--- title: "RTX PRO 6000 WS vs RTX 6000Ada: Specs & Price per Hour (2026) | PowerGPU" description: "RTX PRO 6000 WS vs RTX 6000Ada: 96 vs 48 GB VRAM, 505 vs 364 FP16 TFLOPS, $1.040 vs $0.467/hr on PowerGPU. Specs side by side, live rental prices, which to rent." url: https://powergpu.ai/compare/rtx-pro-6000-ws-vs-rtx-6000ada last_modified: 2026-09-14T11:04:20+00:00 prices_as_of: 2026-09-14 site: PowerGPU (powergpu.ai) --- Compare · prices checked 2026-09-14 # RTX PRO 6000 WS vs RTX 6000Ada: specs, price per hour, which to rent NVIDIA RTX PRO 6000 WS (96 GB, **$1.040** /hr) against NVIDIA RTX 6000Ada (48 GB, **$0.467** /hr): public specs side by side, live fixed prices from our sheet, what fits in each card's VRAM, and a verdict written for real workloads — both are rentable right now. - [NVIDIA RTX PRO 6000 WS Blackwell · 96 GB GDDR7 · 505 FP16 TFLOPS · $1.040/hr on-demand · $0.520/hr interruptible · 74 online](https://powergpu.ai/gpu/rtx-pro-6000-ws) - [NVIDIA RTX 6000Ada Ada Lovelace · 48 GB GDDR6 · 364 FP16 TFLOPS · $0.467/hr on-demand · $0.233/hr interruptible · 34 online](https://powergpu.ai/gpu/rtx-6000ada) ## RTX PRO 6000 WS vs RTX 6000Ada specifications Public NVIDIA figures (dense, non-sparsity). The last column is RTX PRO 6000 WS relative to RTX 6000Ada. | Spec | RTX PRO 6000 WS | RTX 6000Ada | Difference | | --- | --- | --- | --- | | Architecture | Blackwell (2025) | Ada Lovelace (2022) | — | | VRAM | 96 GB GDDR7 | 48 GB GDDR6 | +100% | | Memory bandwidth | 1,792 GB/s | 960 GB/s | +87% | | FP16 tensor (dense) | 505 TFLOPS | 364 TFLOPS | +39% | | FP32 | 125.0 TFLOPS | 91.1 TFLOPS | +37% | | CUDA cores | 24,064 | 18,176 | +32% | | TDP | 600 W | 300 W | +100% | | PCIe · NVLink | Gen 5.0 · no NVLink | Gen 4.0 · no NVLink | — | | PowerScore (RTX 3090 = 100) | 356 | 256 | +39% | | Max GPUs per machine | 8× | 8× | — | ## RTX PRO 6000 WS vs RTX 6000Ada price per hour Fixed rates from our sheet — every on-demand price is the marketplace median × 0.70, rounded down. Monthly = 730 hours. | Rate | RTX PRO 6000 WS | RTX 6000Ada | Cheaper | | --- | --- | --- | --- | | On-demand, per GPU-hour | $1.040 | $0.467 | RTX 6000Ada (−55%) | | Interruptible, per GPU-hour | $0.520 | $0.233 | RTX 6000Ada | | Reserved (3 mo), per GPU-hour | $0.676 | $0.303 | RTX 6000Ada | | On-demand, per month | $759 | $341 | RTX 6000Ada | | Market median (reference) | $1.49 | $0.67 | — | | $ per 1,000 FP16 TFLOP-hours | $2.06 | $1.28 | RTX 6000Ada (better value) | | $ per GB of VRAM per hour | $0.0108 | $0.0097 | RTX 6000Ada (better value) | Try a full month with storage and bandwidth in the [GPU cost calculator](https://powergpu.ai/calculator). ## What fits in VRAM: 96 GB vs 48 GB | Workload | RTX PRO 6000 WS | RTX 6000Ada | | --- | --- | --- | | Largest LLM in FP16, one card | ~32B | ~14B | | Largest LLM at 4-bit, one card | ~141B | ~72B | | Flux dev (FP8, ~17 GB) | fits | fits | | Wan 2.x 14B video (offloaded) | yes | yes | | 70B 4-bit LLM on one card | yes | yes | Rules of thumb: ~2.4 GB per billion parameters in FP16 all-in, ~0.62 GB in 4-bit. Full tables in the [VRAM guide](https://powergpu.ai/guides/llm-vram-requirements). ## Verdict: which should you rent? The RTX PRO 6000 Blackwell doubles VRAM (96 vs 48 GB), nearly doubles bandwidth with GDDR7 and adds FP4; the RTX 6000 Ada is cheaper and still a superb 48 GB workstation card. Go Blackwell for 70B single-card inference and huge scenes, Ada for everything under 48 GB. - **Cheaper per hour:** RTX 6000Ada ($0.467 vs $1.040, −55%). - **More VRAM:** RTX PRO 6000 WS (96 GB vs 48 GB). - **More FP16 throughput:** RTX PRO 6000 WS (about 1.4×). - **Best value per TFLOP-hour:** RTX 6000Ada. - **Best value per GB of VRAM:** RTX 6000Ada. - **Multi-GPU:** RTX PRO 6000 WS over PCIe · RTX 6000Ada over PCIe. ## Related comparisons [All comparisons](https://powergpu.ai/compare) - [RTX PRO 6000 WS vs H100 PCIE $1.040 vs $1.867 per hour](https://powergpu.ai/compare/rtx-pro-6000-ws-vs-h100-pcie) - [RTX PRO 6000 WS vs RTX 5090 $1.040 vs $0.439 per hour](https://powergpu.ai/compare/rtx-pro-6000-ws-vs-rtx-5090) - [RTX 6000Ada vs RTX A6000 $0.467 vs $0.281 per hour](https://powergpu.ai/compare/rtx-6000ada-vs-rtx-a6000) ## RTX PRO 6000 WS vs RTX 6000Ada: FAQ Deeper reading: [H100 vs H200 vs B200](https://powergpu.ai/guides/h100-vs-h200-vs-b200), [RTX 4090 vs RTX 5090](https://powergpu.ai/guides/rtx-4090-vs-rtx-5090), [how cloud GPU pricing works](https://powergpu.ai/guides/cloud-gpu-pricing-explained). **Is the RTX PRO 6000 WS faster than the RTX 6000Ada?** On dense FP16 tensor throughput the RTX PRO 6000 WS leads by about 1.4× (505 vs 364 TFLOPS). Memory bandwidth matters as much for inference: RTX PRO 6000 WS 1,792 GB/s vs RTX 6000Ada 960 GB/s. **Which is cheaper to rent, the RTX PRO 6000 WS or the RTX 6000Ada?** The RTX 6000Ada: $0.467/hr on-demand versus $1.040/hr — 55% less. Interruptible rates are $0.520 (RTX PRO 6000 WS) and $0.233 (RTX 6000Ada). Per TFLOP-hour the better value is the RTX 6000Ada. **Which has more VRAM and what does that change?** The RTX PRO 6000 WS has 96 GB versus 48 GB. In LLM terms that is roughly a 32B FP16 model (or ~141B in 4-bit) on one card against 14B FP16 (~72B 4-bit). If the model does not fit, speed is irrelevant. **Can I rent both on PowerGPU right now?** Yes — 74 × RTX PRO 6000 WS and 34 × RTX 6000Ada are online as this page renders, deployable in about 30 seconds, billed per second, paid in crypto with no KYC. --- *About PowerGPU:* PowerGPU (powergpu.ai) is a cloud GPU rental service offering 80 NVIDIA GPU models — from the RTX A2000 at $0.024/hr to the B300 — at fixed prices set at least 30% below the public GPU marketplace median and re-checked weekly (H100 SXM: $1.428/hr on-demand). Billing is per second with no minimums; payment is crypto only (USDT, BTC, XMR, ETH, SOL, LTC, TRX) with no KYC. Instances run in Tier-III datacenters across 32 regions with a 99.9% uptime SLA and deploy in about 30 seconds from the web console (cloud.powergpu.ai) or the REST API. Source: https://powergpu.ai/compare/rtx-pro-6000-ws-vs-rtx-6000ada · Site index for AI assistants: https://powergpu.ai/llms.txt · Full content: https://powergpu.ai/llms-full.txt