NVIDIA GPU India: H100, RTX 6000 Ada, DGX systems for your AI workload
RTX A6000 and RTX 6000 Ada workstation cards for design and inference. H100, H200 and the new B100, B200 data-centre GPUs for LLM training. DGX H100 turnkey systems for serious AI labs. Sirius Star sources, sizes and delivers across India. Quote in four hours.
Serving 200+ Indian businesses · 15+ years sourcing enterprise hardware · Microsoft Partner · Bitdefender Partner · Pan-India delivery.
Why teams buy NVIDIA instead of renting
A single H100 80GB on Indian cloud rents for roughly ₹2.5 to ₹3.5 Lakh per month. Owned H100 capex of ₹35 Lakh pays back in about 14 months at continuous use. After that the GPU keeps earning. We do the sizing math before you sign anything.
What NVIDIA actually sells, and which line fits your workload
NVIDIA splits into four buying lanes. Workstation cards live in a tower or rack workstation. Data-centre GPUs ship in 8-GPU server chassis. DGX systems are turnkey AI machines. Grace and Jetson cover the edges of the portfolio. Pick by workload, not by headline.
RTX A6000, RTX 6000 Ada, L40S
48 GB VRAM cards for CAD, Blender, Maya, Unreal, smaller LLM inference and stable-diffusion fine-tuning. Drops into a Lenovo P-series or HP Z-series workstation. The Ada generation roughly doubles ray-trace throughput over Ampere.
RTX A6000 from ₹4 Lakh+, RTX 6000 Ada from ₹6 Lakh+, L40S from ₹8 Lakh+ — approximate India retail.
H100, H200, B100, B200
The cards everyone is queuing for. H100 80GB SXM for LLM training and large inference. H200 doubles HBM to 141 GB so a 70B model fits in fewer GPUs. B100 and B200 are the new Blackwell generation, shipping in India through 2026.
H100 80GB SXM from ₹35 Lakh+, H200 from ₹42 Lakh+ — exact quote depends on chassis and supply window.
DGX H100, DGX B100
Eight H100 or B100 GPUs in one chassis with NVLink and InfiniBand built in. NVIDIA validates the whole stack including drivers, networking and AI Enterprise software. The fastest way for a lab to go from PO to first training run.
DGX H100 from ₹3.5 Crore+. DGX B100 supply opens in waves, ask for current window.
Grace Hopper, Grace Blackwell
ARM-based Grace CPU stitched to Hopper or Blackwell GPU over NVLink-C2C. Useful for very large recommender systems and graph workloads where CPU memory bandwidth was the bottleneck. Niche but powerful for the right workload.
Quote on request — typically lands in the H100 to DGX range.
Jetson Orin, Jetson AGX Orin
Embedded GPU modules for robots, drones, cameras, factory-floor vision. Runs the same CUDA stack as the big cards. Popular with Indian manufacturing and ADAS teams. From a dev kit on a desk to a deployed fleet.
Jetson Orin Nano dev kit from ₹45,000+, AGX Orin from ₹2 Lakh+.
ConnectX, BlueField, Spectrum-X
The GPU is only half the story. ConnectX-7 NICs and BlueField DPUs move data between GPUs at 400 Gb/s. Spectrum-X is NVIDIA’s Ethernet fabric for AI. Specify the network when you size the cluster, not after.
Per-port pricing — sized as part of the rack quote.
NVIDIA vs AMD MI300 vs Intel Gaudi for Indian buyers
NVIDIA dominates Indian AI buying for one reason — software. CUDA, cuDNN and TensorRT have a decade of head start, and every major model ships with NVIDIA support first. AMD MI300X and Intel Gaudi 3 are real alternatives on paper, but the local talent pool and tooling ecosystem still lean heavily toward NVIDIA. We will still quote AMD or Intel if you have the in-house team to run them.
| What you compare | NVIDIA H100 / H200 | AMD Instinct MI300X | Intel Gaudi 3 |
|---|---|---|---|
| Software stack | CUDA, cuDNN, TensorRT, AI Enterprise — mature | ROCm — improving fast, gaps remain | SynapseAI — narrower model coverage |
| HBM memory | 80 GB (H100) or 141 GB (H200) | 192 GB on MI300X — leads on raw memory | 128 GB on Gaudi 3 |
| India availability | Wide — every major OEM ships it | Narrower — fewer integrators | Limited — Supermicro and Dell only |
| Talent pool | Largest — most engineers trained on CUDA | Growing — small but capable | Smallest — niche skill |
| Price per GPU | Premium — pay for the ecosystem | Roughly 10 to 20% lower | Often the cheapest of the three |
How GPU procurement actually runs in India
Workload sizing call
We start with one question. What model, what batch size, what training or inference target. From there we work backward to GPU count, VRAM, NVLink topology and network. No sales theatre.
BOQ and quote in four hours
Bill of quantities covers GPUs, server chassis, NICs, switches, racks, PDUs and the AI software stack. Quote includes distributor source, lead time and the rupee landing cost.
Authorised distributor sourcing
We buy through NVIDIA’s authorised India distributors. That keeps your warranty valid and supply traceable. Grey-market H100s exist, we will not sell them.
Deliver, rack, validate
Courier delivery for workstation cards. White-glove deployment for DGX and multi-rack clusters. We benchmark with your test workload before handover so you know what you bought.
The India AI ecosystem you actually plug into
NVIDIA hardware does not live in isolation. CDAC’s PARAM supercomputers run NVIDIA GPUs. IIT supercomputing centres at Madras, Delhi and Kanpur run mixed H100 and A100 estates. Yotta, E2E and Sify all rent NVIDIA cloud capacity inside India. Global Capability Centres in Bangalore and Hyderabad standardised on NVIDIA years ago. Your stack will talk to all of this without translation.
Where NVIDIA earns its place in Indian industry
AI and ML research
LLM pre-training and fine-tuning at IITs, IISc, AI startups in Bangalore. H100 and H200 clusters with InfiniBand. The default stack for serious work.
Global Capability Centres
Bangalore and Hyderabad GCCs running internal copilots, code-gen models and RAG systems. Typically 4 to 16 H100 nodes per project, scaling as adoption grows.
Manufacturing and CAD
Tata, Mahindra, Bajaj design teams running CATIA, NX and Solidworks on RTX A6000 and RTX 6000 Ada workstations. Real-time ray tracing for design review.
Healthcare imaging
Apollo, Manipal, AIIMS using L40S and A100 for radiology AI, pathology slide analysis, and medical-imaging research workflows.
Telecom and 5G
Jio, Airtel and BSNL using NVIDIA Aerial and BlueField for 5G RAN, network function offload and edge inference at cell sites.
Robotics and edge
Jetson Orin in factory-floor cameras, AMR fleets, drone payloads. Same CUDA code from cloud training to edge deployment.
NVIDIA GPU India FAQ
What is the price of an NVIDIA H100 in India?
Approximate India retail for an H100 80GB SXM lands from ₹35 Lakh and up. The exact landing cost depends on chassis, NIC, the rupee, and the supply window. Send us the workload and we will quote within four hours.
Should I buy a GPU or rent on Indian cloud?
Continuous training runs favour ownership — payback is roughly 14 months on an H100 at full utilisation. Bursty or experimental workloads favour rental on Yotta, E2E or Sify. We will run the math on your usage pattern, not push you to either side.
Is Sirius Star an authorised NVIDIA partner in India?
We source through NVIDIA’s authorised India distributor channel. We carry Microsoft Partner and Bitdefender Partner badges from our own programmes. We do not claim NVIDIA partner status on this page until that is formally signed.
What is the lead time for an H100 or DGX system in India?
Workstation cards typically ship in two to four weeks. H100 server nodes run four to eight weeks depending on chassis. DGX H100 and DGX B100 land in supply waves — we tell you the current window when you ask, not a stock answer.
Can you handle the full data-centre build, not just the GPU?
Yes. We quote the chassis, the InfiniBand or Spectrum-X fabric, the racks, the PDU, the cooling brief and the AI Enterprise software stack as one bundle. One PO covers the lot.
What about Blackwell — B100 and B200?
Blackwell ships in waves through 2026. Indian supply is opening up but still tight. If you need Blackwell, get on the queue early. We can flag your slot with the distributor when you start the conversation.
Why Sirius Star for NVIDIA in India
15+ years sourcing enterprise hardware. Authorised distributor channel only. Four-hour quote turnaround. PAN-India delivery and white-glove install for cluster builds. We will not invent a partnership badge we do not hold.
Bitdefender Partner
15+ years in enterprise IT
BNI member, Mumbai
Send us your AI workload. BOQ in four hours.
Model, batch size, training target, deployment plan. We come back with GPU count, chassis, network, software and the landed-in-India price. No hedging, no fishing call.
P.S. An Indian fintech’s data science lead asked: ‘GPU or cloud GPU credits?’ We modelled both. On-prem H100 cluster paid back in 14 months. He still gets to brag about the H100s in the rack.