Can I Run Mistral Family on MacBook Air (M4, 16 GB)?

Autor: Jakub Rusinowski · Ostatnia aktualizacja: 28 stycznia 2025

Yes, but it is tight

Yes, but it is tight — Mistral NeMo 12B at Q6_K needs about 12 GB of the 12 GB usable on MacBook Air (M4, 16 GB), leaving only ~0 GB before the runtime starts swapping. Expect ~6.1 tok/s (estimated), with room for about 8,192 tokens of context.

Confidence: medium · Recommended quantization: Q6_K · Estimated speed: ~6.1 tok/s

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MacBook Air (M4, 16 GB) — what it gives a model

Usable memory for models	12 GB
Memory bandwidth	120 GB/s
Form factor	Laptop
Operating system	macOS
Memory upgradeable	No — soldered

Mistral Family on MacBook Air (M4, 16 GB): memory by quantization

Quant	Memory needed	Fits 12 GB?	Max context	Est. speed	Download
F16	26.1 GB	✗ No	—	—	24 GB
Q8_0	14.9 GB	✗ No	—	—	12.8 GB
Q6_K	12 GB	✓ Yes	8K	~6.1 tok/s	9.8 GB
Q5_K_M	10.6 GB	✓ Yes	16K	~7 tok/s	8.5 GB
Q4_K_M	9.4 GB	✓ Yes	16K	~8.1 tok/s	7.2 GB
Q3_K_M	7.3 GB	✓ Yes	32K	~11 tok/s	5.1 GB
Q2_K	6.1 GB	✓ Yes	32K	~13.7 tok/s	3.9 GB

Superseded model. Mistral Family has been superseded by Mistral Small 4. This page is kept for reference; the newer family is a better starting point. Mistral Small 4 needs at least 75.5 GB at Q4_K_M with an 8K context, so it does not fit the MacBook Air (M4, 16 GB).

Which Mistral Family sizes fit

Variant	Needs at Q4_K_M	Fits?	Est. speed
Mistral Small 3 (24B)	17.2 GB	✗ Too large	—
Mistral NeMo 12B	9.4 GB	✓ Fits	~8.1 tok/s

What to watch out for

Only ~0 GB of headroom at Q6_K: a longer context or a second application can push this into swapping.
1 larger variant of Mistral Family does not fit and would need CPU offload or different hardware.
Memory on this machine is not upgradeable, so the configuration you buy is the ceiling for every model you will ever run on it.

MacBook Air M4 16 GB limitations

Fanless: sustained generation throttles on long runs in a way the same chip in a MacBook Pro does not.
16 GB unified memory is shared with the OS and every open app.

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.
16 GB unified memory at 120 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 computed from this model's published attention configuration.

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