Yes — Bonsai 27B (27B) runs at 22 tok/s on M4 with 16 GB RAM using 1-bit quantization via MLX. First token latency is 0.3s. A capable open-source LLM with 27B parameters.
Want to run Bonsai 27B faster — or step up to bigger models? Find your Mac →The LLMCheck index estimates Bonsai 27B on M4 using our published methodology: Q4_K_M quantization, memory-bandwidth scaling, and cross-referenced third-party benchmarks where available. Figures are transparent estimates — own this config? Submit a real benchmark →
| Metric | Value |
|---|---|
| Tokens per second | 22 tok/s |
| Time to first token | 0.3s |
| Quantization | 1-bit |
| Minimum RAM | 16 GB |
| Recommended engine | MLX |
| Parameters | 27B |
| Benchmark date | 2026-08 |
1-bit 27B MLX M4
The recommended engine for Bonsai 27B on M4 is MLX. Install with pip and pull the model:
Alternatively, you can use Ollama for a simpler setup:
To run Bonsai 27B on M4 you need:
Bonsai 27B needs about 16 GB of unified memory. These current Apple Silicon Macs have the headroom to run it comfortably:
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See how Bonsai 27B stacks up against other models on your specific Mac hardware.
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