NVIDIA GPU infrastructure in India, sized against your workload before you sign anything.
How a Bengaluru AI startup nearly bought twice the GPUs it needed for a training run, until a sizing call cut the order in half. Story below.
NVIDIA AI and data centre GPUs at a glance
Why NVIDIA anchors most Indian ai and data centre gpus estates.
- What it is
- NVIDIA is the dominant GPU platform for AI training, inference and professional visualisation, sold across workstation cards, data centre GPUs, turnkey DGX systems and edge modules.
- Why CUDA matters
- CUDA, cuDNN and TensorRT have a decade head start over rival software stacks, which is the main reason Indian AI teams standardise on NVIDIA.
- India presence
- NVIDIA GPUs run inside CDAC’s PARAM supercomputers, IIT supercomputing centres, and the AI clusters used by Yotta, E2E and Sify for India-hosted GPU cloud.
- Hardware lanes
- Workstation cards, data centre GPUs, turnkey DGX systems, the Grace CPU platform, Jetson edge modules, and ConnectX or BlueField networking gear.
- India sourcing
- Sirius Star buys through NVIDIA’s authorised India distributor channel only. We do not sell grey-market cards, even when a customer asks.
- Typical deployment
- A single workstation card for a design seat, up to an eight-GPU H100 or DGX cluster for LLM training, sized against a real workload before the order is placed.
The NVIDIA AI and data centre GPUs ranges Sirius Star supplies
Pick the range that matches the use case. We size the mix in the free 30-minute review.
RTX A6000, RTX 6000 Ada, L40S
48GB VRAM cards for CAD, Blender, Maya, Unreal, and smaller AI inference, dropped into a tower or rack workstation.
- Fits a Lenovo P-series or HP Z-series workstation
- Ada generation roughly doubles ray-trace throughput over Ampere
- Handles smaller LLM inference and stable-diffusion fine-tuning
- Approximate India retail, exact quote depends on chassis and configuration
H100, H200, B100, B200
The cards Indian AI labs queue for. H100 and H200 for LLM training and large inference, B100 and B200 as the new Blackwell generation.
- H200 doubles HBM to 141GB, so a 70B model fits in fewer GPUs
- Blackwell (B100, B200) is shipping into India through 2026 in supply waves
- Ships in eight-GPU server chassis with NVLink between cards
- Exact price depends on chassis, NIC and the current supply window
DGX H100, DGX B100
Eight H100 or B100 GPUs in one validated chassis with NVLink and InfiniBand built in, the fastest path from PO to first training run.
- NVIDIA validates the whole stack, including drivers and networking
- AI Enterprise software licence included
- Best fit for a lab that wants one accountable vendor for the box
- Ask for the current Blackwell supply window when you enquire
Grace Hopper, Grace Blackwell
An ARM-based Grace CPU stitched to a Hopper or Blackwell GPU over NVLink-C2C, built for workloads where CPU memory bandwidth was the bottleneck.
- Useful for very large recommender systems and graph workloads
- A niche fit, but the right one for memory-bound pipelines
- Sized as part of the same workload sizing call
- Supply and lead time confirmed at enquiry, not published as a fixed number
Jetson Orin, Jetson AGX Orin
Embedded GPU modules for robots, drones, cameras and factory-floor vision, running the same CUDA stack as the data centre cards.
- Popular with Indian manufacturing and ADAS teams
- Code moves from cloud training to edge deployment without a rewrite
- Scales from a single dev kit on a desk to a deployed fleet
- Fits factory-floor vision and drone payload projects
ConnectX, BlueField, Spectrum-X
The GPU is only half the story. ConnectX NICs and BlueField DPUs move data between GPUs at up to 400 Gb/s, with Spectrum-X as the Ethernet fabric built for AI traffic.
- Specify the network fabric when you size the cluster, not after
- BlueField DPUs offload networking and security tasks from the CPU
- Spectrum-X is built specifically for AI east-west traffic patterns
- Quoted as one bundle with the GPU and rack, not a separate order
NVIDIA AI and data centre GPUs vs AMD, Intel
All four are honest choices. Most Indian buyers land on the first option for service depth and ecosystem fit.
| Brand | Where it wins | Best fit |
|---|---|---|
| NVIDIA via Sirius Star | Deepest software stack and the widest India availability across every major server OEM | Teams that want the largest talent pool and the least integration risk. |
| AMD Instinct MI300X | 192GB of HBM memory, ahead of both NVIDIA and Intel on raw capacity | Memory-bound workloads where a team already has ROCm experience in-house. |
| Intel Gaudi 3 | Often the lowest price per GPU of the three | Budget-constrained projects with a narrower, well-understood model set. |
How a Sirius Star NVIDIA procurement runs
Free 30 minute review first. Then a written quote in 24 working hours.
Size
Free workload sizing call, model, batch size, training or inference target.
Written quote
In 24 working hours. GPU, network and rack bill of quantities, GST broken out.
Authorised sourcing and delivery
Ordered through NVIDIA’s authorised India distributor, delivered and racked.
Benchmark and lifecycle wrap
Tested against your workload, then support tier and quarterly capacity review.
Buying NVIDIA GPUs in India: an AI infrastructure field guide
A short guide to sizing an NVIDIA GPU order, from a single workstation card to a full DGX cluster.
- How to size a GPU order against real model and batch size, not a round number.
- The 8-point checklist before you sign a GPU purchase order.
- Why authorised-channel sourcing protects the warranty on every card.
- Four moves that quietly change what a GPU order costs.
NVIDIA AI and data centre GPUs India FAQ
Common questions about this brand for Indian buyers. Hover any underlined term for a plain-English definition.
What is the price of an NVIDIA H100 in India?
Approximate India retail for an H100 80GB SXM lands from Rs 35 Lakh and up. The exact landed cost depends on chassis, network fabric and the current supply window. Send us the workload and we quote in writing within 24 working hours.
Should I buy a GPU or rent on Indian cloud?
Continuous training runs usually favour ownership. Payback on an owned H100 typically runs around fourteen months at full utilisation. Bursty or experimental workloads often favour renting from an Indian GPU cloud provider. We run the math on your usage pattern before recommending either.
Is Sirius Star an authorised NVIDIA partner in India?
We source NVIDIA hardware through NVIDIA’s authorised India distributor channel, which keeps the warranty valid and supply traceable. We do not claim formal NVIDIA partner status on this page unless that status has been 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 usually run four to eight weeks depending on chassis. DGX H100 and DGX B100 land in supply waves, and we share the current window when you enquire rather than quoting a fixed number.
Can Sirius Star handle the full data centre build, not just the GPU?
Yes. We quote the chassis, the InfiniBand or Spectrum-X fabric, the racks, the power and cooling brief, and the AI Enterprise software stack as one bundle, on one purchase order.
What about Blackwell, the B100 and B200?
Blackwell is shipping into India in waves through 2026, and supply is still tight. If Blackwell fits your workload, we recommend starting the conversation early so we can flag your position with the distributor.
Not sure how many GPUs you actually need?
Send us your model, batch size and training target. We come back with a sized bill of quantities and a landed India price, not a chip-name pitch.
Pair this on one PO
What buyers typically add to a Sirius Star order. Each link is a live page on the Sirius Star site.
Related reading from the Sirius Star blog
Long-form context from our team. Each link is a live post on siriusstar.in.