Leanstral 119B-A6B on NVIDIA GB10 (128 GB)

Can the NVIDIA GB10 (128 GB) run Leanstral 119B-A6B?

83 pts

Yes, it runs well

Runs well. At Q4_K_M it needs about 82.8 GB of 115 GB usable, with an estimated speed of 25.8 tok/s.

Best quant: Q4_K_M
Generation speed: 25.8 tok/s
Prompt processing: 3,434 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 6 days ago against Hugging Face, Ollama and GitHub.

How the A 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.	12.0 / 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
Total	83.7 / 100	83 ptsGreat (A) · 83 of 100 points: Model quality 31.6/45, Memory fit 25.0/25, Speed 12.0/15, 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 GB10 (128 GB)

Quant	Memory needed	Available	Speed	Fit	Grade · points	Download
`Q2_K`	57.8 GB	115 GB	42.3 tok/s	Runs well	74 ptsGreat (A) · 74 of 100 points: Model quality 23.3/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 11.6/15	All files (opens in a new tab)
`Q3_K_M`	68.5 GB	115 GB	33.3 tok/s	Runs well	80 ptsGreat (A) · 80 of 100 points: Model quality 28.0/45, Memory fit 25.0/25, Speed 13.7/15, Memory use 13.7/15	All files (opens in a new tab)
`Q4_K_M`	82.8 GB	115 GB	25.8 tok/s	Runs well	83 ptsGreat (A) · 83 of 100 points: Model quality 31.6/45, Memory fit 25.0/25, Speed 12.0/15, Memory use 15.0/15	All files (opens in a new tab)
`Q5_K_M`	94.8 GB	115 GB	21.3 tok/s	Runs well	83 ptsGreat (A) · 83 of 100 points: Model quality 32.3/45, Memory fit 25.0/25, Speed 10.9/15, Memory use 15.0/15	All files (opens in a new tab)
`Q6_K`	108 GB	115 GB	17.9 tok/s	Tight fit	81 ptsGreat (A) · 81 of 100 points: Model quality 33.0/45, Memory fit 24.0/25, Speed 10.0/15, Memory use 15.0/15	All files (opens in a new tab)
`Q8_0`	137 GB	115 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`	249 GB	115 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

87 ptsExcellent (S) · 87 of 100 points: Model quality 33.0/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 Apple M2 Ultra (192 GB) Q6_K · 45.1 tok/s
86 ptsExcellent (S) · 86 of 100 points: Model quality 33.0/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 13.7/15 Apple M3 Ultra (256 GB) Q6_K · 46.2 tok/s
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 Apple M4 Max (128 GB) Q4_K_M · 44.4 tok/s
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 NVIDIA RTX PRO 6000 Blackwell Q4_K_M · 169 tok/s
82 ptsGreat (A) · 82 of 100 points: Model quality 31.6/45, Memory fit 25.0/25, Speed 10.8/15, Memory use 15.0/15 AMD Ryzen AI Max+ 395 (128 GB) Q4_K_M · 20.8 tok/s

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.