HomeCan I run it?Mistral Small 24BMistral Small 24B on a Mac mini 16GB
No. Mistral Small 24B at Q4_K_M needs about 17.7 GB, and the Mac mini M6 16GB has 12.0 GB usable at a ~4k context.
Can I run Mistral Small 24B on a Mac mini 16GB?
Mistral Small 24B at Q4_K_M needs about 17.7 GB, and the Mac mini M6 16GB has 12.0 GB usable. That figure is 16 GB of unified memory on the spec sheet, of which 12.0 GB is usable for weights and cache, at 153 GB/s memory bandwidth. Mistral’s 24B Small instruct model, a dense mid-size alternative to the 27B–32B class. These are estimates from our formula, not measured benchmarks.
- Quant that fits
- None of Q4, Q8 or FP16 needs 17.7 GB
- Memory needed
- 17.7 GB at Q4_K_M, ~4k context
- Usable unified memory
- 12.0 GB of 16 GB unified memory
- Est. tokens/sec
- n/a does not fit
Memory at each quant
| Quant | Need vs 12.0 GB | Verdict |
|---|---|---|
| Q4_K_M | 17.7 GB | Q4Won’t fit |
| Q8_0 | 30.3 GB | Q8Won’t fit |
| FP16 | 56.2 GB | FP16Won’t fit |
Estimated tokens per second
No speed estimate: Mistral Small 24B does not fit in the 12.0 GB this machine can use, so we do not publish a tokens/sec figure for CPU offload.
Context headroom
Even at a short ~4k context, the weights do not fit. Extending context would only increase the gap.
| Context | KV cache (FP16) | Total at Q4_K_M | Verdict |
|---|---|---|---|
| 4k | 0.7 GB | 17.7 GB | Won’t fit |
| 8k | 1.3 GB | 18.4 GB | Won’t fit |
| 16k | 2.7 GB | 19.8 GB | Won’t fit |
| 32k | 5.4 GB | 22.4 GB | Won’t fit |
| 64k | 10.7 GB | 27.8 GB | Won’t fit |
| 128k | 21.5 GB | 38.5 GB | Won’t fit |
What to do instead
- Run R1 Distill 14B instead (11.3 GB at Q4). It is a different model, not a drop-in, but it does fit this machine.
- To hold Mistral Small 24B at Q4, you need about 17.7 GB. The Mac mini M6 24GB has 18.0 GB usable ($1299 Apple list price, M6 12C CPU/12C GPU, 24GB/512GB (MHQM4LL/A)).
- CPU offload can load the weights anyway, but it is slow. We do not publish an offload tokens/sec figure.
- Full hardware list: Mistral-Small-3.2-24B-Instruct-2506. Specs for this machine: Mac mini M6 16GB.
Other hardware for Mistral Small 24B
- Mistral Small 24B on an RTX 3060 12GBWon’t fit
- Mistral Small 24B on an RTX 3070 TiWon’t fit
- Mistral Small 24B on an RTX 3080Won’t fit
- Mistral Small 24B on an RTX 3090Fits
- Mistral Small 24B on an RTX 4060 Ti 16GBWon’t fit
- Mistral Small 24B on an RTX 4070 Ti SuperWon’t fit
Other models on a Mac mini 16GB
- Qwen3-32B on a Mac mini 16GBWon’t fit
- Qwen3-30B-A3B on a Mac mini 16GBWon’t fit
- Qwen3.8-27B on a Mac mini 16GBWon’t fit
- Gemma 3 27B on a Mac mini 16GBWon’t fit
- Gemma 4 31B on a Mac mini 16GBWon’t fit
- gpt-oss-20b on a Mac mini 16GBWon’t fit
Quick answers
- Can I run Mistral Small 24B on a Mac mini 16GB?
- No. Mistral Small 24B at Q4_K_M needs about 17.7 GB, and the Mac mini M6 16GB has 12.0 GB usable.
- How much VRAM does Mistral Small 24B need?
- About 17.7 GB at Q4_K_M, 30.3 GB at Q8_0 and 56.2 GB at FP16, estimated for a ~4k context.
- How fast is Mistral Small 24B on a Mac mini 16GB?
- We do not estimate tokens/sec when the model does not fit. CPU offload is possible but slow.
- What context length can I use?
- The weights already do not fit, so longer context is not the limiting factor.