Can I Run Bonsai 27B on Mac mini (M4 Pro, 64 GB)?
Autor: Jakub Rusinowski · Ostatnia aktualizacja: 15 lipca 2026
Yes — comfortably
Yes, comfortably — 1-bit Bonsai 27B at 1-bit (binary, ~1.125 bpw) needs about 6.3 GB of the 48 GB usable on Mac mini (M4 Pro, 64 GB), leaving ~41.7 GB spare and running at ~29.2 tok/s (estimated), with room for about 131,072 tokens of context.
Confidence: medium · Recommended quantization: 1-bit (binary, ~1.125 bpw) · Estimated speed: ~29.2 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 |
Bonsai 27B on Mac mini (M4 Pro, 64 GB): memory by quantization
| Quant | Memory needed | Fits 48 GB? | Max context | Est. speed | Download |
|---|---|---|---|---|---|
| 1-bit (binary, ~1.125 bpw) | 6.3 GB | ✓ Yes | 128K | ~29.2 tok/s | 3.8 GB |
Which Bonsai 27B sizes fit
| Variant | Needs at Q4_K_M | Fits? | Est. speed |
|---|---|---|---|
| 1-bit Bonsai 27B | 18.8 GB | ✓ Fits | ~8.5 tok/s |
| Ternary Bonsai 27B | 18.8 GB | ✓ Fits | ~8.5 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 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 Bonsai 27B on Mac mini (M4 Pro, 64 GB)?
Yes, comfortably — 1-bit Bonsai 27B at 1-bit (binary, ~1.125 bpw) needs about 6.3 GB of the 48 GB usable on Mac mini (M4 Pro, 64 GB), leaving ~41.7 GB spare and running at ~29.2 tok/s (estimated), with room for about 131,072 tokens of context.
Which quantization of Bonsai 27B should I use on Mac mini (M4 Pro, 64 GB)?
1-bit (binary, ~1.125 bpw) — it needs about 6.3 GB of the 48 GB available, downloads as roughly 3.8 GB, and runs at an estimated 29.2 tokens/sec with up to 128K of context.
What limits Bonsai 27B 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 Computers
Other Models on Mac mini (M4 Pro, 64 GB)
- Codestral on Mac mini (M4 Pro, 64 GB)
- Cogito v1 on Mac mini (M4 Pro, 64 GB)
- Command R Family on Mac mini (M4 Pro, 64 GB)
- Cosmos 3 on Mac mini (M4 Pro, 64 GB)
- DeepSeek-OCR on Mac mini (M4 Pro, 64 GB)
Bonsai 27B on GPUs
- Bonsai 27B on NVIDIA GeForce RTX 5070
- Bonsai 27B on NVIDIA GeForce RTX 5060 Ti 8GB
- Bonsai 27B on NVIDIA GeForce RTX 5060
- Bonsai 27B on NVIDIA GeForce RTX 4070 Ti
What This Model Is Good At
Model & Tools
← Can I Run It? | Bonsai 27B model page | Check your hardware