--- title: "NVIDIA RTX PRO 6000 Server Edition GPU | AI Cloud India | From ₹182/hr | E2E Networks" description: "Rent the NVIDIA RTX PRO 6000 Blackwell Server Edition on E2E Networks. 96GB GDDR7, 4,000 AI TOPS, 70B LLM on a single GPU — from ₹182/hr. INR pricing. Data stays in India. Deploy in 60 seconds." url: "https://www.e2enetworks.com/gpus/nvidia-rtx-pro-6000" canonical: "https://www.e2enetworks.com/gpus/nvidia-rtx-pro-6000" provider: "E2E Networks Limited" type: "Product" keywords: ["rent rtx pro 6000 gpu", "rtx pro 6000 cloud", "nvidia rtx pro 6000 pricing", "rtx pro 6000 gpu cloud", "ai gpu rental", "gpu cloud computing", "llm training gpu", "gpu for machine learning", "deep learning gpu", "ai training infrastructure"] brand: "NVIDIA" gpuModel: "NVIDIA RTX PRO 6000" vramGB: 96 vcpus: 32 ramGB: 170 priceCurrency: "INR" pricePerHourINR: 182 taxNote: "Prices exclude GST" region: "India (Delhi NCR, Chennai)" generated: "2026-09-11" --- # NVIDIA RTX PRO 6000 Server Edition GPU | AI Cloud India | From ₹182/hr | E2E Networks > Rent the NVIDIA RTX PRO 6000 Blackwell Server Edition on E2E Networks. 96GB GDDR7, 4,000 AI TOPS, 70B LLM on a single GPU — from ₹182/hr. INR pricing. Data stays in India. Deploy in 60 seconds. Canonical page: https://www.e2enetworks.com/gpus/nvidia-rtx-pro-6000 One Server GPU. Every AI Workload. Now on E2E Cloud. The NVIDIA RTX PRO 6000 Blackwell delivers 4,000 AI TOPS and 96 GB of ECC-protected GDDR7 on dedicated, server-grade silicon. Run 70B models at FP8 on a single card with deterministic performance, isolated workloads, and a production SLA. ## 96 GB GDDR7. 4,000 AI TOPS. Built for Production. The RTX PRO 6000 Blackwell Server Edition is the most capable single-GPU instance on E2E Cloud — engineered for sustained production AI workloads, not burst experiments. Run 70B parameter models at FP8 on a single card with 26 GB of KV cache headroom remaining. Partition into up to four isolated 24 GB MIG instances for concurrent tenants. Deploy on hardened, monitored infrastructure backed by a production SLA. ## Key figures - **LLM Inference Gain — vs NVIDIA L40S:** 6× - **CFD vs 64-core CPU — faster simulations:** 4.5× - **Tensor Core Gain — vs 4th gen Tensor Cores:** 3× - **Max Context (Q4 70B) — single card, no splitting:** 128K - **Configurations:** MIG — Up to 4× 24GB isolated instances | 1× full 96GB — run concurrent isolated workloads on a single server GPU ## Instance specification - **GPU:** NVIDIA RTX PRO 6000 - **GPU memory (VRAM):** 96 GB - **vCPUs:** 32 - **System RAM:** 170 GB - **On-demand price:** ₹182/hour ($1.90/hour) - **Regions:** Delhi NCR and Chennai, India - **Billing:** Hourly, in INR, exclusive of GST ## Hardware capabilities - **AI Performance:** 4,000 TOPS — AI compute (FP4 with sparsity) - **AI Performance:** 120 TFLOPS — FP32 compute - **AI Performance:** 5th Gen Tensor Cores — 3× faster than previous gen - **Massive Memory:** 96GB GDDR7 — with ECC error correction - **Massive Memory:** 1,597 GB/s — memory bandwidth - **Massive Memory:** 70B models — on a single card — no multi-GPU needed - **Core Configuration:** 24,064 — CUDA Cores - **Core Configuration:** PCIe Gen 5 — interface — 2× bandwidth of Gen 4 - **Core Configuration:** 600W — sustained server-grade performance - **Advanced Ray Tracing:** 355 TFLOPS — ray tracing performance - **Advanced Ray Tracing:** 4th Gen RT Cores — 2× ray-triangle intersection rate - **Advanced Ray Tracing:** DLSS 4 — Multi Frame Generation — up to 3× faster frames ## The Performance Numbers | Metric | Value | Compared with | | --- | --- | --- | | Faster LLM Inference | 6× | vs NVIDIA L40S | | Faster Text-to-Video | 5.6× | vs NVIDIA L40S | | Faster CFD Simulation | 4.5× | vs 64-core CPU | | RT Core Ray Rate | 2× | vs previous generation | | More Ray-Traced Triangles | 100× | RTX Mega Geometry | ## Pricing NVIDIA RTX PRO 6000 on E2E Networks, billed from Indian data centers. | Term | Price (INR) | Price (USD) | | --- | --- | --- | | On-demand, per hour | ₹182 | $1.90 | | 1 month (total) | ₹1,19,040 | $1,240.00 | | 6 months (total) | ₹6,79,200 | $7,075.00 | | 12 months (total) | ₹13,45,440 | $14,015.00 | INR is the authoritative billing currency; USD figures are a converted convenience. Prices exclude GST. Live rate card: https://www.e2enetworks.com/pricing · JSON feed: https://www.e2enetworks.com/pricing.json ## Supported model sizes Which models fit on RTX PRO 6000, by precision and VRAM footprint. | Model | Notes | Precision | VRAM required | Fit | Example workloads | | --- | --- | --- | --- | --- | --- | | 7B | Small — fast inference | FP16 / FP4 | ~14 GB | Full headroom | Llama 3 7B, Mistral 7B, Gemma 7B, Qwen2.5 7B | | 13B | Balanced quality | FP16 | ~26 GB | Full headroom | Llama 2 13B, CodeLlama 13B, Vicuna 13B | | 30–34B | High quality | AWQ / Q4 | ~18 GB | Full headroom | Qwen3-Coder-30B, Yi-34B, DeepSeek-Coder-33B | | 70B | Production frontier | FP8 | ~70 GB | 26 GB KV cache left | Llama 3 70B, Qwen 72B, Falcon 70B, Mixtral 8×7B | | 70B | Max throughput | Q4 | ~38 GB | 128K ctx supported | Llama 3 70B Q4, full long-context deployment | | 8×22B | 141B total · MoE | Q4_K_M | ~71 GB | Max capacity · 25GB headroom | Mixtral 8×22B Instruct, 141B params, 39B active | ## Built for Every Professional AI Workload From local LLM inference to engineering simulation — the RTX PRO 6000 handles it all on a single card. - **AI Development & LLM Fine-Tuning** — Fine-tune 7B models at full FP16 precision. Run 70B models locally at FP8 without multi-GPU complexity. Deploy on E2E Cloud — no multi-GPU complexity, no infrastructure overhead. (4,000 TOPS — AI Performance) - **Data Science & Analytics** — Process large datasets efficiently using NVIDIA RAPIDS and CUDA-X libraries. Accelerate model training, evaluation, and visualisation with 96GB of GPU memory — no data leaves India. (96 GB — GDDR7 Memory) - **3D Rendering & VFX** — RTX Neural Shaders and DLSS 4 Multi Frame Generation enable real-time photorealistic rendering. Handle billion-polygon scenes and 4K textures on a single server GPU. (4th Gen RT Cores) - **Video Production & Broadcast** — 9th Gen NVENC and 6th Gen NVDEC with 4:2:2 support accelerate 4K/8K video encoding, decoding, and AI-enhanced broadcast workflows in real time. (8K Video Support) - **Engineering Simulation** — Run computational fluid dynamics 4.5× faster than a 64-core CPU. Accelerate structural analysis, physics simulation, and digital twin development with full GPU-accelerated solvers. (4.5× Faster than CPU) - **Agentic AI Development** — Build and deploy autonomous AI agents with 128K context windows at Q4 precision. The 96GB VRAM enables long-horizon reasoning that no other single server GPU can match. (128K Context Window) ## Related pages - [All GPU instances and prices](https://www.e2enetworks.com/gpus) - [GPU Cloud overview](https://www.e2enetworks.com/gpu-cloud) - [Full rate card](https://www.e2enetworks.com/pricing) - [Deploy models as inference endpoints](https://www.e2enetworks.com/inference-endpoints) - [Fine-tuning and distributed training](https://www.e2enetworks.com/training-fine-tuning) ## Get started Deploy RTX PRO 6000 GPUs for AI training, fine-tuning, simulation, and professional graphics — from a single card to an 8-GPU cluster. INR billing. Indian data centres. No commitment needed to start. Pricing: https://www.e2enetworks.com/pricing · Talk to sales: https://www.e2enetworks.com/contact-sales - [Deploy RTX PRO 6000](https://myaccount.e2enetworks.com/accounts/signup) - [Talk to an Expert](https://www.e2enetworks.com/contact-sales) --- This Markdown is generated from the same data that renders https://www.e2enetworks.com/gpus/nvidia-rtx-pro-6000. Provider: E2E Networks Limited (NSE: E2E), India. Site index for AI agents: https://www.e2enetworks.com/llms.txt