Can I run it?
Can I run Qwen3.6 27B on Apple M5 Pro?
Tight fit
Tight fit fully in unified memory on your Apple M5 Pro at UD-Q4_K_XL, 8K context, about 9.3–13 tok/s. Weights 16.4 GB plus 0.57 GB of KV cache — 17.4 GB of 18.0 GB usable.
Best quantUD-Q4_K_XL
Working context8K
Max that fits8K
Speed9.3–13 tok/sEstimate from memory bandwidth, not a benchmark. Method.
Weights16.4 GB
KV cache0.57 GB
Total17.4 GB
Usable18.0 GB
Qwen3.6 27B details · Apple M5 Pro page · How this estimate is made
Run commands
llama.cpp
llama-server -hf unsloth/Qwen3.6-27B-GGUF:UD-Q4_K_XL -c 8192 -ngl 64
Ollama
ollama run qwen3.6
LM Studio
lms get unsloth/Qwen3.6-27B-GGUF # Then load quant UD-Q4_K_XL
Assumptions
- Estimate from memory bandwidth, not a benchmark. Decode speed uses 55–75% of peak bandwidth.
- KV cache is FP16. Engine overhead assumes llama.cpp (0.3 GB + 1% of the weights). Ollama is closer to 0.9 GB + 3%, LM Studio closer to 1 GB + 3%.
- UD-Q4_K_XL size is the real GGUF file size from Hugging Face.
- Unified memory uses 75% for the GPU by default, and always leaves about 5 GB for the OS.
- Speed is quoted at 8K context, not at the maximum context that still fits.
Larger models that also fit
- Can I run Qwen3.8 27B on Apple M5 Pro? — Tight fit, UD-Q4_K_XL, 9.3–13 tok/s (estimate)
- Can I run Qwen3.6 35B A3B on Apple M5 Pro? — Tight fit, UD-IQ4_XS, 23–31 tok/s (estimate)
- Can I run Qwen3.8 35B A3B Distill on Apple M5 Pro? — Tight fit, Q3_K_M, 23–31 tok/s (estimate)
Updated 2026-10-24. Profile on this page is the device default.