NVIDIA - workstation GPU - verified
Local LLMs that run on NVIDIA RTX PRO 6000 Blackwell Workstation Edition (96 GB)
By this directory's rule of thumb, 42 of 63 open-weight models fit in the 96 GB of VRAM on the RTX PRO 6000 Blackwell Workstation Edition. The largest by total parameters is Mistral Medium 3.5 128B (127.7B), whose smallest non-MLX download is 74.9 GB, the Q4_K_M GGUF build from unsloth/Mistral-Medium-3.5-128B-GGUF.
- Models that fit
- 42 of 63
- Memory
- 96 GB
- Memory type
- GDDR7 ECC
- Bandwidth
- 1,792 GB/s
Spec sheet
- Memory
- 96 GB
- Memory type
- GDDR7 with ECC
- Unified memory
- No
- Bandwidth
- 1,792 GB/s
NVIDIA lists 96 GB GDDR7 with error-correcting code (ECC) and 1792 GB/sec memory bandwidth.
Source: NVIDIA spec page (nvidia.com)
42 models that fit in 96 GB
Total params, largest first| Model | Total params | Smallest download | Quant | Commercial |
|---|---|---|---|---|
| Mistral Medium 3.5 128BMistral AI | 127.7B | 74.9 GB | Q4_K_MGGUF | Commercial use: Conditions |
| Devstral 2 123B Instruct 2512Mistral AI | 125B | 74.9 GB | Q4_K_MGGUF | Commercial use: Conditions |
| NVIDIA Nemotron 3.5 Super VL 120B-A12BNVIDIA | 124.5B12B active | 71.8 GB | Q4_0GGUF | Commercial use: Yes |
| Mistral Small 4 119B (2603)Mistral AI | 119.4B6.5B active | 73.8 GB | UD-Q4_K_MGGUF | Commercial use: Yes |
| gpt-oss-120bOpenAI | 116.8B5.1B active | 62.8 GB | Q4_K_MGGUF | Commercial use: Yes |
| Cohere Command A (03-2025)Cohere | 111.1B | 67.1 GB | Q4_K_MGGUF | Commercial use: No |
| GLM-4.5-AirZ.ai | 110.5B12B active | 73.0 GB | Q4_K_MGGUF | Commercial use: Yes |
| Llama 4 Scout 17B-16E InstructMeta | 108.6B17B active | 65.4 GB | Q4_K_MGGUF | Commercial use: Conditions |
| GLM-4.6VZ.ai | 107.7B | 70.6 GB | Q4_K_MGGUF | Commercial use: Yes |
| Qwen3-Coder-NextAlibaba Cloud (Qwen) | 79.7B3B active | 48.4 GB | Q4_K_MGGUF | Commercial use: Yes |
| NVIDIA Nemotron 3.5 Bolt 74B-A9BNVIDIA | 74.9B9B active | 22.0 GB | 24GB (native 2-bit)GGUF | Commercial use: Yes |
| AI21 Jamba2 MiniAI21 Labs | 51.6B12B active | 31.2 GB | Q4_K_MGGUF | Commercial use: Yes |
| Qwen3.6-35B-A3BAlibaba Cloud (Qwen) | 36B3B active | 22.1 GB | UD-Q4_K_MGGUF | Commercial use: Yes |
| Cohere Aya Expanse 32BCohere | 32.3B | 19.8 GB | Q4_K_MGGUF | Commercial use: No |
| Ai2 Olmo 3.1 32B ThinkAi2 | 32.2B | 19.5 GB | Q4_K_MGGUF | Commercial use: Yes |
| NVIDIA Nemotron 3.5 Lightning 30B-A3BNVIDIA | 31.6B3B active | 18.9 GB | Q4_0GGUF | Commercial use: Yes |
| Gemma 4 31BGoogle | 31.3B | 17.7 GB | Q4_0 (QAT)GGUF | Commercial use: Yes |
| IBM Granite 4.2 30BIBM | 29.3B | 17.7 GB | Q4_K_MGGUF | Commercial use: Yes |
| Qwen3.8-27BAlibaba Cloud (Qwen) | 27.8B | 16.5 GB | UD-Q4_K_MGGUF | Commercial use: Yes |
| Gemma 4 26B A4BGoogle | 25.8B3.8B active | 14.4 GB | Q4_0 (QAT)GGUF | Commercial use: Yes |
| Devstral Small 2 24B Instruct 2512Mistral AI | 24B | 14.3 GB | Q4_K_MGGUF | Commercial use: Yes |
| Liquid AI LFM2.5-24B-A2BLiquid AI | 24B2.5B active | 14.5 GB | Q4_K_MGGUF | Commercial use: Conditions |
| gpt-oss-20bOpenAI | 20.9B3.6B active | 11.6 GB | Q4_K_MGGUF | Commercial use: Yes |
| Phi-4-reasoning-vision-15BMicrosoft | 15.1B | 30.2 GB | BF16Official weights | Commercial use: Yes |
| Phi-4Microsoft | 14.7B | 9.1 GB | Q4_KGGUF | Commercial use: Yes |
| Phi-4-reasoning-plusMicrosoft | 14.7B | 9.1 GB | Q4_K_MGGUF | Commercial use: Yes |
| Ministral 3 14B Instruct 2512Mistral AI | 13.9B | 8.2 GB | Q4_K_MGGUF | Commercial use: Yes |
| Gemma 4 12BGoogle | 12B | 7.0 GB | Q4_0 (QAT)GGUF | Commercial use: Yes |
| Qwen3.5-9BAlibaba Cloud (Qwen) | 9.7B | 5.7 GB | Q4_K_MGGUF | Commercial use: Yes |
| Ministral 3 8B Instruct 2512Mistral AI | 8.9B | 5.2 GB | Q4_K_MGGUF | Commercial use: Yes |
| IBM Granite 4.2 8BIBM | 8.8B | 5.3 GB | Q4_K_MGGUF | Commercial use: Yes |
| Cohere Command R7B (12-2024)Cohere | 8B | 5.1 GB | Q4_K_MGGUF | Commercial use: No |
| Gemma 4 E4BGoogle | 8B | 5.0 GB | Q4_K_MGGUF | Commercial use: Yes |
| Ai2 Olmo Hybrid Instruct DPO 7BAi2 | 7.4B | 14.9 GB | BF16Official weights | Commercial use: Yes |
| Gemma 4 E2BGoogle | 5.1B | 3.1 GB | Q4_K_MGGUF | Commercial use: Yes |
| Qwen3.5-4BAlibaba Cloud (Qwen) | 4.7B | 2.7 GB | Q4_K_MGGUF | Commercial use: Yes |
| Ministral 3 3B Instruct 2512Mistral AI | 3.8B | 2.1 GB | Q4_K_MGGUF | Commercial use: Yes |
| Phi-4-mini-instructMicrosoft | 3.8B | 2.5 GB | Q4_K_MGGUF | Commercial use: Yes |
| Phi-4-mini-reasoningMicrosoft | 3.8B | 2.5 GB | Q4_K_MGGUF | Commercial use: Yes |
| Liquid AI LFM2.5-2.6BLiquid AI | 2.7B | 1.7 GB | Q4_K_MGGUF | Commercial use: Conditions |
| Qwen3.5-2BAlibaba Cloud (Qwen) | 2.3B | 1.3 GB | Q4_K_MGGUF | Commercial use: Yes |
| Qwen3.5-0.8BAlibaba Cloud (Qwen) | 0.9B | 0.5 GB | Q4_K_MGGUF | Commercial use: Yes |
The rest of the 63 need more than 96 GB. Browse every local model.
Compare all 33 GPUs and Macs by memory, bandwidth and how many models fit.
FAQ
How many local LLMs can the RTX PRO 6000 Blackwell Workstation Edition run?
42 of the 63 open-weight models in this directory fit, with 96 GB of VRAM, by this site's rule of thumb that the smallest non-MLX download is at most 85% of the memory. MLX builds do not count here: they run on Apple silicon only.
Can the RTX PRO 6000 Blackwell Workstation Edition run Mistral Medium 3.5 128B?
Yes, by this directory's rule of thumb: its smallest non-MLX download, 74.9 GB, is at most 85% of 96 GB (81.6 GB), the Q4_K_M GGUF build from unsloth/Mistral-Medium-3.5-128B-GGUF. That leaves room for the context. It is a memory check, not a speed estimate.
Can the RTX PRO 6000 Blackwell Workstation Edition run NVIDIA Nemotron 3.5 Super VL 120B-A12B?
Yes, by this directory's rule of thumb: its smallest non-MLX download, 71.8 GB, is at most 85% of 96 GB (81.6 GB), the Q4_0 GGUF build from ggml-org/NVIDIA-Nemotron-3.5-Super-VL-120B-A12B-GGUF. That leaves room for the context. It is a memory check, not a speed estimate.
Can the RTX PRO 6000 Blackwell Workstation Edition run Step 3.7 Flash?
Not by this directory's rule of thumb: its smallest non-MLX download, 111.5 GB, is more than 85% of 96 GB (81.6 GB). It needs the 256 GB tier or more: https://www.developersdigest.tech/local-models/fits/256.
Can the RTX PRO 6000 Blackwell Workstation Edition use system RAM for bigger models?
This page only counts models that fit entirely in the 96 GB of VRAM. Runtimes can offload layers to system RAM, but this directory does not list or measure that.
What memory bandwidth does the RTX PRO 6000 Blackwell Workstation Edition have?
NVIDIA states 1,792 GB/s of memory bandwidth (GDDR7 with ECC). From the spec notes: NVIDIA lists 96 GB GDDR7 with error-correcting code (ECC) and 1792 GB/sec memory bandwidth. This page does not turn bandwidth into a speed estimate.
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