Can I Run Llama 4 on Mac Studio (M4 Max, 64 GB)?

Autor: Jakub Rusinowski · Ostatnia aktualizacja: 5 kwietnia 2025

Yes

Yes — Llama 4 Scout 17B at Q2_K needs about 38.2 GB of the 48 GB usable on Mac Studio (M4 Max, 64 GB) (~9.8 GB spare), at ~41 tok/s (estimated), with room for about 32,768 tokens of context.

Confidence: high · Recommended quantization: Q2_K · Estimated speed: ~41 tok/s

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Mac Studio (M4 Max, 64 GB) — what it gives a model

Usable memory for models	48 GB
Memory bandwidth	546 GB/s
Form factor	Desktop
Operating system	macOS
Memory upgradeable	No — soldered

Llama 4 on Mac Studio (M4 Max, 64 GB): memory by quantization

Quant	Memory needed	Fits 48 GB?	Max context	Est. speed	Download
F16	220.4 GB	✗ No	—	—	218 GB
Q8_0	118.2 GB	✗ No	—	—	115.8 GB
Q6_K	91.8 GB	✗ No	—	—	89.4 GB
Q5_K_M	79.7 GB	✗ No	—	—	77.3 GB
Q4_K_M	68.2 GB	✗ No	—	—	65.8 GB
Q3_K_M	48.9 GB	✗ No	—	—	46.5 GB
Q2_K	38.2 GB	✓ Yes	32K	~41 tok/s	35.8 GB

Which Llama 4 sizes fit

Variant	Needs at Q4_K_M	Fits?	Est. speed
Llama 4 Maverick 17B	243.9 GB	✗ Too large	—
Llama 4 Scout 17B	68.2 GB	✗ Too large	—

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.
2 larger variants of Llama 4 do 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.

Mac Studio M4 Max 64 GB limitations

Memory is soldered; the configuration chosen at purchase is permanent.

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 546 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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