text model · Mistral · macOS
Can I run Mistral Small 3.1 24B on Apple M3 Pro (18GB)?
No. Mistral Small 3.1 24B needs ~15.4 GB even at Q4_K_M, but Apple M3 Pro (18GB) only has ~12 GB usable.
Needs ~15.4 GB even at Q4_K_M, but only ~12 GB is usable.
That figure is at a 4k context and moves about ±15% as context length changes.
The gap is about 3.4 GB: Mistral Small 3.1 24B needs roughly 15.4 GB at Q4_K_M and Apple M3 Pro (18GB) leaves only about 12 GB usable for a model. The lightest tracked hardware that runs Mistral Small 3.1 24B is the Apple M4 (24GB) at 24 GB. See Mistral Small 3.1 24B on Apple M4 (24GB).
- Q4_K_M needed
- ~15.4 GB
- Usable on device
- ~12 GB
- Device memory
- 18 GB
Which quant fits
- Parameters
- 24B
- Q4_K_M size
- 13.35 GB
- Q8_0 size
- 23.33 GB
- Context
- 128k
- Ollama tag
- mistral-small3.1:24b
- Memory
- 18 GB unified
- Usable for weights
- ~12 GB
- Power draw
- ~70 W
- Best runtime
- Ollama (llama.cpp Metal backend) / MLX
What you can run instead
Run Mistral Small 3.1 24B on other hardware
FAQ
Can Apple M3 Pro (18GB) run Mistral Small 3.1 24B?
No. Mistral Small 3.1 24B needs ~15.4 GB even at Q4_K_M, but Apple M3 Pro (18GB) only has ~12 GB usable.
How much memory does Mistral Small 3.1 24B need?
Apple M3 Pro (18GB) does not have enough memory. At Q4_K_M the weights are ~13.35 GB; with KV cache and runtime overhead, budget ~15.4 GB at a 4k context.
What is the best tool to run Mistral Small 3.1 24B on macOS?
LM Studio for a simple setup; mlx-lm for the most speed. vLLM is NOT a Mac tool, it is a CUDA/Linux serving engine. Unified memory is not a fixed VRAM slice; ~70% is usable for weights.
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A live badge for your model card or README, updated as the data is. [](https://localmodel.run/can-i-run/mistral-small-3.1-24b/apple-m3-18gb) Sources
Weights are measured from GGUF files; KV cache and overhead are computed, so totals can vary ~15% with context and runtime. Any tok/s is a bandwidth estimate. See methodology.