Can I run it?
Can I run Qwen3.5 4B on Apple M4 Max (40-core GPU)?
Runs great
Runs great fully in unified memory on your Apple M4 Max (40-core GPU) at BF16, 8K context, about 35–47 tok/s. Weights 7.85 GB plus 0.27 GB of KV cache — 8.50 GB of 36.0 GB usable. Up to 256K context still fits.
Best quantBF16
Working context8K
Max that fits256K
Speed35–47 tok/s
Weights7.85 GB
KV cache0.27 GB
Total8.50 GB
Usable36.0 GB
Qwen3.5 4B details · Apple M4 Max (40-core GPU) page · How this estimate is made
Run commands
llama.cpp
llama-server -hf unsloth/Qwen3.5-4B-GGUF:BF16 -c 8192 -ngl 32
Ollama
ollama run qwen3.5
LM Studio
lms get unsloth/Qwen3.5-4B-GGUF # Then load quant BF16
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%.
- BF16 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 Max (40-core GPU)? — Runs, UD-Q8_K_L, 11–14 tok/s
- Can I run gemma 4 12b it on Apple M4 Max (40-core GPU)? — Runs, BF16, 11–15 tok/s
- Can I run Qwen3.5 9B on Apple M4 Max (40-core GPU)? — Runs great, BF16, 17–23 tok/s
Updated 2026-10-24. Profile on this page is the device default.