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Yes. Mixtral 8x7B (MoE) fits in fast memory on M3 Max (40c GPU) 64GB at Q5_K_M (34.8 GB needed, 48.0 GB usable), about 18 tok/s (estimate).
Hardware: M3 Max (40c GPU) 64GB · Model: Mixtral 8x7B (MoE)
M3 Max (40c GPU) 64GB has 64 GB of unified memory and 400 GB/s of memory bandwidth. M1 Max (32c GPU) 64GB and M2 Max (30c GPU) 64GB and M2 Max (38c GPU) 64GB have the same memory and bandwidth, so the fit numbers match; this page is M3 Max (40c GPU) 64GB. The checker leaves macOS a share of unified memory, so Ollama can use 48.0 GB. Mixtral 8x7B (MoE) (46.7B, 12.9B active, Mistral) at Q5_K_M is a 33 GB download and needs 34.8 GB with headroom for about 8k tokens.
| Best quant | Q5_K_M |
|---|---|
| Download size | 33 GB |
| Memory needed | 34.8 GB |
| Usable fast memory | 48.0 GB |
| Fit | fits in fast memory |
| Estimated speed | ~18 tok/s (estimate) |
| Command | ollama run mixtral:8x7b-instruct-v0.1-q5_K_M |
Estimates, not benchmarks. Model sizes are ollama.com download sizes; memory needed adds headroom for ~8k tokens of context; speeds are rough figures from memory bandwidth. Data updated 2026-10-23.
A project by OnDevice Labs · llms.txt