Can I run it?
Can I run Qwen3.5 9B on Apple M3 Pro?
Tight fit
Tight fit fully in unified memory on your Apple M3 Pro at UD-Q8_K_XL, 4K context, about 6.3–8.6 tok/s. Weights 12.1 GB plus 0.15 GB of KV cache — 12.7 GB of 13.0 GB usable.
Best quantUD-Q8_K_XL
Working context4K
Max that fits4K
Speed6.3–8.6 tok/sEstimate from memory bandwidth, not a benchmark. Method.
Weights12.1 GB
KV cache0.15 GB
Total12.7 GB
Usable13.0 GB
Qwen3.5 9B details · Apple M3 Pro page · How this estimate is made
Run commands
llama.cpp
llama-server -hf unsloth/Qwen3.5-9B-GGUF:UD-Q8_K_XL -c 4096 -ngl 32
Ollama
ollama run qwen3.5
LM Studio
lms get unsloth/Qwen3.5-9B-GGUF # Then load quant UD-Q8_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-Q8_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 4K context, not at the maximum context that still fits.
Larger models that also fit
- Can I run Qwen3.8 27B on Apple M3 Pro? — Tight fit, UD-IQ3_S, 6.6–8.9 tok/s (estimate)
- Can I run gemma 4 12b it on Apple M3 Pro? — Tight fit, UD-Q6_K_XL, 5.9–8.1 tok/s (estimate)
- Can I run Qwen3.6 35B A3B on Apple M3 Pro? — Tight fit, UD-Q2_K_XL, 16–22 tok/s (estimate)
Updated 2026-10-24. Profile on this page is the device default.