Rent NVIDIA RTX PRO 6000 in India — ₹1,10,000/month ($1,249)
96GB GDDR7 — image and video generation, fine-tuning, and quantized-70B inference.
RTX PRO 6000 pricing
An NVIDIA RTX PRO 6000 96GB node costs ₹1,10,000 ($1,249) per month in ZenoCloud’s Mumbai datacenter as of July 2026, about ₹151 per hour effective, on a 1-month minimum. It is among the lowest published monthly rates for this card in India. Managed ops adds ₹15,000 ($179) per node per month.
| Config | Total VRAM | Per Node / Month | ≈ Effective / hr |
|---|---|---|---|
| 1× RTX PRO 6000 96GB | 96GB | ₹1,10,000$1,249 | ≈ ₹151/hr≈ $1.71/hr |
| 2× RTX PRO 6000 | 192GB | On request | — |
| 4× RTX PRO 6000 | 384GB | On request | — |
* Prices checked July 2026. Monthly commitment, 1-month minimum; no hourly product. ≈ /hr = monthly ÷ 730, for comparison only. INR prices attract 18% GST, claimable as input tax credit. Managed ops add-on: ₹15,000 ($179) per node/month. Node CPU, RAM, and NVMe sized at scoping; multi-GPU and NVLink pricing confirmed at scoping.
Will your model fit on one RTX PRO 6000?
Weight sizes at the stated precision; KV cache needs headroom on top. Unsure — the trial node settles it.
| Model | Params | Precision | Fits on 1× RTX PRO 6000? | Notes |
|---|---|---|---|---|
| SDXL / Flux.1 | 2–12B | FP16 | Yes | Image gen with batch headroom |
| Mistral 7B | 7B | FP16 | Yes | ~14GB weights |
| Llama 2 13B | 13B | FP16 | Yes | ~26GB weights |
| Qwen2.5 32B | 32B | FP16 | Yes | ~64GB weights |
| Llama 3.1 70B | 70B | INT4 (AWQ/GPTQ) | Yes | ~40GB weights quantized |
| Llama 3.1 70B | 70B | FP8 | Tight | ~70GB weights; limited KV cache |
| Llama 3.1 70B | 70B | FP16 | No | ~140GB weights; H200 or B200 |
RTX PRO 6000 — or something else?
Where does the RTX PRO 6000 fit?
Between the L40S and the A100 on price, above both on VRAM: 96GB of GDDR7 runs SDXL and Flux image pipelines, video generation, and Llama 3.1 70B quantized on a single card. Blackwell tensor cores add FP4 inference. It skips NVLink, so keep it to single-GPU workloads.
RTX PRO 6000 vs L40S
Twice the VRAM (96GB vs 48GB), roughly twice the bandwidth (1.79 TB/s GDDR7 vs 864 GB/s GDDR6), and a Blackwell generation ahead of Ada, at ₹1,10,000 vs ₹55,000 per month. The L40S serves 7B–13B models for half the price; step up when you need 70B quantized, 32B at FP16, or heavier image and video pipelines.
RTX PRO 6000 vs A100
More VRAM (96GB vs 80GB) and newer tensor cores with FP4, at ₹1,10,000 vs ₹97,000 per month. The A100 keeps two advantages: HBM2e at 2 TB/s and NVLink for multi-GPU training. Pick the RTX PRO 6000 for single-node inference and generation; pick the A100 when the job scales across GPUs.
NVIDIA RTX PRO 6000 96GB — chip reference
| Architecture | Blackwell |
| VRAM | 96GB GDDR7 with ECC |
| Memory bandwidth | 1.79 TB/s |
| CUDA cores | 24,064 |
| Tensor cores | 752 (5th gen) |
| AI performance | Up to 4,000 TOPS (FP4) |
| Interconnect | PCIe Gen5 x16 (no NVLink) |
| MIG | Up to 4 instances |
| TDP | Up to 600W |
RTX PRO 6000 hosting questions
How much does an RTX PRO 6000 cost per month in India? +
₹1,10,000 ($1,249) per node per month in our Mumbai datacenter, about ₹151/hr effective, as of July 2026. Monthly commitment, 1-month minimum; no hourly product. Managed ops adds ₹15,000 ($179) per node per month. 18% GST applies on INR invoices and is claimable as input tax credit.
RTX PRO 6000 vs L40S: which should I choose? +
Choose the L40S at ₹55,000 per month for 7B–13B inference and standard SDXL image generation. Choose the RTX PRO 6000 at ₹1,10,000 when you need its 96GB: Llama 3.1 70B INT4, Qwen2.5 32B FP16, video generation, or larger image batches. Same single-GPU deployment model on both.
What workloads suit the RTX PRO 6000? +
Image and video generation (SDXL, Flux.1, LTX-style pipelines), quantized 70B inference, 32B-class models at FP16, and LoRA fine-tuning of 7B–13B models. It has no NVLink, so multi-GPU tensor parallelism belongs on A100, H100, or H200 nodes instead.
How long does RTX PRO 6000 provisioning take? +
A single RTX PRO 6000 node is ready in 2–3 business days, the fastest class in our lineup alongside the L40S. Multi-card configurations are confirmed during scoping. We share the exact lead time before you commit.
Does RTX PRO 6000 hosting satisfy DPDP data residency? +
Yes. The node runs in our Mumbai datacenter under Indian jurisdiction. Generation prompts, outputs, and inference payloads stay on your server; we collect only infrastructure metrics. We sign a Data Processing Agreement confirming no data leaves India.
Is there an RTX PRO 6000 trial before the monthly commitment? +
Yes. We provision a trial node so you can benchmark your generation pipeline or quantized model on the actual hardware before the 1-month commitment. Request one with your workload and target throughput.
Benchmark your model on an RTX PRO 6000 first.
We provision a trial node, you validate throughput on the exact hardware, then convert to a monthly node.