Can I run it?
Can I run Qwen3.6 14B A3B FableVibes on Apple M4?
Tight fit
Tight fit fully in unified memory on your Apple M4 at Q5_K_M, 8K context, about 28–39 tok/s. Weights 9.18 GB plus 0.19 GB of KV cache — 9.75 GB of 11.0 GB usable. Up to 32K context still fits.
Best quantQ5_K_M
Working context8K
Max that fits32K
Speed28–39 tok/s
Weights9.18 GB
KV cache0.19 GB
Total9.75 GB
Usable11.0 GB
Qwen3.6 14B A3B FableVibes details · Apple M4 page · How this estimate is made
Run commands
llama.cpp
llama-server -hf tvall43/Qwen3.6-14B-A3B-FableVibes-GGUF:Q5_K_M -c 8192 -ngl 40
Ollama
ollama run qwen3.6
LM Studio
lms get tvall43/Qwen3.6-14B-A3B-FableVibes-GGUF # Then load quant Q5_K_M
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%.
- Q5_K_M 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 M4? — Tight fit, UD-Q2_K_XL, 6.4–8.7 tok/s
- Can I run Qwen3.6 35B A3B on Apple M4? — Tight fit, UD-IQ2_XXS, 60–82 tok/s
- Can I run Qwen3.5 35B A3B on Apple M4? — Tight fit, UD-IQ2_XXS, 61–83 tok/s
Updated 2026-10-24. Profile on this page is the device default.