Can I run it?
Can I run Swift Qwen3.8 27B on Apple M5 Max (40-core GPU)?
Runs
Runs fully in unified memory on your Apple M5 Max (40-core GPU) at Q8_0, 8K context, about 11–16 tok/s. Weights 27.1 GB plus 0.57 GB of KV cache — 28.3 GB of 36.0 GB usable. Up to 64K context still fits.
Best quantQ8_0
Working context8K
Max that fits64K
Speed11–16 tok/sEstimate from memory bandwidth, not a benchmark. Method.
Weights27.1 GB
KV cache0.57 GB
Total28.3 GB
Usable36.0 GB
Swift Qwen3.8 27B details · Apple M5 Max (40-core GPU) page · How this estimate is made
Run commands
llama.cpp
llama-server -hf ukisai/Swift-Qwen3.8-27B-GGUF:Q8_0 -c 8192 -ngl 64
No matching name in the Ollama library snapshot.
LM Studio
lms get ukisai/Swift-Qwen3.8-27B-GGUF # Then load quant Q8_0
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%.
- Q8_0 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 M5 Max (40-core GPU)? — Runs, UD-Q8_K_L, 12–16 tok/s (estimate)
- Can I run Qwen3.6 35B A3B on Apple M5 Max (40-core GPU)? — Tight fit, Q8_0, 22–30 tok/s (estimate)
- Can I run Qwen3.8 35B A3B Distill on Apple M5 Max (40-core GPU)? — Runs, Q6_K, 28–38 tok/s (estimate)
Updated 2026-10-24. Profile on this page is the device default.