Can I Run Llama 3.3 on Mac mini (M4 Pro, 64 GB)?
Autor: Jakub Rusinowski · Ostatnia aktualizacja: 8 grudnia 2024
Yes — comfortably
Yes, comfortably — Llama 3.3 70B Instruct at Q2_K needs about 26.5 GB of the 48 GB usable on Mac mini (M4 Pro, 64 GB), leaving ~21.5 GB spare and running at ~6 tok/s (estimated), with room for about 65,536 tokens of context.
Confidence: high · Recommended quantization: Q2_K · Estimated speed: ~6 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 3.3 on Mac mini (M4 Pro, 64 GB): memory by quantization
| Quant | Memory needed | Fits 48 GB? | Max context | Est. speed | Download |
|---|---|---|---|---|---|
| F16 | 143.5 GB | ✗ No | — | — | 140 GB |
| Q8_0 | 77.9 GB | ✗ No | — | — | 74.4 GB |
| Q6_K | 60.9 GB | ✗ No | — | — | 57.4 GB |
| Q5_K_M | 53.1 GB | ✗ No | — | — | 49.6 GB |
| Q4_K_M | 45.7 GB | ✓ Yes | 8K | ~3.4 tok/s | 42.3 GB |
| Q3_K_M | 33.3 GB | ✓ Yes | 32K | ~4.7 tok/s | 29.8 GB |
| Q2_K | 26.5 GB | ✓ Yes | 64K | ~6 tok/s | 23 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.
- 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 computed from this model's published attention configuration.
FAQ
Can I run Llama 3.3 on Mac mini (M4 Pro, 64 GB)?
Yes, comfortably — Llama 3.3 70B Instruct at Q2_K needs about 26.5 GB of the 48 GB usable on Mac mini (M4 Pro, 64 GB), leaving ~21.5 GB spare and running at ~6 tok/s (estimated), with room for about 65,536 tokens of context.
Which quantization of Llama 3.3 should I use on Mac mini (M4 Pro, 64 GB)?
Q2_K — it needs about 26.5 GB of the 48 GB available, downloads as roughly 23 GB, and runs at an estimated 6 tokens/sec with up to 64K of context.
What limits Llama 3.3 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)
- Llama 4 on Mac mini (M4 Pro, 64 GB)
- Llama 4.5 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)
Llama 3.3 on GPUs
- Llama 3.3 on NVIDIA GeForce RTX 5090
- Llama 3.3 on NVIDIA GeForce RTX 5080
- Llama 3.3 on NVIDIA GeForce RTX 5070 Ti
- Llama 3.3 on NVIDIA GeForce RTX 5070
What This Model Is Good At
Model & Tools
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