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No. Mistral Small 24B does not fit on M1 Pro 16GB: Q4_K_M needs 15.8 GB and 10.7 GB is usable.
Hardware: M1 Pro 16GB · Model: Mistral Small 24B
M1 Pro 16GB has 16 GB of unified memory and 200 GB/s of memory bandwidth. M2 Pro 16GB has the same memory and bandwidth, so the fit numbers match; this page is M1 Pro 16GB. The checker leaves macOS a share of unified memory, so Ollama can use 10.7 GB. Mistral Small 24B (23.6B, Mistral) at Q4_K_M is a 14 GB download and needs 15.8 GB with headroom for about 8k tokens.
| Best quant | Q4_K_M |
|---|---|
| Download size | 14 GB |
| Memory needed | 15.8 GB |
| Usable fast memory | 10.7 GB |
| Fit | does not fit |
| Estimated speed | no estimate, it does not fit |
| Command | ollama run mistral-small:24b |
Smallest hardware that runs it: RTX 3060 8GB at Q4_K_M (partial offload (slower), 15.8 GB needed, 7.5 GB usable, about 4 tok/s (estimate)). Can a RTX 3060 8GB run Mistral Small 24B?
A smaller Mistral model that fits this hardware: Ministral 3 14B at Q4_K_M (fits in fast memory, 10.7 GB). Can a M1 Pro 16GB run Ministral 3 14B?
Open M1 Pro 16GB in the checkerEstimates, 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