Can I run it?
Can I run MiMo V2.6 Distill Qwen 9B on Apple M5 Pro?
Tight fit
Tight fit fully in unified memory on your Apple M5 Pro at BF16, 8K context, about 9.3–13 tok/s. Weights 16.7 GB plus 0.27 GB of KV cache — 17.4 GB of 18.0 GB usable.
Best quantBF16
Working context8K
Max that fits8K
Speed9.3–13 tok/sEstimate from memory bandwidth, not a benchmark. Method.
Weights16.7 GB
KV cache0.27 GB
Total17.4 GB
Usable18.0 GB
MiMo V2.6 Distill Qwen 9B details · Apple M5 Pro page · How this estimate is made
Run commands
llama.cpp
llama-server -hf bartowski/MiMo-V2.6-Distill-Qwen-9B-GGUF:BF16 -c 8192 -ngl 32
No matching name in the Ollama library snapshot.
LM Studio
lms get bartowski/MiMo-V2.6-Distill-Qwen-9B-GGUF # Then load quant BF16
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%.
- 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 M5 Pro? — Tight fit, UD-Q4_K_XL, 9.3–13 tok/s (estimate)
- Can I run gemma 4 12b it on Apple M5 Pro? — Runs, UD-Q8_K_XL, 10–14 tok/s (estimate)
- Can I run Qwen3.5 9B on Apple M5 Pro? — Tight fit, BF16, 9.3–13 tok/s (estimate)
Updated 2026-10-24. Profile on this page is the device default.