text model · Mistral · macOS
Can I run Mistral Small 3 24B on Apple M5 Pro (48GB)?
Yes. Mistral Small 3 24B runs on Apple M5 Pro (48GB) at Q4_K_M (~16.3 GB of ~32 GB usable).
Runs at Q4_K_M using ~16.3 GB of ~32 GB usable. You have room for Q8_0 for higher quality.
That figure is at a 4k context and moves about ±15% as context length changes. Apple M5 Pro (48GB) leaves ~15.7 GB of headroom, room to step up to Q8_0 for higher quality.
- Q4_K_M needed
- ~16.3 GB
- Usable on device
- ~32 GB
- Device memory
- 48 GB
- Best quant
- Q4_K_M
Which quant fits
Run it
Pick your tool. All 3 load the same Q4_K_M weights.
ollama run mistral-small3.2:24b llama-cli -hf bartowski/mistralai_Mistral-Small-3.2-24B-Instruct-2506-GGUF:Q4_K_M lms get bartowski/mistralai_Mistral-Small-3.2-24B-Instruct-2506-GGUF - Parameters
- 24B
- Q4_K_M size
- 14.33 GB
- Q8_0 size
- 25.05 GB
- Context
- 128k
- Ollama tag
- mistral-small3.2:24b
- Memory
- 48 GB unified
- Usable for weights
- ~32 GB
- Best runtime
- MLX direct / Ollama (MLX backend)
You could also run
Run Mistral Small 3 24B on other hardware
FAQ
Can Apple M5 Pro (48GB) run Mistral Small 3 24B?
Yes. Mistral Small 3 24B runs on Apple M5 Pro (48GB) at Q4_K_M (~16.3 GB of ~32 GB usable).
How much memory does Mistral Small 3 24B need?
Apple M5 Pro (48GB) has room to spare. At Q4_K_M the weights are ~14.33 GB; with KV cache and runtime overhead, budget ~16.3 GB at a 4k context.
What is the best tool to run Mistral Small 3 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-3-24b/apple-m5-pro-48gb) 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.