HomeCan I run it?Mistral Small 24BMistral Small 24B on a Mac mini 24GB
Yes, but it is tight. Mistral Small 24B at Q4_K_M needs about 17.7 GB, and the Mac mini M6 24GB has 18.0 GB usable at a ~4k context.
Can I run Mistral Small 24B on a Mac mini 24GB?
Mistral Small 24B at Q4_K_M needs about 17.7 GB, and the Mac mini M6 24GB has 18.0 GB usable. That figure is 24 GB of unified memory on the spec sheet, of which 18.0 GB is usable for weights and cache, at 170 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
- Q4_K_M Fits, short context only
- Memory needed
- 17.7 GB at Q4_K_M, ~4k context
- Usable unified memory
- 18.0 GB of 24 GB unified memory
- Est. tokens/sec
- 5–9 estimate
Memory at each quant
| Quant | Need vs 18.0 GB | Verdict |
|---|---|---|
| Q4_K_M | 17.7 GB | Q4Tight |
| Q8_0 | 30.3 GB | Q8Won’t fit |
| FP16 | 56.2 GB | FP16Won’t fit |
Estimated tokens per second
Estimate: 5–9 tokens/sec at Q4_K_M. This is a bandwidth-derived range, not a bench. Efficiency is a 45–80% unified-memory band from How we calculate.
Context headroom
At Q4_K_M, this machine has headroom out to about 4k tokens under our KV estimate. Longer chats need more memory for the cache. Figures assume an FP16 KV cache.
| Context | KV cache (FP16) | Total at Q4_K_M | Verdict |
|---|---|---|---|
| 4k | 0.7 GB | 17.7 GB | Tight |
| 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 gpt-oss-20b instead (15.6 GB at Q4). It is a different model, not a drop-in, but it does fit this machine.
- Q8_0 needs 30.3 GB and does not fit here. The GeForce RTX 5090 has 32.0 GB usable, enough for Q8.
- Full hardware list: Mistral-Small-3.2-24B-Instruct-2506. Specs for this machine: Mac mini M6 24GB.
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 24GB
- Qwen3-32B on a Mac mini 24GBWon’t fit
- Qwen3-30B-A3B on a Mac mini 24GBWon’t fit
- Qwen3.8-27B on a Mac mini 24GBWon’t fit
- Gemma 3 27B on a Mac mini 24GBWon’t fit
- Gemma 4 31B on a Mac mini 24GBWon’t fit
- gpt-oss-20b on a Mac mini 24GBFits
Quick answers
- Can I run Mistral Small 24B on a Mac mini 24GB?
- Yes, but it is tight. Mistral Small 24B at Q4_K_M needs about 17.7 GB, and the Mac mini M6 24GB has 18.0 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 24GB?
- Our estimate is 5–9 tokens per second at Q4_K_M. It is not a measured benchmark.
- What context length can I use?
- At Q4_K_M, our KV estimate supports up to about 4k tokens before the cache pushes the total over usable memory.