Can I Run Mistral Small 4 on Mac Studio (M2 Ultra, 192 GB)?
Written by Jakub Rusinowski · Last updated March 16, 2026
Yes, but it is tight
Yes, but it is tight — Mistral Small 4 119B-A6.5B at Q8_0 needs about 130.1 GB of the 144 GB usable on Mac Studio (M2 Ultra, 192 GB), leaving only ~13.9 GB before the runtime starts swapping. Expect ~16.8 tok/s (estimated), with room for about 32,768 tokens of context.
Confidence: low · Recommended quantization: Q8_0 · Estimated speed: ~16.8 tok/s
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Mac Studio (M2 Ultra, 192 GB) — what it gives a model
| Usable memory for models | 144 GB |
| Memory bandwidth | 800 GB/s |
| Form factor | Desktop |
| Operating system | macOS |
| Memory upgradeable | No — soldered |
Mistral Small 4 on Mac Studio (M2 Ultra, 192 GB): memory by quantization
| Quant | Memory needed | Fits 144 GB? | Max context | Est. speed | Download |
|---|---|---|---|---|---|
| F16 | 241.7 GB | ✗ No | — | — | 238 GB |
| Q8_0 | 130.1 GB | ✓ Yes | 32K | ~16.8 tok/s | 126.4 GB |
| Q6_K | 101.2 GB | ✓ Yes | 64K | ~21.1 tok/s | 97.6 GB |
| Q5_K_M | 88 GB | ✓ Yes | 128K | ~23.9 tok/s | 84.3 GB |
| Q4_K_M | 75.5 GB | ✓ Yes | 128K | ~27.4 tok/s | 71.8 GB |
| Q3_K_M | 54.4 GB | ✓ Yes | 128K | ~36.2 tok/s | 50.7 GB |
| Q2_K | 42.8 GB | ✓ Yes | 128K | ~44 tok/s | 39.1 GB |
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 M2 Ultra 192 GB limitations
- Superseded by the M3 Ultra, which is why it is often the better used buy for large-model work.
- 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.
- 192 GB unified memory at 800 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 Mistral Small 4 on Mac Studio (M2 Ultra, 192 GB)?
Yes, but it is tight — Mistral Small 4 119B-A6.5B at Q8_0 needs about 130.1 GB of the 144 GB usable on Mac Studio (M2 Ultra, 192 GB), leaving only ~13.9 GB before the runtime starts swapping. Expect ~16.8 tok/s (estimated), with room for about 32,768 tokens of context.
Which quantization of Mistral Small 4 should I use on Mac Studio (M2 Ultra, 192 GB)?
Q8_0 — it needs about 130.1 GB of the 144 GB available, downloads as roughly 126.4 GB, and runs at an estimated 16.8 tokens/sec with up to 32K of context.
What limits Mistral Small 4 on Mac Studio (M2 Ultra, 192 GB)?
Nothing binding — the model fits with headroom and generates at a usable speed on this hardware.
Which runtime should I use?
Ollama or LM Studio (Metal) — MLX for the fastest Apple-native throughput
Other Models on Mac Studio (M2 Ultra, 192 GB)
- Nemotron 3 Nano Omni on Mac Studio (M2 Ultra, 192 GB)
- Nemotron 3 Super on Mac Studio (M2 Ultra, 192 GB)
- Nemotron 70B on Mac Studio (M2 Ultra, 192 GB)
- Nemotron Cascade 2 on Mac Studio (M2 Ultra, 192 GB)
- Nex-N2 on Mac Studio (M2 Ultra, 192 GB)
Mistral Small 4 on GPUs
- Mistral Small 4 on NVIDIA GeForce RTX 5090
- Mistral Small 4 on Apple M4 Max
- Mistral Small 4 on Apple M4
- Mistral Small 4 on Apple M3 Max
What This Model Is Good At
Model & Tools
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