Can I Run Llama 4.5 on Mac mini (M4 Pro, 64 GB)?
作者： Jakub Rusinowski · 最后更新： 2026年6月26日
Yes
Yes — Llama 4.5 Scout at Q2_K needs about 39.4 GB of the 48 GB usable on Mac mini (M4 Pro, 64 GB) (~8.6 GB spare), at ~20.2 tok/s (estimated), with room for about 32,768 tokens of context.
Confidence: medium · Recommended quantization: Q2_K · Estimated speed: ~20.2 tok/s
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Mac mini (M4 Pro, 64 GB) — what it gives a model
| Usable memory for models | 48 GB |
| Memory bandwidth | 273 GB/s |
| Form factor | Mini PC |
| Operating system | macOS |
| Memory upgradeable | No — soldered |
Llama 4.5 on Mac mini (M4 Pro, 64 GB): memory by quantization
| Quant | Memory needed | Fits 48 GB? | Max context | Est. speed | Download |
|---|---|---|---|---|---|
| F16 | 221.6 GB | ✗ No | — | — | 218 GB |
| Q8_0 | 119.4 GB | ✗ No | — | — | 115.8 GB |
| Q6_K | 92.9 GB | ✗ No | — | — | 89.4 GB |
| Q5_K_M | 80.8 GB | ✗ No | — | — | 77.3 GB |
| Q4_K_M | 69.4 GB | ✗ No | — | — | 65.8 GB |
| Q3_K_M | 50 GB | ✗ No | — | — | 46.5 GB |
| Q2_K | 39.4 GB | ✓ Yes | 32K | ~20.2 tok/s | 35.8 GB |
What to watch out for
- Q2_K is the only quantization that fits, and it is a heavily degraded one — expect noticeably worse output than the same model at Q4_K_M. A smaller model at Q4 is usually the better trade.
- 1 larger variant of Llama 4.5 does not fit and would need CPU offload or different hardware.
- 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 mini M4 Pro 64 GB limitations
- M4 Pro memory bandwidth is half the M4 Max's, so large models that fit will still generate roughly half as fast.
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 273 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 Llama 4.5 on Mac mini (M4 Pro, 64 GB)?
Yes — Llama 4.5 Scout at Q2_K needs about 39.4 GB of the 48 GB usable on Mac mini (M4 Pro, 64 GB) (~8.6 GB spare), at ~20.2 tok/s (estimated), with room for about 32,768 tokens of context.
Which quantization of Llama 4.5 should I use on Mac mini (M4 Pro, 64 GB)?
Q2_K — it needs about 39.4 GB of the 48 GB available, downloads as roughly 35.8 GB, and runs at an estimated 20.2 tokens/sec with up to 32K of context.
What limits Llama 4.5 on Mac mini (M4 Pro, 64 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 mini (M4 Pro, 64 GB)
- Magistral Small on Mac mini (M4 Pro, 64 GB)
- MiniCPM-V on Mac mini (M4 Pro, 64 GB)
- Ministral on Mac mini (M4 Pro, 64 GB)
- Ministral 3 on Mac mini (M4 Pro, 64 GB)
- Mistral Family on Mac mini (M4 Pro, 64 GB)
Llama 4.5 on GPUs
- Llama 4.5 on NVIDIA GeForce RTX 5090
- Llama 4.5 on Apple M4 Max
- Llama 4.5 on Apple M4
- Llama 4.5 on Apple M3 Max
What This Model Is Good At
Model & Tools
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