Can I Run Llama 3.2 Vision on Mac Studio (M3 Ultra, 256 GB)?

Superseded model. Llama 3.2 Vision has been superseded by Llama 4. This page is kept for reference; the newer family is a better starting point. View Llama 4 →

Written by Jakub Rusinowski · Last updated September 25, 2024

Yes — comfortably

Yes, comfortably — Llama 3.2 Vision 90B at Q6_K needs about 77 GB of the 192 GB usable on Mac Studio (M3 Ultra, 256 GB), leaving ~115 GB spare and running at ~5.9 tok/s (estimated), with room for about 65,536 tokens of context.

Confidence: high · Recommended quantization: Q6_K · Estimated speed: ~5.9 tok/s

Mac Studio (M3 Ultra, 256 GB) — what it gives a model

Usable memory for models	192 GB
Memory bandwidth	819 GB/s
Form factor	Desktop
Operating system	macOS
Memory upgradeable	No — soldered

Llama 3.2 Vision on Mac Studio (M3 Ultra, 256 GB): memory by quantization

Quant	Memory needed	Fits 192 GB?	Max context	Est. speed	Download
F16	181.8 GB	✓ Yes	32K	~2.5 tok/s	177.6 GB
Q8_0	98.5 GB	✓ Yes	64K	~4.6 tok/s	94.4 GB
Q6_K	77 GB	✓ Yes	64K	~5.9 tok/s	72.8 GB
Q5_K_M	67.1 GB	✓ Yes	64K	~6.8 tok/s	62.9 GB
Q4_K_M	57.8 GB	✓ Yes	64K	~7.9 tok/s	53.6 GB
Q3_K_M	42 GB	✓ Yes	64K	~11 tok/s	37.9 GB
Q2_K	33.3 GB	✓ Yes	64K	~13.9 tok/s	29.2 GB

Which Llama 3.2 Vision sizes fit

Variant	Needs at Q4_K_M	Fits?	Est. speed
Llama 3.2 Vision 90B	57.8 GB	✓ Fits	~7.9 tok/s
Llama 3.2 Vision 11B	8.5 GB	✓ Fits	~53.3 tok/s

What to watch out for

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 M3 Ultra 256 GB limitations

The largest single-box unified memory pool available, but at roughly half the memory bandwidth of a high-end discrete GPU — very large models load, then run slowly.
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.
256 GB unified memory at 819 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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