NVIDIA RTX PRO 6000 Blackwell (Max-Q Edition) for local LLMs
Written by Jakub Rusinowski · Last updated
With 96 GB of GDDR7 at 1,792 GB/s, the RTX PRO 6000 Blackwell (Max-Q Edition) runs 127 catalogued models at Q4_K_M with 8K context. The largest that fits is Devstral-2 123B (~75.1 GB), and the top pick is Devstral-2 123B at 12–26 tok/s.
The 96 GB, 1,792 GB/s memory system of the RTX PRO 6000 in a 300 W, blower-style card for multi-GPU workstations. Board power is not stored: only NVIDIA's page states it.
Models that run on the RTX PRO 6000 Blackwell (Max-Q Edition)
Q4_K_M, 8K context, 96 GB usable. Ranked by quality and speed.
| Model | Memory · marker = 96 GB | VRAM | Speed |
|---|---|---|---|
| Devstral-2 123B Devstral | 75.1 GB | 12–26 tok/s | |
| Qwen 3.5 122B-A10B Qwen 3.5 | 74.5 GB | 80–167 tok/s | |
| Nemotron 3 Super 120B-A12B Nemotron 3 Super | 73.3 GB | 73–152 tok/s | |
| Mistral Small 4 119B-A6.5B Mistral Small 4 | 72.6 GB | 51–105 tok/s | |
| GPT-OSS 120B GPT-OSS | 71.9 GB | 139–289 tok/s | |
| Llama 4.5 Scout Llama 4.5 | 66.6 GB | 60–125 tok/s | |
| Llama 4 Scout 17B Llama 4 | 68.2 GB | 65–134 tok/s | |
| Llama 3.2 Vision 90B Llama 3.2 Vision | 57.8 GB | 16–34 tok/s | |
| Qwen3-Coder-Next (80B-A3B MoE) Qwen3-Coder | 49.1 GB | 128–267 tok/s | |
| Kolibri 1 Kolibri | 48.4 GB | 174–362 tok/s | |
| Llama 3.3 70B Instruct Llama 3.3 | 45.7 GB | 20–43 tok/s | |
| Cogito v1 70B Cogito v1 | 45.7 GB | 20–43 tok/s |
Buy it or rent the same memory
Buy the card, or rent a GPU with the same memory by the hour to try models first.
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Speed vs other GPUs
Llama 3.1 8B, Q4_K_M. Estimated ranges. How this is calculated
Specifications
Specs last updated 2026-10-07.
- Memory
- 96 GB GDDR7
- Memory bandwidth
- 1,792 GB/s
- Memory bus
- 512-bit
- Architecture
- Blackwell GB202
- Series
- RTX PRO Blackwell
- Release year
- 2025
- Compute backends
- CUDA, VULKAN
- Usable for models
- 96 GB
Similar GPUs
Frequently asked questions
Can the NVIDIA RTX PRO 6000 Blackwell (Max-Q Edition) run local LLMs?
Yes. With 96 GB (96 GB usable by a model) it runs 127 of the catalogued models at Q4_K_M with 8K context; the largest is Devstral-2 123B, needing about 75.1 GB.
How fast is the NVIDIA RTX PRO 6000 Blackwell (Max-Q Edition) for AI inference?
It is estimated to run Llama 3.1 8B at 113–234 tok/s at Q4_K_M. Llama 3.3 70B is estimated at 21–44 tok/s. These are modelled estimates from memory bandwidth, not measurements; the methodology page shows the formula.
What LLMs can I run on 96 GB?
Among the best that fit: Devstral-2 123B, Qwen 3.5 122B-A10B, Nemotron 3 Super 120B-A12B, Mistral Small 4 119B-A6.5B, GPT-OSS 120B.