Can I Run Qwen 2.5 VL on Mac Studio (M4 Max, 64 GB)?

Superseded model. Qwen 2.5 VL has been superseded by Qwen 3. This page is kept for reference; the newer family is a better starting point. View Qwen 3 →

Written by Jakub Rusinowski · Last updated January 25, 2025

Yes, but it is tight

Yes, but it is tight — Qwen 2.5 VL 72B Instruct at Q4_K_M needs about 47.8 GB of the 48 GB usable on Mac Studio (M4 Max, 64 GB), leaving only ~0.2 GB before the runtime starts swapping. Expect ~6.4 tok/s (estimated), with room for about 8,192 tokens of context.

Confidence: medium · Recommended quantization: Q4_K_M · Estimated speed: ~6.4 tok/s

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

Qwen 2.5 VL on Mac Studio (M4 Max, 64 GB): memory by quantization

Quant	Memory needed	Fits 48 GB?	Max context	Est. speed	Download
F16	150.3 GB	✗ No	—	—	146.8 GB
Q8_0	81.5 GB	✗ No	—	—	78 GB
Q6_K	63.7 GB	✗ No	—	—	60.2 GB
Q5_K_M	55.5 GB	✗ No	—	—	52 GB
Q4_K_M	47.8 GB	✓ Yes	8K	~6.4 tok/s	44.3 GB
Q3_K_M	34.8 GB	✓ Yes	32K	~8.9 tok/s	31.3 GB
Q2_K	27.6 GB	✓ Yes	64K	~11.3 tok/s	24.1 GB

Which Qwen 2.5 VL sizes fit

Variant	Needs at Q4_K_M	Fits?	Est. speed
Qwen 2.5 VL 72B Instruct	47.8 GB	✓ Fits	~6.4 tok/s
Qwen 2.5 VL 7B Instruct	6.3 GB	✓ Fits	~48.8 tok/s

What to watch out for

Only ~0.2 GB of headroom at Q4_K_M: a longer context or a second application can push this into swapping.
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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