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Can the Apple M2 Ultra (192 GB) run Leanstral 119B-A6B?

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

Yes, it runs well

Runs well. At Q6_K it needs about 110 GB of 144 GB usable, with an estimated speed of 45.1 tok/s.

Best quant
Q6_K
Generation speed
45.1 tok/s
Prompt processing
2,594 tok/s
First token (1K prompt)
0.4 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 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.33.0 / 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
Total88.0 / 10087 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

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

Every quantization on the Apple M2 Ultra (192 GB)

Quant Memory needed Available Speed Fit Grade · points Download
Q2_K 60.1 GB 144 GB 107 tok/s Runs well 72 ptsGreat (A) · 72 of 100 points: Model quality 23.3/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 9.6/15 All files (opens in a new tab)
Q3_K_M 70.8 GB 144 GB 84.1 tok/s Runs well 79 ptsGreat (A) · 79 of 100 points: Model quality 28.0/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 11.3/15 All files (opens in a new tab)
Q4_K_M 85.1 GB 144 GB 65.0 tok/s Runs well 85 ptsExcellent (S) · 85 of 100 points: Model quality 31.6/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 13.6/15 All files (opens in a new tab)
Q5_K_M 97.1 GB 144 GB 53.7 tok/s Runs well 87 ptsExcellent (S) · 87 of 100 points: Model quality 32.3/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 All files (opens in a new tab)
Q6_K 110 GB 144 GB 45.1 tok/s Runs well 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 All files (opens in a new tab)
Q8_0 139 GB 144 GB 33.1 tok/s Tight fit 85 ptsExcellent (S) · 85 of 100 points: Model quality 33.3/45, Memory fit 24.0/25, Speed 13.6/15, Memory use 15.0/15 All files (opens in a new tab)
F16 251 GB 144 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.