Can I run it?
Can I run Qwen3.8 35B A3B Distill on Apple M4 Max (40-core GPU)?
Runs
Runs fully in unified memory on your Apple M4 Max (40-core GPU) at Q6_K, 8K context, about 114–155 tok/s. Weights 27.2 GB plus 0.19 GB of KV cache — 28.0 GB of 36.0 GB usable. Up to 256K context still fits.
Best quantQ6_K
Working context8K
Max that fits256K
Speed114–155 tok/s
Weights27.2 GB
KV cache0.19 GB
Total28.0 GB
Usable36.0 GB
Qwen3.8 35B A3B Distill details · Apple M4 Max (40-core GPU) page · How this estimate is made
Run commands
llama.cpp
llama-server -hf empero-ai/Qwen3.8-35B-A3B-Distill-GGUF:Q6_K -c 8192 -ngl 40
Ollama
ollama run qwen3.8
LM Studio
lms get empero-ai/Qwen3.8-35B-A3B-Distill-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 Cyber Tiel Coder 35B A3B GGUF MTP on Apple M4 Max (40-core GPU)? — Runs, Q6_K, 114–156 tok/s
- Can I run Qwen3 Next 80B A3B Instruct on Apple M4 Max (40-core GPU)? — Tight fit, UD-Q3_K_XL, 140–191 tok/s
- Can I run Qwen2.5 72B Instruct on Apple M4 Max (40-core GPU)? — Tight fit, IQ3_M, 8.2–11 tok/s
Updated 2026-10-24. Profile on this page is the device default.