What Can I Run AI?

HomeCan I run it?Mixtral 8x22BMixtral 8x22B on a Mac mini 64GB

No. Mixtral 8x22B at Q4_K_M needs about 99.0 GB, and the Mac mini M5 Pro 64GB has 48.0 GB usable at a ~4k context.

Can I run Mixtral 8x22B on a Mac mini 64GB?

Mixtral 8x22B at Q4_K_M needs about 99.0 GB, and the Mac mini M5 Pro 64GB has 48.0 GB usable. That figure is 64 GB of unified memory on the spec sheet, of which 48.0 GB is usable for weights and cache, at 307 GB/s memory bandwidth. Mixtral 8x22B, a large Mixture-of-Experts. Total weights need a high-memory box; only a fraction is active per token. These are estimates from our formula, not measured benchmarks.

Quant that fits
None of Q4, Q8 or FP16 needs 99.0 GB
Memory needed
99.0 GB at Q4_K_M, ~4k context
Usable unified memory
48.0 GB of 64 GB unified memory
Est. tokens/sec
n/a does not fit

Mixtral-8x22B-Instruct-v0.1 · Mac mini M5 Pro 64GB · Everything this machine runs · Q4 vs Q8 vs FP16

Memory at each quant

QuantNeed vs 48.0 GBVerdict
Q4_K_M99.0 GBQ4Won’t fit
Q8_0172.8 GBQ8Won’t fit
FP16324.4 GBFP16Won’t fit

Estimated tokens per second

No speed estimate: Mixtral 8x22B does not fit in the 48.0 GB this machine can use, so we do not publish a tokens/sec figure for CPU offload.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 headroom for Mixtral 8x22B on a Mac mini 64GB at Q4_K_M
ContextKV cache (FP16)Total at Q4_K_MVerdict
4k0.9 GB99.0 GBWon’t fit
8k1.9 GB100.0 GBWon’t fit
16k3.8 GB101.9 GBWon’t fit
32k7.5 GB105.6 GBWon’t fit
64k15.0 GB113.1 GBWon’t fit
128k30.1 GB128.2 GBWon’t fit

From the model’s config. Try other sizes in the VRAM calculator or see the context length guide.

What to do instead

Other hardware for Mixtral 8x22B

Other models on a Mac mini 64GB

Quick answers

Can I run Mixtral 8x22B on a Mac mini 64GB?
No. Mixtral 8x22B at Q4_K_M needs about 99.0 GB, and the Mac mini M5 Pro 64GB has 48.0 GB usable.
How much VRAM does Mixtral 8x22B need?
About 99.0 GB at Q4_K_M, 172.8 GB at Q8_0 and 324.4 GB at FP16, estimated for a ~4k context.
How fast is Mixtral 8x22B on a Mac mini 64GB?
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.

New models, and what they need to run

One short email a week: fresh open models with their VRAM numbers, plus hardware worth watching.