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Can the Apple M2 Pro (32 GB) run North Mini Code 1.0 (30B-A3B)?

87 ptsExcellent (S) · 87 of 100 points: Model quality 34.2/45, Memory fit 24.0/25, Speed 14.1/15, Memory use 15.0/15

Yes, with little memory to spare

Tight fit. At Q4_K_M it needs about 21.2 GB of 21.4 GB usable, with an estimated speed of 35.2 tok/s.

Best quant
Q4_K_M
Generation speed
35.2 tok/s
Prompt processing
1,405 tok/s
First token (1K prompt)
0.7 s
Largest safe context
14K

Download North Mini Code 1.0 (30B-A3B)

Recommended for the Apple M2 Pro (32 GB): Q4_K_M. Every other quantization has its own download link in the table below.

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/North-Mini-Code-1.0-GGUF (opens in a new tab)

ollama run hf.co/unsloth/North-Mini-Code-1.0-GGUF:Q4_K_M

Original weights · Hugging Face

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

huggingface.co/CohereLabs/North-Mini-Code-1.0 (opens in a new tab)

No sign-in needed.

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.34.2 / 45
Memory fitFull marks when everything sits in GPU or unified memory; fewer when part spills to system RAM.24.0 / 25
SpeedGeneration speed against a 40 tokens/s target for LLMs, or render time against a target for image and video.14.1 / 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
Total87.3 / 10087 ptsExcellent (S) · 87 of 100 points: Model quality 34.2/45, Memory fit 24.0/25, Speed 14.1/15, 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 Pro (32 GB)

Quant Memory needed Available Speed Fit Grade · points Download
Q2_K 14.8 GB 21.4 GB 57.9 tok/s Runs well 80 ptsGreat (A) · 80 of 100 points: Model quality 25.2/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 GGUF (UD-Q2_K_XL) (opens in a new tab)
Q3_K_M 17.6 GB 21.4 GB 45.6 tok/s Runs well 85 ptsExcellent (S) · 85 of 100 points: Model quality 30.2/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 GGUF (opens in a new tab)
Q4_K_M 21.2 GB 21.4 GB 35.2 tok/s Tight fit 87 ptsExcellent (S) · 87 of 100 points: Model quality 34.2/45, Memory fit 24.0/25, Speed 14.1/15, Memory use 15.0/15 GGUF (opens in a new tab)
Q5_K_M 24.3 GB 21.4 GB 24.7 tok/s Heavy offload 65 ptsGood (B) · 65 of 100 points: Model quality 34.9/45, Memory fit 4.0/25, Speed 11.8/15, Memory use 15.0/15 GGUF (opens in a new tab)
Q6_K 27.6 GB 21.4 GB — Won't run 10 ptsWon't run (F) · 10 of 100 points: Model quality 10.7/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 GGUF (opens in a new tab)
Q8_0 34.9 GB 21.4 GB — Won't run 10 ptsWon't run (F) · 10 of 100 points: Model quality 10.8/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 GGUF (opens in a new tab)
F16 63.6 GB 21.4 GB — Won't run 10 ptsWon't run (F) · 10 of 100 points: Model quality 10.8/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 GGUF · folder (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.