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HomeCan I run it?Qwen3.8-27BQwen3.8-27B on a Mac mini 24GB

No. Qwen3.8-27B at Q4_K_M needs about 20.4 GB, and the Mac mini M6 24GB has 18.0 GB usable at a ~4k context.

Can I run Qwen3.8-27B on a Mac mini 24GB?

Qwen3.8-27B at Q4_K_M needs about 20.4 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. Alibaba’s denser Qwen3.8 27B, a newer mid-size chat model in the same memory class as Gemma 3 27B. These are estimates from our formula, not measured benchmarks.

Quant that fits
None of Q4, Q8 or FP16 needs 20.4 GB
Memory needed
20.4 GB at Q4_K_M, ~4k context
Usable unified memory
18.0 GB of 24 GB unified memory
Est. tokens/sec
n/a does not fit

Qwen3.8-27B · Mac mini M6 24GB · Everything this machine runs · Q4 vs Q8 vs FP16

Memory at each quant

QuantNeed vs 18.0 GBVerdict
Q4_K_M20.4 GBQ4Won’t fit
Q8_034.9 GBQ8Won’t fit
FP1664.9 GBFP16Won’t fit

Estimated tokens per second

No speed estimate: Qwen3.8-27B does not fit in the 18.0 GB this machine can use, so we do not publish a tokens/sec figure for CPU offload.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 Qwen3.8-27B on a Mac mini 24GB at Q4_K_M
ContextKV cache (FP16)Total at Q4_K_MVerdict
4k0.3 GB20.4 GBWon’t fit
8k0.5 GB20.6 GBWon’t fit
16k1.1 GB21.2 GBWon’t fit
32k2.1 GB22.2 GBWon’t fit
64k4.3 GB24.4 GBWon’t fit
128k8.6 GB28.7 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 Qwen3.8-27B

Other models on a Mac mini 24GB

Quick answers

Can I run Qwen3.8-27B on a Mac mini 24GB?
No. Qwen3.8-27B at Q4_K_M needs about 20.4 GB, and the Mac mini M6 24GB has 18.0 GB usable.
How much VRAM does Qwen3.8-27B need?
About 20.4 GB at Q4_K_M, 34.9 GB at Q8_0 and 64.9 GB at FP16, estimated for a ~4k context.
How fast is Qwen3.8-27B on a Mac mini 24GB?
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.