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Yes. Mistral Small 24B fits in fast memory on M2 Max (38c GPU) 64GB at Q8_0 (26.8 GB needed, 48.0 GB usable), about 13 tok/s (estimate).
Hardware: M2 Max (38c GPU) 64GB · Model: Mistral Small 24B
M2 Max (38c 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 M3 Max (40c GPU) 64GB have the same memory and bandwidth, so the fit numbers match; this page is M2 Max (38c GPU) 64GB. The checker leaves macOS a share of unified memory, so Ollama can use 48.0 GB. Mistral Small 24B (23.6B, Mistral) at Q8_0 is a 25 GB download and needs 26.8 GB with headroom for about 8k tokens.
| Best quant | Q8_0 |
|---|---|
| Download size | 25 GB |
| Memory needed | 26.8 GB |
| Usable fast memory | 48.0 GB |
| Fit | fits in fast memory |
| Estimated speed | ~13 tok/s (estimate) |
| Command | ollama run mistral-small:24b-instruct-2501-q8_0 |
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