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Can the Apple M5 Max (64 GB) run Magistral Small 2506?

76 ptsGreat (A) · 76 of 100 points: Model quality 29.1/45, Memory fit 25.0/25, Speed 12.4/15, Memory use 9.7/15

Yes, it runs well

Runs well. At Q4_K_M it needs about 20.2 GB of 48.0 GB usable, with an estimated speed of 27.5 tok/s.

Best quant
Q4_K_M
Generation speed
27.5 tok/s
Prompt processing
497 tok/s
First token (1K prompt)
2.1 s
Largest safe context
40K

Download Magistral Small 2506

Recommended for the Apple M5 Max (64 GB): Q4_K_M. Every other quantization has its own download link in the table below.

Quickest · Ollama

One command downloads a ready-to-run version and starts a chat.

ollama run magistral:24b-small-2506-q4_K_M

Get Ollama at ollama.com/download (opens in a new tab) · model page (opens in a new tab)

Quantized files · GGUF

Works in LM Studio, llama.cpp, Jan and Ollama. No sign-in needed.

Download the Q4_K_M file (opens in a new tab)

huggingface.co/unsloth/Magistral-Small-2506-GGUF (opens in a new tab)

ollama run hf.co/unsloth/Magistral-Small-2506-GGUF:Q4_K_M

Original weights · Hugging Face

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

huggingface.co/mistralai/Magistral-Small-2506 (opens in a new tab)

No sign-in needed.

Links checked 7 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.29.1 / 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.12.4 / 15
Memory useRewards using the memory you have, so a bigger, better variant beats a tiny one that leaves most memory idle.9.7 / 15
Total76.2 / 10076 ptsGreat (A) · 76 of 100 points: Model quality 29.1/45, Memory fit 25.0/25, Speed 12.4/15, Memory use 9.7/15

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

Every quantization on the Apple M5 Max (64 GB)

Quant Memory needed Available Speed Fit Grade · points Download
Q2_K 15.2 GB 48.0 GB 45.2 tok/s Runs well 68 ptsGood (B) · 68 of 100 points: Model quality 21.4/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 7.3/15 GGUF (opens in a new tab)
Q3_K_M 17.3 GB 48.0 GB 35.6 tok/s Runs well 73 ptsGreat (A) · 73 of 100 points: Model quality 25.7/45, Memory fit 25.0/25, Speed 14.2/15, Memory use 8.3/15 GGUF (opens in a new tab)
Q4_K_M 20.2 GB 48.0 GB 27.5 tok/s Runs well 76 ptsGreat (A) · 76 of 100 points: Model quality 29.1/45, Memory fit 25.0/25, Speed 12.4/15, Memory use 9.7/15 GGUF (opens in a new tab)
Q5_K_M 22.5 GB 48.0 GB 22.7 tok/s Runs well 76 ptsGreat (A) · 76 of 100 points: Model quality 29.7/45, Memory fit 25.0/25, Speed 11.3/15, Memory use 10.8/15 GGUF (opens in a new tab)
Q6_K 25.1 GB 48.0 GB 19.1 tok/s Runs well 77 ptsGreat (A) · 77 of 100 points: Model quality 30.3/45, Memory fit 25.0/25, Speed 10.4/15, Memory use 12.1/15 GGUF (opens in a new tab)
Q8_0 30.8 GB 48.0 GB 14.0 tok/s Runs well 79 ptsGreat (A) · 79 of 100 points: Model quality 30.6/45, Memory fit 25.0/25, Speed 8.9/15, Memory use 14.8/15 GGUF (opens in a new tab)
F16 52.9 GB 48.0 GB 5.5 tok/s Heavy offload 55 ptsUsable (C) · 55 of 100 points: Model quality 30.6/45, Memory fit 4.0/25, Speed 5.6/15, Memory use 15.0/15 GGUF (opens in a new tab) 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.