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Can the NVIDIA RTX PRO 6000 Blackwell run Leanstral 119B-A6B?

86 ptsExcellent (S) · 86 of 100 points: Model quality 31.6/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15

Yes, it runs well

Runs well. At Q4_K_M it needs about 78.4 GB of 96.0 GB usable, with an estimated speed of 169 tok/s.

Best quant
Q4_K_M
Generation speed
169 tok/s
Prompt processing
13,846 tok/s
First token (1K prompt)
0.3 s
Largest safe context
256K

Download Leanstral 119B-A6B

Original weights · Hugging Face

Full-precision files from Mistral AI, for fine-tuning, vLLM, Transformers.

huggingface.co/mistralai/Leanstral-2603 (opens in a new tab)

No sign-in needed.

Links checked 1 week ago against Hugging Face, Ollama and GitHub.

How the S grade is scored

Every result gets up to 100 points from four parts. The points decide the letter grade.

Model qualityEditorial quality tier of the model, scaled by the quantization or precision used.31.6 / 45
Memory fitFull marks when everything sits in GPU or unified memory; fewer when part spills to system RAM.25.0 / 25
SpeedGeneration speed against a 40 tokens/s target for LLMs, or render time against a target for image and video.15.0 / 15
Memory useRewards using the memory you have, so a bigger, better variant beats a tiny one that leaves most memory idle.15.0 / 15
Total86.6 / 10086 ptsExcellent (S) · 86 of 100 points: Model quality 31.6/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15

Grade scale: S 85+ · A 72+ · B 58+ · C 42+ · D 25+ · F under 25 points.

Every quantization on the NVIDIA RTX PRO 6000 Blackwell

Quant Memory needed Available Speed Fit Grade · points Download
Q2_K 53.3 GB 96.0 GB 278 tok/s Runs well 76 ptsGreat (A) · 76 of 100 points: Model quality 23.3/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 12.8/15 All files (opens in a new tab)
Q3_K_M 64.1 GB 96.0 GB 219 tok/s Runs well 82 ptsGreat (A) · 82 of 100 points: Model quality 28.0/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 All files (opens in a new tab)
Q4_K_M 78.4 GB 96.0 GB 169 tok/s Runs well 86 ptsExcellent (S) · 86 of 100 points: Model quality 31.6/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 All files (opens in a new tab)
Q5_K_M 90.4 GB 96.0 GB 140 tok/s Tight fit 86 ptsExcellent (S) · 86 of 100 points: Model quality 32.3/45, Memory fit 24.0/25, Speed 15.0/15, Memory use 15.0/15 All files (opens in a new tab)
Q6_K 103 GB 96.0 GB 39.4 tok/s Runs with offload 72 ptsGreat (A) · 72 of 100 points: Model quality 33.0/45, Memory fit 10.0/25, Speed 14.9/15, Memory use 15.0/15 All files (opens in a new tab)
Q8_0 132 GB 96.0 GB — Won't run 9 ptsWon't run (F) · 9 of 100 points: Model quality 10.0/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 All files (opens in a new tab)
F16 244 GB 96.0 GB — Won't run 9 ptsWon't run (F) · 9 of 100 points: Model quality 10.0/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 Original weights (opens in a new tab)

Memory figures assume 8K of context. Longer conversations or documents grow the KV cache.

Other hardware that runs it

Estimates come from published hardware specs and our open formulas, not from running the model on your machine. Real speed varies with runtime, drivers and settings. Numbers marked “Measured” come from a linked benchmark.