Can I run it?
Can I run Qwen3.6 14B A3B FableVibes on Apple M3 Pro?
Tight fit
Tight fit fully in unified memory on your Apple M3 Pro at Q6_K, 8K context, about 31–43 tok/s. Weights 10.5 GB plus 0.19 GB of KV cache — 11.1 GB of 13.0 GB usable. Up to 64K context still fits.
Best quantQ6_K
Working context8K
Max that fits64K
Speed31–43 tok/s
Weights10.5 GB
KV cache0.19 GB
Total11.1 GB
Usable13.0 GB
Qwen3.6 14B A3B FableVibes details · Apple M3 Pro page · How this estimate is made
Run commands
llama.cpp
llama-server -hf tvall43/Qwen3.6-14B-A3B-FableVibes-GGUF:Q6_K -c 8192 -ngl 40
Ollama
ollama run qwen3.6
LM Studio
lms get tvall43/Qwen3.6-14B-A3B-FableVibes-GGUF # Then load quant Q6_K
Assumptions
- Estimate, not a benchmark. Decode speed uses a memory-bandwidth model at 55–75% of peak.
- 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%.
- Q6_K 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 M3 Pro? — Tight fit, UD-IQ3_S, 6.6–8.9 tok/s
- Can I run Qwen3.6 35B A3B on Apple M3 Pro? — Tight fit, UD-Q2_K_XL, 67–91 tok/s
- Can I run Qwen3.5 35B A3B on Apple M3 Pro? — Tight fit, UD-IQ3_XXS, 68–93 tok/s
Updated 2026-10-24. Profile on this page is the device default.