Yes — Qwen3.8-27B (27.8B) runs at 8 tok/s on M6 with 24 GB RAM using Q4_K_M quantization via MLX. First token latency is Nones. A capable open-source LLM with 27.8B parameters.
Want to run Qwen3.8-27B faster — or step up to bigger models? Find your Mac →The LLMCheck index estimates Qwen3.8-27B on M6 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 | 8 tok/s |
| Time to first token | Nones |
| Quantization | Q4_K_M |
| Minimum RAM | 24 GB |
| Recommended engine | MLX |
| Parameters | 27.8B |
| Benchmark date | 2026-08 |
Q4_K_M 27.8B MLX M6
The recommended engine for Qwen3.8-27B on M6 is MLX. Install with pip and pull the model:
Alternatively, you can use Ollama for a simpler setup:
| Chip | Speed | First Token | Min RAM | Engine |
|---|---|---|---|---|
| M5 Ultra | 57 tok/s | Nones | 96 GB | MLX |
To run Qwen3.8-27B on M6 you need:
Qwen3.8-27B needs about 24 GB of unified memory. These current Apple Silicon Macs have the headroom to run it comfortably:
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See how Qwen3.8-27B stacks up against other models on your specific Mac hardware.
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