Can I Run Mistral Small 4 on Mac mini (M4 Pro, 64 GB)?
Written by Jakub Rusinowski · Last updated March 16, 2026
Yes
Yes — Mistral Small 4 119B-A6.5B at Q2_K needs about 42.8 GB of the 48 GB usable on Mac mini (M4 Pro, 64 GB) (~5.2 GB spare), at ~16.4 tok/s (estimated), with room for about 16,384 tokens of context.
Confidence: medium · Recommended quantization: Q2_K · Estimated speed: ~16.4 tok/s
Mac mini (M4 Pro, 64 GB) — what it gives a model
| Usable memory for models | 48 GB |
| Memory bandwidth | 273 GB/s |
| Form factor | Mini PC |
| Operating system | macOS |
| Memory upgradeable | No — soldered |
Mistral Small 4 on Mac mini (M4 Pro, 64 GB): memory by quantization
| Quant | Memory needed | Fits 48 GB? | Max context | Est. speed | Download |
|---|
| F16 | 241.7 GB | ✗ No | — | — | 238 GB |
| Q8_0 | 130.1 GB | ✗ No | — | — | 126.4 GB |
| Q6_K | 101.2 GB | ✗ No | — | — | 97.6 GB |
| Q5_K_M | 88 GB | ✗ No | — | — | 84.3 GB |
| Q4_K_M | 75.5 GB | ✗ No | — | — | 71.8 GB |
| Q3_K_M | 54.4 GB | ✗ No | — | — | 50.7 GB |
| Q2_K | 42.8 GB | ✓ Yes | 16K | ~16.4 tok/s | 39.1 GB |
What to watch out for
- Q2_K is the only quantization that fits, and it is a heavily degraded one — expect noticeably worse output than the same model at Q4_K_M. A smaller model at Q4 is usually the better trade.
- 1 larger variant of Mistral Small 4 does not fit and would need CPU offload or different hardware.
- This model does not publish its full attention configuration, so the KV-cache share of these figures is inferred from its parameter count rather than computed exactly.
- Memory on this machine is not upgradeable, so the configuration you buy is the ceiling for every model you will ever run on it.
Mac mini M4 Pro 64 GB limitations
- M4 Pro memory bandwidth is half the M4 Max's, so large models that fit will still generate roughly half as fast.
Recommended setup
Ollama or LM Studio (Metal) — MLX for the fastest Apple-native throughput
How these numbers are calculated
- Memory need = quantized weights + KV cache at 8,192 tokens (f16) + 0.8 GB runtime overhead.
- 64 GB unified memory at 273 GB/s, shared between CPU and GPU.
- macOS reserves a share of unified memory for the system, so not all of it is available to a model.
- Throughput is a memory-bandwidth roofline estimate, not a measurement. It is labelled "estimated" everywhere it appears.
- KV cache is inferred from the parameter count because this model does not publish its full attention configuration.
FAQ
Can I run Mistral Small 4 on Mac mini (M4 Pro, 64 GB)?
Yes — Mistral Small 4 119B-A6.5B at Q2_K needs about 42.8 GB of the 48 GB usable on Mac mini (M4 Pro, 64 GB) (~5.2 GB spare), at ~16.4 tok/s (estimated), with room for about 16,384 tokens of context.
Which quantization of Mistral Small 4 should I use on Mac mini (M4 Pro, 64 GB)?
Q2_K — it needs about 42.8 GB of the 48 GB available, downloads as roughly 39.1 GB, and runs at an estimated 16.4 tokens/sec with up to 16K of context.
What limits Mistral Small 4 on Mac mini (M4 Pro, 64 GB)?
Nothing binding — the model fits with headroom and generates at a usable speed on this hardware.
Which runtime should I use?
Ollama or LM Studio (Metal) — MLX for the fastest Apple-native throughput
Other Computers
Other Models on Mac mini (M4 Pro, 64 GB)
Mistral Small 4 on GPUs
What This Model Is Good At
Model & Tools
← Can I Run It? | Mistral Small 4 model page | Check your hardware