP.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Se" }, { "type": "rdp-page", "title": "AI Edge PCs India | Compact Edge AI Computers for Inference – RDP", "url": "https://www.rdp.in/ai/edge-pcs/", "sku": "", "text": "AI edge PCs for real-time inference, computer vision & IoT edge computing. Compact, rugged, NVIDIA-powered. Make in India by RDP. Get specs & pricing.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service Ce" }, { "type": "rdp-page", "title": "Edge AI for Agriculture | Smart Farming Edge PCs by RDP", "url": "https://www.rdp.in/ai/edge-pcs/agriculture", "sku": "", "text": "RDP Edge PCs for agriculture: precision farming, livestock monitoring, irrigation control, crop disease detection. Made-in-India ruggedised edge AI.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service Cent" }, { "type": "rdp-page", "title": "AMD Ryzen Edge AI PCs | Compact Edge Inference by RDP", "url": "https://www.rdp.in/ai/edge-pcs/amd-edge", "sku": "", "text": "AMD Ryzen-powered Edge PCs from RDP for compact, energy-efficient edge inference workloads. Made-in-India ruggedised edge computing.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service Centers Resources Do" }, { "type": "rdp-page", "title": "Edge AI for Education | Classroom & Lab Edge PCs by RDP", "url": "https://www.rdp.in/ai/edge-pcs/education", "sku": "", "text": "RDP Edge PCs for schools, ITIs, and universities: AI labs, smart classrooms, proctoring, accessibility. Made-in-India ruggedised edge AI for education.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service C" }, { "type": "rdp-page", "title": "Hailo-Powered Edge AI PCs | Low-Power Vision by RDP", "url": "https://www.rdp.in/ai/edge-pcs/hailo", "sku": "", "text": "Hailo-8 / Hailo-15 powered Edge PCs from RDP for ultra-low-power AI vision at the edge. Made-in-India ruggedised inference appliances.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service Centers Resources" }, { "type": "rdp-page", "title": "Edge AI for Healthcare | Hospital & Clinical Edge PCs", "url": "https://www.rdp.in/ai/edge-pcs/healthcare", "sku": "", "text": "RDP Edge PCs for healthcare: medical imaging, telemedicine, patient monitoring, hospital workflows. Made-in-India ruggedised edge AI.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service Centers Resources D" }, { "type": "rdp-page", "title": "Intel-Powered Edge AI PCs | Core & Xeon-D Edge by RDP", "url": "https://www.rdp.in/ai/edge-pcs/intel-edge", "sku": "", "text": "Intel Core / Xeon-D powered Edge PCs from RDP for versatile edge inference and control workloads. Made-in-India ruggedised edge computing.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service Centers Resour" }, { "type": "rdp-page", "title": "Edge AI for Manufacturing | Factory Floor Edge PCs", "url": "https://www.rdp.in/ai/edge-pcs/manufacturing", "sku": "", "text": "RDP Edge PCs for manufacturing: machine vision QC, predictive maintenance, MES integration, robotics control. Made-in-India ruggedised edge AI.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service Centers R" }, { "type": "rdp-page", "title": "NVIDIA Jetson Edge AI PCs | Orin & Xavier Edge by RDP", "url": "https://www.rdp.in/ai/edge-pcs/nvidia-jetson", "sku": "", "text": "NVIDIA Jetson Orin / Xavier powered Edge PCs from RDP for high-performance edge AI inference. Made-in-India ruggedised inference appliances.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service Centers Reso" }, { "type": "rdp-page", "title": "Qualcomm Edge AI PCs | Snapdragon Edge by RDP", "url": "https://www.rdp.in/ai/edge-pcs/qualcomm", "sku": "", "text": "Qualcomm Snapdragon-powered Edge PCs from RDP for low-power, always-on edge AI at the network edge. Made-in-India ruggedised inference appliances.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service Center" }, { "type": "rdp-page", "title": "RDP Custom Edge AI PCs | Bespoke Ruggedised Edge Builds", "url": "https://www.rdp.in/ai/edge-pcs/rdp-custom", "sku": "", "text": "Custom Edge PC builds by RDP: bespoke form factors, I/O, certifications, and AI accelerators for unique deployment needs. Made-in-India.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service Centers Resource" }, { "type": "rdp-page", "title": "AI Edge PCs India | Compact Edge AI Computers for Inference – RDP", "url": "https://www.rdp.in/ai/edge-pcs/ref-arch/", "sku": "", "text": "AI edge PCs for real-time inference, computer vision & IoT edge computing. Compact, rugged, NVIDIA-powered. Make in India by RDP. Get specs & pricing.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service Ce" }, { "type": "rdp-page", "title": "Agricultural Monitoring", "url": "https://www.rdp.in/ai/edge-pcs/ref-arch/agricultural-monitoring", "sku": "", "text": "Reference architecture for agricultural monitoring at the edge: crop health, livestock, soil and irrigation. Built on RDP Edge PCs.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service Centers Resources Dow" }, { "type": "rdp-page", "title": "Campus Surveillance", "url": "https://www.rdp.in/ai/edge-pcs/ref-arch/campus-surveillance", "sku": "", "text": "Reference architecture for campus surveillance at the edge: ANPR, perimeter, intrusion detection, and centralised VMS. Built on RDP Edge PCs.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service Centers Res" }, { "type": "rdp-page", "title": "Factory Quality Inspection", "url": "https://www.rdp.in/ai/edge-pcs/ref-arch/factory-quality-inspection", "sku": "", "text": "Reference architecture for factory quality inspection at the edge: machine vision QC, defect detection, and MES. Built on RDP Edge PCs.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service Centers Resources" }, { "type": "rdp-page", "title": "Retail Chain Analytics", "url": "https://www.rdp.in/ai/edge-pcs/ref-arch/retail-chain-analytics", "sku": "", "text": "Per-store AI edge node architecture for footfall analytics, shelf compliance, queue management & loss prevention. Chain-wide dashboard scales 50–500+ stores.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Ser" }, { "type": "rdp-page", "title": "Smart City ITMS", "url": "https://www.rdp.in/ai/edge-pcs/ref-arch/smart-city-itms", "sku": "", "text": "Reference architecture for smart city Intelligent Traffic Management Systems at the edge: junction control, ANPR, incident detection.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service Centers Resources D" }, { "type": "rdp-page", "title": "University AI Lab", "url": "https://www.rdp.in/ai/edge-pcs/ref-arch/university-ai-lab", "sku": "", "text": "Reference architecture for university AI labs: training and inference clusters built on RDP GPU workstations and Edge PCs for hands-on AI learning.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service Cente" }, { "type": "rdp-page", "title": "Edge AI for Retail | Store, Kiosk & Shelf Edge PCs", "url": "https://www.rdp.in/ai/edge-pcs/retail", "sku": "", "text": "RDP Edge PCs for retail: smart checkout, shelf analytics, kiosks, footfall counting, loss prevention. Made-in-India ruggedised edge AI for stores.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service Center" }, { "type": "rdp-page", "title": "Edge AI for Robotics | AMR & Cobot Edge PCs by RDP", "url": "https://www.rdp.in/ai/edge-pcs/robotics", "sku": "", "text": "RDP Edge PCs for robotics: AMRs, cobots, drones, robotic arms. Real-time perception, SLAM, and motion control. Made-in-India ruggedised edge AI.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service Centers" }, { "type": "rdp-page", "title": "Edge AI for Smart City | Traffic, Safety & Civic Edge PCs", "url": "https://www.rdp.in/ai/edge-pcs/smart-city", "sku": "", "text": "RDP Edge PCs for smart city: ITMS, surveillance, ANPR, civic safety, environmental sensors. Made-in-India ruggedised edge AI for urban deployments.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service Cente" }, { "type": "rdp-page", "title": "Edge AI for Video Surveillance | NVR & VMS Edge PCs", "url": "https://www.rdp.in/ai/edge-pcs/video-surveillance", "sku": "", "text": "RDP Edge PCs for video surveillance: NVR, VMS, on-camera analytics, ANPR, intrusion detection. Made-in-India ruggedised edge AI for security.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service Centers Res" }, { "type": "rdp-page", "title": "GPU RDP Workstations India | NVIDIA RTX AI PCs", "url": "https://www.rdp.in/ai/gpu-workstations", "sku": "", "text": "Compare RDP GPU workstations for AI, deep learning and rendering in India. NVIDIA RTX options, Make-in-India build, enterprise support and quote guidance.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Servic" }, { "type": "rdp-page", "title": "RDP J Series | NVIDIA Jetson Edge AI Computers", "url": "https://www.rdp.in/ai/j-series/", "sku": "", "text": "RDP J Series — rugged, ready-to-deploy NVIDIA Jetson edge AI computers for robotics, autonomous machines, smart cities & industrial vision. 36 SKUs across 6 Jetson platforms.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Wa" }, { "type": "rdp-page", "title": "Jetson AGX Orin Edge AI Computers", "url": "https://www.rdp.in/ai/j-series/agx-orin", "sku": "", "text": "RDP J Series Jetson AGX Orin edge AI computers - 200 / 275 TOPS. Make in India, JetPack + Ubuntu pre-installed.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service Centers Resources Downloads & Drivers Kno" }, { "type": "rdp-page", "title": "Jetson AGX Xavier Edge AI Computers", "url": "https://www.rdp.in/ai/j-series/agx-xavier", "sku": "", "text": "RDP J Series Jetson AGX Xavier edge AI computers - 32 TOPS. Make in India, JetPack + Ubuntu pre-installed.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service Centers Resources Downloads & Drivers Knowledg" }, { "type": "rdp-page", "title": "Jetson Nano Edge AI Computers", "url": "https://www.rdp.in/ai/j-series/jetson-nano", "sku": "", "text": "RDP J Series Jetson Nano edge AI computers - 472 GFLOPS. Make in India, JetPack + Ubuntu pre-installed.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service Centers Resources Downloads & Drivers Knowledge B" }, { "type": "rdp-page", "title": "Jetson Orin Nano Edge AI Computers", "url": "https://www.rdp.in/ai/j-series/orin-nano", "sku": "", "text": "RDP J Series Jetson Orin Nano edge AI computers - 20 / 40 TOPS (Super Mode: 34 / 67 TOPS). Make in India, JetPack + Ubuntu pre-installed.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service Centers Resourc" }, { "type": "rdp-page", "title": "Jetson Orin NX Edge AI Computers", "url": "https://www.rdp.in/ai/j-series/orin-nx", "sku": "", "text": "RDP J Series Jetson Orin NX edge AI computers - 70 / 100 TOPS (Super Mode: 117 / 157 TOPS). Make in India, JetPack + Ubuntu pre-installed.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service Centers Resour" }, { "type": "rdp-page", "title": "RDP-J100 | Jetson Nano Edge Computer", "url": "https://www.rdp.in/ai/j-series/products/rdp-j100", "sku": "", "text": "NVIDIA Jetson Nano computer — 472 GFLOPS, Gigabit Ethernet with POE, lightweight aluminium alloy. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service Centers Resources Downloads & Drivers Knowledge Base / F" }, { "type": "rdp-page", "title": "RDP-J201 | Orin Nano Developer Kit", "url": "https://www.rdp.in/ai/j-series/products/rdp-j201", "sku": "", "text": "NVIDIA Jetson Orin Nano developer kit — 20/40 TOPS, official-kit compatible, 2× CSI camera connectors. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service Centers Resources Downloads & Drivers Knowledge Bas" }, { "type": "rdp-page", "title": "RDP-J201S | AI Edge Computer for Development", "url": "https://www.rdp.in/ai/j-series/products/rdp-j201s", "sku": "", "text": "NVIDIA Jetson Orin Nano developer-grade edge computer — 20/40 TOPS, 40-pin GPIO, wide-temperature. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service Centers Resources Downloads & Drivers Knowledge Base /" }, { "type": "rdp-page", "title": "RDP-J202 | Dual-LAN Surveillance Edge Computer", "url": "https://www.rdp.in/ai/j-series/products/rdp-j202", "sku": "", "text": "NVIDIA Jetson Orin Nano computer — 20/40 TOPS, 2× Gigabit Ethernet, for surveillance and safety. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service Centers Resources Downloads & Drivers Knowledge Base / FA" }, { "type": "rdp-page", "title": "RDP-J203 | Dual-LAN Smart-City Edge Computer", "url": "https://www.rdp.in/ai/j-series/products/rdp-j203", "sku": "", "text": "NVIDIA Jetson Orin Nano computer — 20/40 TOPS, 2× Gigabit Ethernet with POE, novel lightweight design. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service Centers Resources Downloads & Drivers Knowledge Bas" }, { "type": "rdp-page", "title": "RDP-J205 | Compact UAV & Edge Computer", "url": "https://www.rdp.in/ai/j-series/products/rdp-j205", "sku": "", "text": "NVIDIA Jetson Orin Nano compact computer — 20/40 TOPS, lightweight, for UAV data processing and robotics. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service Centers Resources Downloads & Drivers Knowledge" }, { "type": "rdp-page", "title": "RDP-J206 | 5-LAN Fanless Edge Computer", "url": "https://www.rdp.in/ai/j-series/products/rdp-j206", "sku": "", "text": "NVIDIA Jetson Orin Nano computer — 20/40 TOPS, 5× Gigabit Ethernet, passive cooling, Ubuntu 20.04. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service Centers Resources Downloads & Drivers Knowledge Base /" }, { "type": "rdp-page", "title": "RDP-J208P | Rugged Autonomous Vehicle Computer", "url": "https://www.rdp.in/ai/j-series/products/rdp-j208p", "sku": "", "text": "NVIDIA Jetson Orin Nano vehicle computer — 20/40 TOPS (up to 67 Super), 8× GMSL2, IP65, RTK, zero-power ACC. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service Centers Resources Downloads & Drivers Knowled" }, { "type": "rdp-page", "title": "RDP-J216 | 1U Rail-Transit Edge Server", "url": "https://www.rdp.in/ai/j-series/products/rdp-j216", "sku": "", "text": "NVIDIA Jetson Orin Nano 1U server — 20/40 TOPS, 5× M12 Gigabit, for rail foreign-object detection. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service Centers Resources Downloads & Drivers Knowledge Base /" }, { "type": "rdp-page", "title": "RDP-J218 | Wide-Temperature Value Edge Computer", "url": "https://www.rdp.in/ai/j-series/products/rdp-j218", "sku": "", "text": "NVIDIA Jetson Orin Nano compact computer — 20/40 TOPS (up to 67 Super), POE, −20°C to +70°C operation. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service Centers Resources Downloads & Drivers Knowledge Bas" }, { "type": "rdp-page", "title": "RDP-J50101 | Jetson Nano Developer Kit", "url": "https://www.rdp.in/ai/j-series/products/rdp-j50101", "sku": "", "text": "NVIDIA Jetson Nano developer kit — 472 GFLOPS, official-kit compatible, 2× CSI camera connectors. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service Centers Resources Downloads & Drivers Knowledge Base / F" }, { "type": "rdp-page", "title": "RDP-J50101S | Jetson Nano AI Edge Computer for Development", "url": "https://www.rdp.in/ai/j-series/products/rdp-j50101s", "sku": "", "text": "NVIDIA Jetson Nano developer-grade edge computer — 472 GFLOPS, 40-pin GPIO, HDMI + DP, passive cooling. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service Centers Resources Downloads & Drivers Knowledge Ba" }, { "type": "rdp-page", "title": "RDP-J50103 | Xavier NX Developer Kit (8GB)", "url": "https://www.rdp.in/ai/j-series/products/rdp-j50103", "sku": "", "text": "NVIDIA Jetson Xavier NX developer kit — 21 TOPS, official-kit compatible, 2× CSI connectors, 8GB. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service Centers Resources Downloads & Drivers Knowledge Base / F" }, { "type": "rdp-page", "title": "RDP-J50103S | Xavier NX AI Edge Computer for Development", "url": "https://www.rdp.in/ai/j-series/products/rdp-j50103s", "sku": "", "text": "NVIDIA Jetson Xavier NX developer-grade edge computer — 21 TOPS, 40-pin GPIO, HDMI + DP, passive cooling. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service Centers Resources Downloads & Drivers Knowledge" }, { "type": "rdp-page", "title": "RDP-J50104 | Xavier NX Developer Kit (16GB)", "url": "https://www.rdp.in/ai/j-series/products/rdp-j50104", "sku": "", "text": "NVIDIA Jetson Xavier NX developer kit — 21 TOPS, official-kit compatible, 2× CSI connectors, 16GB. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service Centers Resources Downloads & Drivers Knowledge Base /" }, { "type": "rdp-page", "title": "RDP-J503 | Dual-LAN Xavier NX Edge Computer", "url": "https://www.rdp.in/ai/j-series/products/rdp-j503", "sku": "", "text": "NVIDIA Jetson Xavier NX computer — 21 TOPS, 2× Gigabit Ethernet with POE, for smart-city deployment. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service Centers Resources Downloads & Drivers Knowledge Base" }, { "type": "rdp-page", "title": "RDP-J505 | Compact Xavier NX Edge Computer", "url": "https://www.rdp.in/ai/j-series/products/rdp-j505", "sku": "", "text": "NVIDIA Jetson Xavier NX compact computer — 21 TOPS, lightweight aluminium alloy, for drones and robotics. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service Centers Resources Downloads & Drivers Knowledge" }, { "type": "rdp-page", "title": "RDP-J506S | 5-LAN Fanless Edge Computer", "url": "https://www.rdp.in/ai/j-series/products/rdp-j506s", "sku": "", "text": "NVIDIA Jetson Xavier NX computer — 21 TOPS, 5× Gigabit Ethernet, passive cooling, Ubuntu 18.04. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service Centers Resources Downloads & Drivers Knowledge Base / FAQ" }, { "type": "rdp-page", "title": "RDP-J600 | Passively-Cooled AGX Xavier Edge Computer", "url": "https://www.rdp.in/ai/j-series/products/rdp-j600", "sku": "", "text": "NVIDIA Jetson AGX Xavier computer — 32 TOPS, fanless aluminium-alloy chassis, dual Gigabit Ethernet. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service Centers Resources Downloads & Drivers Knowledge Base" }, { "type": "rdp-page", "title": "RDP-J801 | Orin NX Developer Kit", "url": "https://www.rdp.in/ai/j-series/products/rdp-j801", "sku": "", "text": "NVIDIA Jetson Orin NX developer kit — 70/100 TOPS, official-kit compatible, 2× CSI camera connectors. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service Centers Resources Downloads & Drivers Knowledge Base" }, { "type": "rdp-page", "title": "RDP-J801S | AI Edge Computer for Development", "url": "https://www.rdp.in/ai/j-series/products/rdp-j801s", "sku": "", "text": "NVIDIA Jetson Orin NX developer-grade edge computer — 70/100 TOPS, 40-pin GPIO, wide-temperature, large storage. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service Centers Resources Downloads & Drivers Kno" }, { "type": "rdp-page", "title": "RDP-J802 | Dual-LAN Compact Edge Computer", "url": "https://www.rdp.in/ai/j-series/products/rdp-j802", "sku": "", "text": "NVIDIA Jetson Orin NX compact computer — 70/100 TOPS, 2× Gigabit Ethernet, industrial design. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service Centers Resources Downloads & Drivers Knowledge Base / FAQ S" }, { "type": "rdp-page", "title": "RDP-J805 | Compact Fanless Edge Computer", "url": "https://www.rdp.in/ai/j-series/products/rdp-j805", "sku": "", "text": "NVIDIA Jetson Orin NX compact computer — 70/100 TOPS, lightweight aluminium alloy, passive cooling. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service Centers Resources Downloads & Drivers Knowledge Base /" }, { "type": "rdp-page", "title": "RDP-J806 | 5-LAN Fanless Edge Computer", "url": "https://www.rdp.in/ai/j-series/products/rdp-j806", "sku": "", "text": "NVIDIA Jetson Orin NX computer — 70/100 TOPS, 5× Gigabit Ethernet, passive cooling, Ubuntu 20.04 pre-installed. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service Centers Resources Downloads & Drivers Know" }, { "type": "rdp-page", "title": "RDP-J808P | Rugged Autonomous Vehicle Computer", "url": "https://www.rdp.in/ai/j-series/products/rdp-j808p", "sku": "", "text": "NVIDIA Jetson Orin NX vehicle computer — 70/100 TOPS (up to 157 Super), 8× GMSL2, IP65, RTK, zero-power ACC. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service Centers Resources Downloads & Drivers Knowled" }, { "type": "rdp-page", "title": "RDP-J816 | 1U Rail-Transit Edge AI Server", "url": "https://www.rdp.in/ai/j-series/products/rdp-j816", "sku": "", "text": "NVIDIA Jetson Orin NX 1U server — 70/100 TOPS, 5× M12 Gigabit, designed for rail track foreign-object detection. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service Centers Resources Downloads & Drivers Kno" }, { "type": "rdp-page", "title": "RDP-J818 | Wide-Temperature Compact Edge Computer", "url": "https://www.rdp.in/ai/j-series/products/rdp-j818", "sku": "", "text": "NVIDIA Jetson Orin NX compact computer — 70/100 TOPS (up to 157 Super), POE, −20°C to +70°C operation. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service Centers Resources Downloads & Drivers Knowledge Bas" }, { "type": "rdp-page", "title": "RDP-J902 | Compact Vehicle Edge Computer", "url": "https://www.rdp.in/ai/j-series/products/rdp-j902", "sku": "", "text": "NVIDIA Jetson AGX Orin compact computer — up to 275 TOPS, actively cooled, for space-constrained installations. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service Centers Resources Downloads & Drivers Know" }, { "type": "rdp-page", "title": "RDP-J906 | Vehicle-Mounted Low-Speed Autonomy", "url": "https://www.rdp.in/ai/j-series/products/rdp-j906", "sku": "", "text": "NVIDIA Jetson AGX Orin vehicle computer — up to 275 TOPS for unmanned delivery, sanitation, and intelligent commercial vehicles. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service Centers Resources Downloa" }, { "type": "rdp-page", "title": "RDP-J919 | 1U Rack-Mount Edge AI Server", "url": "https://www.rdp.in/ai/j-series/products/rdp-j919", "sku": "", "text": "NVIDIA Jetson AGX Orin 1U edge server — up to 275 TOPS, cabinet-integrable, with mass storage and 10GbE. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service Centers Resources Downloads & Drivers Knowledge B" }, { "type": "rdp-page", "title": "RDP-J930 | Autonomous Driving & Industrial Vision Flagship", "url": "https://www.rdp.in/ai/j-series/products/rdp-j930", "sku": "", "text": "NVIDIA Jetson AGX Orin Edge AI Computer — up to 275 TOPS, 8× GMSL2 cameras, 10 Gigabit Ethernet, RTK positioning & IP65 rugged design. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service Centers Resources D" }, { "type": "rdp-page", "title": "RDP-JB01 | Jetson Nano B01-T Developer Kit", "url": "https://www.rdp.in/ai/j-series/products/rdp-jb01", "sku": "", "text": "NVIDIA Jetson Nano 4GB developer kit — 472 GFLOPS, official carrier-board layout, 2× CSI connectors. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service Centers Resources Downloads & Drivers Knowledge Base" }, { "type": "rdp-page", "title": "Jetson Xavier NX Edge AI Computers", "url": "https://www.rdp.in/ai/j-series/xavier-nx", "sku": "", "text": "RDP J Series Jetson Xavier NX edge AI computers - 21 TOPS. Make in India, JetPack + Ubuntu pre-installed.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service Centers Resources Downloads & Drivers Knowledge" }, { "type": "rdp-page", "title": "AI VIDYA | AI-Ready Computer Labs for Schools", "url": "https://www.rdp.in/ai/vidya", "sku": "", "text": "AI VIDYA by RDP helps schools and colleges build AI-ready computer labs with AI PCs, GPU workstations, STEM learning support and NEP 2020 alignment.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service Cent" }, { "type": "rdp-page", "title": "About AI VIDYA Program", "url": "https://www.rdp.in/ai/vidya/about", "sku": "", "text": "AI VIDYA by RDP Technologies: India AI education initiative equipping schools, colleges, and skill centers with AI-ready labs. Learn about our mission and impact.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Statu" }, { "type": "rdp-page", "title": "AI VIDYA Certification | AI Skills Certification – RDP India", "url": "https://www.rdp.in/ai/vidya/certification", "sku": "", "text": "AI VIDYA certification program: Industry-recognized AI skills certification for students. Hands-on GPU workstation training, project portfolio. Enroll via RDP.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status S" }, { "type": "rdp-page", "title": "AI VIDYA Curriculum | AI Education Syllabus – RDP India", "url": "https://www.rdp.in/ai/vidya/curriculum", "sku": "", "text": "AI VIDYA curriculum: NEP 2020 aligned AI syllabus for schools and colleges. ML, deep learning, computer vision modules with hands-on GPU training. Download curriculum.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty" }, { "type": "rdp-page", "title": "AI VIDYA for Colleges | University AI Labs – RDP India", "url": "https://www.rdp.in/ai/vidya/higher-education", "sku": "", "text": "AI VIDYA university labs: GPU clusters, AI workstations for B.Tech, M.Tech, PhD research. NVIDIA powered, NEP 2020. Request college AI lab quote from RDP.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Servic" }, { "type": "rdp-page", "title": "AI VIDYA for Schools | AI-Ready Computer Labs – RDP India", "url": "https://www.rdp.in/ai/vidya/schools", "sku": "", "text": "AI VIDYA school labs by RDP: GPU workstations, AI PCs, and NEP 2020 curriculum for K-12 AI education. Make in India, affordable lab setup. Request school lab quote.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Sta" }, { "type": "rdp-page", "title": "AI VIDYA for ITI & Skill Centers | AI Training Labs – RDP", "url": "https://www.rdp.in/ai/vidya/skills-iti", "sku": "", "text": "AI VIDYA skill development labs for ITIs and training centers. Hands-on AI hardware for vocational training. Make in India, affordable. Get ITI lab specs from RDP.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Stat" }, { "type": "rdp-page", "title": "Contact RDP India | Server, PC & AI Workstation Quotes", "url": "https://www.rdp.in/contact", "sku": "", "text": "Contact RDP India for server, PC, thin client and AI workstation quotes. Reach the Hyderabad team for enterprise procurement and deployment support.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service Cent" }, { "type": "rdp-page", "title": "Corporate IT Hardware India", "url": "https://www.rdp.in/corporate", "sku": "", "text": "Enterprise desktops, laptops, workstations & servers from RDP. Make in India, ISO 9001, SLA support. HP & Dell alternative for Indian corporates. Request a quote.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Statu" }, { "type": "rdp-page", "title": "All-in-One PCs India", "url": "https://www.rdp.in/corporate/aio", "sku": "", "text": "RDP All-in-One PCs for front desks, reception & labs. Make in India AIO with Intel. HP ProOne & Dell OptiPlex AIO alternative. Compact, reliable. Get quote.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Serv" }, { "type": "rdp-page", "title": "Desktop PCs India", "url": "https://www.rdp.in/corporate/desktops", "sku": "", "text": "Buy Make in India desktop PCs from RDP. Intel & AMD, ISO 9001. HP ProDesk & Dell OptiPlex alternative. 50+ SKUs for office, govt & education. Get specs.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service" }, { "type": "rdp-page", "title": "Corporate Mini PCs | Ultra-Compact Desktops | 18 SKUs | Make in India", "url": "https://www.rdp.in/corporate/edge-pc", "sku": "", "text": "Buy ultra-compact mini PCs for corporate space-saving deployments from RDP – 18 SKUs across Essential, Business & Performance series. Intel & AMD with VESA mount, dual display, and monitor bundles. Fanless options for signage, kiosks & clean-desk setups with volume pricing and 3-year warranty.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitme" }, { "type": "rdp-page", "title": "RDP Laptops India | Business & Education Laptop PCs", "url": "https://www.rdp.in/corporate/laptops", "sku": "", "text": "Compare RDP laptops for Indian business, education and institutional deployments. Make-in-India systems, enterprise support and quote guidance.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service Centers R" }, { "type": "rdp-page", "title": "Rack & Tower Servers India", "url": "https://www.rdp.in/corporate/servers", "sku": "", "text": "RDP rack & tower servers with Intel Xeon. HPE ProLiant & Dell PowerEdge alternative. Make in India servers for enterprise & government. Get server specs.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service" }, { "type": "rdp-page", "title": "Rugged Tablets India", "url": "https://www.rdp.in/corporate/tablets", "sku": "", "text": "RDP tablets for education, field & enterprise. Android & Windows. Durable Make in India tablets. Bulk orders for schools & government. Buy online.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service Center" }, { "type": "rdp-page", "title": "RDP Thin Clients India | VDI & Secure Endpoint Devices", "url": "https://www.rdp.in/corporate/thin-clients", "sku": "", "text": "Evaluate RDP thin clients for VDI, remote desktop and secure endpoint deployments in India. Make-in-India devices, low-power options and enterprise quote support.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Statu" }, { "type": "rdp-page", "title": "GPU Workstations India", "url": "https://www.rdp.in/corporate/workstations", "sku": "", "text": "Compare RDP GPU workstation PCs for CAD, rendering, engineering and AI workloads in India. NVIDIA RTX options, Make-in-India build and quote support.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service Cen" }, { "type": "rdp-page", "title": "RDP Customers & Deployments | 300K+ Devices Across India", "url": "https://www.rdp.in/customers", "sku": "", "text": "RDP Technologies customer success stories: 300,000+ devices deployed across government, corporate, education, and AI projects in India. See our deployments.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Serv" }, { "type": "rdp-page", "title": "Data Centre Solutions India | Servers, Storage & HCI – RDP", "url": "https://www.rdp.in/dc", "sku": "", "text": "Complete data centre solutions from RDP – rack servers, tower servers, storage, HCI & networking. Make in India. Supermicro & HPE alternative. Get a quote.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Servi" }, { "type": "rdp-page", "title": "AI for Agriculture India", "url": "https://www.rdp.in/dc/ai-agriculture", "sku": "", "text": "RDP AI infrastructure for agriculture: GPU servers for crop analytics, precision farming AI, and agricultural research computing. Make in India. Get agri AI specs.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Stat" }, { "type": "rdp-page", "title": "RDP India | Agri Supply Chain Market", "url": "https://www.rdp.in/dc/ai-agriculture/agri-supply-chain-market", "sku": "", "text": "RDP Technologies - Make in India IT hardware OEM. AI computing, desktops, servers, and enterprise solutions. ISO 9001, GeM listed. Contact us for details.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Servic" }, { "type": "rdp-page", "title": "RDP India | Climate Water Resource", "url": "https://www.rdp.in/dc/ai-agriculture/climate-water-resource", "sku": "", "text": "RDP Technologies - Make in India IT hardware OEM. AI computing, desktops, servers, and enterprise solutions. ISO 9001, GeM listed. Contact us for details.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Servic" }, { "type": "rdp-page", "title": "RDP India | Precision Farming Crop", "url": "https://www.rdp.in/dc/ai-agriculture/precision-farming-crop", "sku": "", "text": "RDP Technologies - Make in India IT hardware OEM. AI computing, desktops, servers, and enterprise solutions. ISO 9001, GeM listed. Contact us for details.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Servic" }, { "type": "rdp-page", "title": "AI for BFSI India", "url": "https://www.rdp.in/dc/ai-bfsi", "sku": "", "text": "RDP AI infrastructure for banks & financial services. GPU compute for fraud detection, risk analytics & algorithmic trading. Make in India. Contact us.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service C" }, { "type": "rdp-page", "title": "RDP India | Customer Intelligence", "url": "https://www.rdp.in/dc/ai-bfsi/customer-intelligence", "sku": "", "text": "RDP Technologies - Make in India IT hardware OEM. AI computing, desktops, servers, and enterprise solutions. ISO 9001, GeM listed. Contact us for details.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Servic" }, { "type": "rdp-page", "title": "RDP India | Fraud Detection Risk", "url": "https://www.rdp.in/dc/ai-bfsi/fraud-detection-risk", "sku": "", "text": "RDP Technologies - Make in India IT hardware OEM. AI computing, desktops, servers, and enterprise solutions. ISO 9001, GeM listed. Contact us for details.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Servic" }, { "type": "rdp-page", "title": "RDP India | Regulatory Compliance", "url": "https://www.rdp.in/dc/ai-bfsi/regulatory-compliance", "sku": "", "text": "RDP Technologies - Make in India IT hardware OEM. AI computing, desktops, servers, and enterprise solutions. ISO 9001, GeM listed. Contact us for details.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Servic" }, { "type": "rdp-page", "title": "AI for Defence India", "url": "https://www.rdp.in/dc/ai-defence", "sku": "", "text": "RDP AI infrastructure for Indian defence. GPU servers, edge AI & secure computing for military applications. Make in India, sovereign AI. Talk to experts.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Servic" }, { "type": "rdp-page", "title": "RDP India | Command Control", "url": "https://www.rdp.in/dc/ai-defence/command-control", "sku": "", "text": "RDP Technologies - Make in India IT hardware OEM. AI computing, desktops, servers, and enterprise solutions. ISO 9001, GeM listed. Contact us for details.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Servic" }, { "type": "rdp-page", "title": "RDP India | Cyber Defence Ew", "url": "https://www.rdp.in/dc/ai-defence/cyber-defence-ew", "sku": "", "text": "RDP Technologies - Make in India IT hardware OEM. AI computing, desktops, servers, and enterprise solutions. ISO 9001, GeM listed. Contact us for details.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Servic" }, { "type": "rdp-page", "title": "RDP India | Isr Surveillance", "url": "https://www.rdp.in/dc/ai-defence/isr-surveillance", "sku": "", "text": "RDP Technologies - Make in India IT hardware OEM. AI computing, desktops, servers, and enterprise solutions. ISO 9001, GeM listed. Contact us for details.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Servic" }, { "type": "rdp-page", "title": "AI for Governance India", "url": "https://www.rdp.in/dc/ai-governance", "sku": "", "text": "RDP AI infrastructure for e-governance & smart cities. GPU compute for citizen services, traffic AI & surveillance. Make in India sovereign AI. Contact us.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Servi" }, { "type": "rdp-page", "title": "RDP India | Digital Government Citizen", "url": "https://www.rdp.in/dc/ai-governance/digital-government-citizen", "sku": "", "text": "RDP Technologies - Make in India IT hardware OEM. AI computing, desktops, servers, and enterprise solutions. ISO 9001, GeM listed. Contact us for details.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Servic" }, { "type": "rdp-page", "title": "Law Enforcement AI India", "url": "https://www.rdp.in/dc/ai-governance/law-enforcement-justice", "sku": "", "text": "RDP AI infrastructure for law enforcement: facial recognition, crime analytics, court case AI, prison management computing. Sovereign Make in India. Contact us.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status" }, { "type": "rdp-page", "title": "Smart City Urban AI", "url": "https://www.rdp.in/dc/ai-governance/smart-city-urban", "sku": "", "text": "RDP AI infrastructure for smart city urban management: traffic, surveillance, waste management, utilities AI. Make in India sovereign computing. Talk to experts.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status" }, { "type": "rdp-page", "title": "AI for Healthcare India", "url": "https://www.rdp.in/dc/ai-health", "sku": "", "text": "RDP AI infrastructure for hospitals & medical imaging. GPU servers for radiology AI, pathology & clinical decision support. Made in India. Get a quote.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Service C" }, { "type": "rdp-page", "title": "RDP India | Drug Discovery Genomics", "url": "https://www.rdp.in/dc/ai-health/drug-discovery-genomics", "sku": "", "text": "RDP Technologies - Make in India IT hardware OEM. AI computing, desktops, servers, and enterprise solutions. ISO 9001, GeM listed. Contact us for details.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Servic" }, { "type": "rdp-page", "title": "RDP India | Hospital Operations", "url": "https://www.rdp.in/dc/ai-health/hospital-operations", "sku": "", "text": "RDP Technologies - Make in India IT hardware OEM. AI computing, desktops, servers, and enterprise solutions. ISO 9001, GeM listed. Contact us for details.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Servic" }, { "type": "rdp-page", "title": "RDP India | Medical Imaging Diagnostics", "url": "https://www.rdp.in/dc/ai-health/medical-imaging-diagnostics", "sku": "", "text": "RDP Technologies - Make in India IT hardware OEM. AI computing, desktops, servers, and enterprise solutions. ISO 9001, GeM listed. Contact us for details.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Servic" }, { "type": "rdp-page", "title": "AI Infrastructure | GPU Servers, NVMe Storage, AI-POD & Lossless Fabric", "url": "https://www.rdp.in/dc/ai-infrastructure", "sku": "", "text": "RDP AI Infrastructure – 22 fixed reference configs across AI-GPU compute, NVMe storage, lossless fabric & ops packs. AI-POD rack solutions for inference, vision AI & training. NVIDIA H100/H200, Make in India OEM with BOQ support.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitme" }, { "type": "rdp-page", "title": "AI for Manufacturing India", "url": "https://www.rdp.in/dc/ai-manufacturing", "sku": "", "text": "RDP AI infrastructure for smart factories. GPU servers for predictive maintenance, quality inspection & digital twins. Industry 4.0 Make in India. Get specs.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Ser" }, { "type": "rdp-page", "title": "RDP India | Predictive Maintenance", "url": "https://www.rdp.in/dc/ai-manufacturing/predictive-maintenance", "sku": "", "text": "RDP Technologies - Make in India IT hardware OEM. AI computing, desktops, servers, and enterprise solutions. ISO 9001, GeM listed. Contact us for details.. Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status Servic" }, { "type": "blog", "title": "RDP Blog - Insights from India's Value-for-Money IT Hardware OEM", "url": "https://rdp.in/blog/", "sku": "", "text": "Expert insights on Indian IT hardware, AI infrastructure, GeM procurement, and enterprise computing from RDP Technologies, India's Make in India OEM.. > Skip to content Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty" }, { "type": "blog", "title": "Make-in-India IT Hardware: Why Indian Orgs Choose Local", "url": "https://rdp.in/blog/why-indian-organizations-choosing-made-in-india-it-hardware-2026/", "sku": "", "text": "Indian organisations are switching to Make-in-India IT hardware to cut import risk, meet BIS norms, and build resilient supply chains in 2026.. > Skip to content Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Status" }, { "type": "blog", "title": "Cloud AI vs On-Prem: The Real Cost for Indian Enterprises", "url": "https://rdp.in/blog/the-real-cost-of-cloud-ai-why-indian-enterprises-are-moving-gpu-workloads-on-prem-in-2026/", "sku": "", "text": "Indian enterprises are moving AI workloads on-prem after discovering that cloud AI TCO exceeds on-premise infrastructure costs within 18 months at scale.. > Skip to content Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warra" }, { "type": "blog", "title": "Building an AI Factory in India: A CIO's 2026 Playbook", "url": "https://rdp.in/blog/building-your-ai-factory-in-india-a-cios-playbook-for-2026/", "sku": "", "text": "Indian CIOs building an AI factory in 2026 must navigate GPU procurement, sovereign data norms, and on-prem deployment to stay ahead of the curve.. > Skip to content Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty Sta" }, { "type": "blog", "title": "Sovereign AI Needs Sovereign Compute: India's Infra Case", "url": "https://rdp.in/blog/sovereign-ai-starts-with-sovereign-compute-the-case-for-indias-on-prem-ai-stack/", "sku": "", "text": "India cannot achieve sovereign AI without sovereign compute, and this piece makes the definitive case for domestically built server and edge infrastructure.. > Skip to content Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Wa" }, { "type": "blog", "title": "India's AI Hardware Market Is Tripling: Here's Who Wins", "url": "https://rdp.in/blog/indias-ai-hardware-market-triple-who-wins/", "sku": "", "text": "India’s AI hardware market is set to triple by 2028, and the OEMs, channel partners, and system integrators who localise fastest will capture the.... > Skip to content Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty S" }, { "type": "blog", "title": "AI PC Fleet Refresh 2026: Decision Framework for IT Heads", "url": "https://rdp.in/blog/2026-ai-pc-fleet-refresh-decision-framework-india/", "sku": "", "text": "Indian IT heads facing a 2026 AI PC fleet refresh need a clear decision framework covering TCO, BIS compliance, and AI-readiness before signing any.... > Skip to content Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty" }, { "type": "blog", "title": "GeM Playbook: What PSU IT Heads Get Wrong at Scale", "url": "https://rdp.in/blog/gem-playbook-psu-it-heads-6000-sku-catalogue/", "sku": "", "text": "PSU IT heads managing GeM catalogues of 6,000-plus SKUs routinely make procurement errors that inflate costs and delay deployments across government.... > Skip to content Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warrant" }, { "type": "blog", "title": "NEP 2020 AI Mandate: What Indian Schools Actually Need", "url": "https://rdp.in/blog/nep-2020-class-3-ai-mandate-schools-2026/", "sku": "", "text": "The Class-3 AI mandate under NEP 2020 requires Indian schools to deploy AI-ready hardware that most current lab configurations are entirely unprepared to.... > Skip to content Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Wa" }, { "type": "blog", "title": "Indian Hardware TCO: Five-Year Fleet Data vs Imported", "url": "https://rdp.in/blog/tco-indian-vs-imported-it-hardware-5-year-fleet/", "sku": "", "text": "Five years of Indian enterprise fleet data show that domestically manufactured hardware delivers measurably lower TCO than imported alternatives across.... > Skip to content Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warr" }, { "type": "blog", "title": "BIS Trusted Sources: What Indigenous Means for IT in 2026", "url": "https://rdp.in/blog/bis-trusted-sources-indigenous-it-procurement-india/", "sku": "", "text": "Indian IT procurement teams misread BIS and Trusted Source norms — this piece clarifies what indigenous hardware classification actually requires in.... > Skip to content Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warrant" }, { "type": "blog", "title": "The 10/10/10 Mission: 10,000 AI-Ready Institutions India", "url": "https://rdp.in/blog/10-10-10-mission-ai-ready-institutions-india/", "sku": "", "text": "India’s 10/10/10 mission to create 10,000 AI-ready institutions demands a coordinated push on hardware, teacher training, and curriculum delivery at.... > Skip to content Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warrant" }, { "type": "blog", "title": "Semicon India PLI 2.0: Five-Year Hardware Thesis 2026–2030", "url": "https://rdp.in/blog/semicon-india-pli-2-hardware-thesis-2026-2030/", "sku": "", "text": "Semicon India and PLI 2.0 together create a five-year hardware investment thesis that Indian VCs and OEM strategists cannot afford to misread heading into 2030.. > Skip to content Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Chec" }, { "type": "blog", "title": "Made-in-India Workstations: Media, Engineering, AI Studios", "url": "https://rdp.in/blog/workstations-media-engineering-ai-studios-india/", "sku": "", "text": "Indian media houses, engineering firms, and AI studios now have a credible Made-in-India workstation option meeting professional-grade performance and.... > Skip to content Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warra" }, { "type": "blog", "title": "AICTE Year of AI: The ITI Angle in India's Skills System", "url": "https://rdp.in/blog/aicte-year-of-ai-iti-skills-ecosystem/", "sku": "", "text": "AICTE’s Year of AI initiative has an underexplored ITI dimension that could bring AI skills delivery to hundreds of thousands of vocational learners.... > Skip to content Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warrant" }, { "type": "blog", "title": "State Digital Missions: IT Hardware for India’s 28 States", "url": "https://rdp.in/blog/state-digital-missions-it-hardware-partner-stack-india/", "sku": "", "text": "Every Indian state runs distinct digital missions with unique IT hardware requirements — this guide maps the partner stack OEMs need to win state.... > Skip to content Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check Warranty S" }, { "type": "blog", "title": "AI VIDYA: Making 100 Million Indian Students AI-Ready", "url": "https://rdp.in/blog/ai-vidya-making-100-million-indian-students-ai-ready/", "sku": "", "text": "NEP 2020 has made AI a formal classroom subject from Class 3. AICTE has told every engineering institution to treat AI literacy as a graduate attribute..... > Skip to content Become a Partner Login Contact Us Who We Serve Products AI Solutions Support Company Get a Quote GPU Mart Who We Serve India's value-for-money IT hardware brand 14 years. 28,000 sq ft. 100,000+ devices. From desktops to data center — designed, engineered, and manufactured in India. Why choose RDP Business Verticals Government & GeM 8,000+ SKUs on GeM. Bid, RA, BOQ & Direct (L1). Corporate & Institutional Standardized fleets with lifecycle support. AI Computing AI PCs, GPU workstations & edge devices. Data Center & AI Infra Servers, storage, GPU pods & rack integration. Download Company Profile Talk to Sales Products Desktops to data center, all Make in India 14 product categories across compute, AI, and data center. Deployment-ready from our 28,000 sq ft facility. Download Product Catalog Compute Desktop PCs AIO PCs Laptops Tablets Workstation PCs Servers Mini PCs Thin Clients AI Compute AI-Ready PCs GPU Workstations AI Starter Servers GPU Servers AI Storage AI-POD Solutions GeM Products Brochure Corp & Inst Brochure AI Computing Brochure Data Center & AI Infra Brochure AI Solutions Sovereign AI infrastructure End-to-end AI compute under one sovereign umbrella. Designed here. Manufactured here. Supported here. Talk to a Solutions Architect By Sector AI Edge PCs AI VIDYA AI Defence AI Health AI BFSI AI Manufacturing AI Governance AI Research Download AI Brochure Request AI BoQ Support SLA-driven. Not ticket-driven. Warranty. SLA. On-site service. Account management. Every commitment documented, every response time defined. Download SLA Commitment Get Help Contact Support Support & Warranty Check War" } ] }