North Mini Code 1.0 (30B-A3B) on Apple M2 Pro (32 GB)
Can the Apple M2 Pro (32 GB) run North Mini Code 1.0 (30B-A3B)?
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_MOriginal 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)
How the S grade is scored
Every result gets up to 100 points from four parts. The points decide the letter grade.
| Model quality | 34.2 / 45 | |
|---|---|---|
| Memory fit | 24.0 / 25 | |
| Speed | 14.1 / 15 | |
| Memory use | 15.0 / 15 | |
| Total | 87.3 / 100 | 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 |
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
- 91 ptsExcellent (S) · 91 of 100 points: Model quality 36.0/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 Apple M4 Max (64 GB)
- 91 ptsExcellent (S) · 91 of 100 points: Model quality 36.0/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 NVIDIA RTX PRO 6000 Blackwell
- 89 ptsExcellent (S) · 89 of 100 points: Model quality 35.6/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 14.3/15 Apple M1 Max (64 GB)
- 89 ptsExcellent (S) · 89 of 100 points: Model quality 34.9/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 NVIDIA GeForce RTX 5090
- 89 ptsExcellent (S) · 89 of 100 points: Model quality 34.9/45, Memory fit 25.0/25, Speed 14.9/15, Memory use 15.0/15 Apple M4 Pro (48 GB)
- 88 ptsExcellent (S) · 88 of 100 points: Model quality 34.9/45, Memory fit 24.0/25, Speed 15.0/15, Memory use 15.0/15 AMD Radeon RX 7900 XTX
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.