Can I Run Devstral on Mac Studio (M3 Ultra, 256 GB)?

Written by Jakub Rusinowski · Last updated August 15, 2026

Yes — comfortably

Yes, comfortably — Devstral-2 123B at Q8_0 needs about 134.4 GB of the 192 GB usable on Mac Studio (M3 Ultra, 256 GB), leaving ~57.6 GB spare and running at ~9.9 tok/s (estimated), with room for about 65,536 tokens of context.

Confidence: medium · Recommended quantization: Q8_0 · Estimated speed: ~9.9 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

Devstral on Mac Studio (M3 Ultra, 256 GB): memory by quantization

Quant	Memory needed	Fits 192 GB?	Max context	Est. speed	Download
F16	249.7 GB	✗ No	—	—	246 GB
Q8_0	134.4 GB	✓ Yes	64K	~9.9 tok/s	130.7 GB
Q6_K	104.5 GB	✓ Yes	64K	~12.6 tok/s	100.9 GB
Q5_K_M	90.9 GB	✓ Yes	64K	~14.4 tok/s	87.2 GB
Q4_K_M	77.9 GB	✓ Yes	64K	~16.7 tok/s	74.3 GB
Q3_K_M	56.1 GB	✓ Yes	64K	~22.6 tok/s	52.4 GB
Q2_K	44.1 GB	✓ Yes	64K	~28.2 tok/s	40.4 GB

Which Devstral sizes fit

Variant	Needs at Q4_K_M	Fits?	Est. speed
Devstral-2 123B	77.9 GB	✓ Fits	~16.7 tok/s
Devstral Small 24B	16.6 GB	✓ Fits	~27.2 tok/s
Devstral-2 22B	15.7 GB	✓ Fits	~29.1 tok/s

What to watch out for

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 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 inferred from the parameter count because this model does not publish its full attention configuration.

FAQ

Can I run Devstral on Mac Studio (M3 Ultra, 256 GB)?

Which quantization of Devstral should I use on Mac Studio (M3 Ultra, 256 GB)?

Q8_0 — it needs about 134.4 GB of the 192 GB available, downloads as roughly 130.7 GB, and runs at an estimated 9.9 tokens/sec with up to 64K of context.

What limits Devstral on Mac Studio (M3 Ultra, 256 GB)?

Nothing binding — the model fits with headroom and generates at a usable speed on this hardware.

Can I Run Devstral on Mac Studio (M3 Ultra, 256 GB)?

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

Devstral on Mac Studio (M3 Ultra, 256 GB): memory by quantization

Which Devstral sizes fit

What to watch out for

Mac Studio M3 Ultra 256 GB limitations

Recommended setup

How these numbers are calculated

FAQ

Can I run Devstral on Mac Studio (M3 Ultra, 256 GB)?

Which quantization of Devstral should I use on Mac Studio (M3 Ultra, 256 GB)?

What limits Devstral on Mac Studio (M3 Ultra, 256 GB)?

Which runtime should I use?

Other Computers

Other Models on Mac Studio (M3 Ultra, 256 GB)

Devstral on GPUs

What This Model Is Good At

Model & Tools