Can I Run Mistral Small 4 on MacBook Pro 16" (M4 Max, 128 GB)?
Autor: Jakub Rusinowski · Ostatnia aktualizacja: 16 marca 2026
Yes, but it is tight
Yes, but it is tight — Mistral Small 4 119B-A6.5B at Q5_K_M needs about 88 GB of the 96 GB usable on MacBook Pro 16" (M4 Max, 128 GB), leaving only ~8 GB before the runtime starts swapping. Expect ~43.2 tok/s (estimated), with room for about 16,384 tokens of context.
Confidence: low · Recommended quantization: Q5_K_M · Estimated speed: ~43.2 tok/s
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MacBook Pro 16" (M4 Max, 128 GB) — what it gives a model
| Usable memory for models | 96 GB |
| Memory bandwidth | 546 GB/s |
| Form factor | Laptop |
| Operating system | macOS |
| Memory upgradeable | No — soldered |
Mistral Small 4 on MacBook Pro 16" (M4 Max, 128 GB): memory by quantization
| Quant | Memory needed | Fits 96 GB? | Max context | Est. speed | Download |
|---|---|---|---|---|---|
| F16 | 241.7 GB | ✗ No | — | — | 238 GB |
| Q8_0 | 130.1 GB | ✗ No | — | — | 126.4 GB |
| Q6_K | 101.2 GB | ✗ No | — | — | 97.6 GB |
| Q5_K_M | 88 GB | ✓ Yes | 16K | ~43.2 tok/s | 84.3 GB |
| Q4_K_M | 75.5 GB | ✓ Yes | 64K | ~47.9 tok/s | 71.8 GB |
| Q3_K_M | 54.4 GB | ✓ Yes | 64K | ~58.7 tok/s | 50.7 GB |
| Q2_K | 42.8 GB | ✓ Yes | 128K | ~67.1 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.
MacBook Pro M4 Max 128 GB limitations
- Unified memory is soldered — the 128 GB decision is permanent and cannot be upgraded later.
- Sustained decode speed on battery is materially below the plugged-in figures quoted here.
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.
- 128 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 inferred from the parameter count because this model does not publish its full attention configuration.
FAQ
Can I run Mistral Small 4 on MacBook Pro 16" (M4 Max, 128 GB)?
Yes, but it is tight — Mistral Small 4 119B-A6.5B at Q5_K_M needs about 88 GB of the 96 GB usable on MacBook Pro 16" (M4 Max, 128 GB), leaving only ~8 GB before the runtime starts swapping. Expect ~43.2 tok/s (estimated), with room for about 16,384 tokens of context.
Which quantization of Mistral Small 4 should I use on MacBook Pro 16" (M4 Max, 128 GB)?
Q5_K_M — it needs about 88 GB of the 96 GB available, downloads as roughly 84.3 GB, and runs at an estimated 43.2 tokens/sec with up to 16K of context.
What limits Mistral Small 4 on MacBook Pro 16" (M4 Max, 128 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 MacBook Pro 16" (M4 Max, 128 GB)
- Nemotron 3 Nano Omni on MacBook Pro 16" (M4 Max, 128 GB)
- Nemotron 3 Super on MacBook Pro 16" (M4 Max, 128 GB)
- Nemotron 70B on MacBook Pro 16" (M4 Max, 128 GB)
- Nemotron Cascade 2 on MacBook Pro 16" (M4 Max, 128 GB)
- Nex-N2 on MacBook Pro 16" (M4 Max, 128 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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