How much memory does Qwen3.8 27B need?

About 19 GB at Q4_K_M with an 8K context. It runs on a Mac with 32 GB of unified memory or more.

Try other settings in the calculator

Memory by quantization and context

Total memory: weights, KV cache in F16 and about 1 GB of buffers. Under each total, the smallest Mac that can run it with the default GPU memory limit.

Quantization8K context32K context128K context
Q3_K_M15 GB24 GB Mac17 GB24 GB Mac23 GB32 GB Mac
Q4_K_M19 GB32 GB Mac20 GB32 GB Mac27 GB48 GB Mac
Q5_K_M21 GB32 GB Mac23 GB32 GB Mac29 GB48 GB Mac
Q6_K24 GB48 GB Mac26 GB48 GB Mac32 GB48 GB Mac
Q8_031 GB48 GB Mac33 GB48 GB Mac39 GB64 GB Mac
F1657 GB96 GB Mac59 GB96 GB Mac65 GB96 GB Mac

About the model

Parameters
27.78B
Type
Dense
Attention
hybrid: linear attention plus full attention
KV cache, F16
0.5 GB at 8K, 8.6 GB at 128K
On Hugging Face
Qwen/Qwen3.8-27B

Most layers use linear attention, which keeps a small fixed-size state instead of a cache. Only the full-attention layers grow with context, so long contexts are cheap.

Questions

How much memory does Qwen3.8 27B need?

About 19 GB at Q4_K_M with an 8K context: 17 GB of weights, 0.5 GB of KV cache and about 1 GB of buffers. At 32K context it needs about 20 GB.

Can Qwen3.8 27B run on a Mac?

Yes. At Q4_K_M with an 8K context it fits on a Mac with 32 GB of unified memory or more, using the default GPU memory limit of about three quarters.

How big is the Qwen3.8 27B KV cache?

About 0.5 GB at 8K tokens and 8.6 GB at 128K tokens with an F16 cache. Its attention design: hybrid: linear attention plus full attention.

Other models

Data read from Hugging Face on 2026-11-09. These are estimates; benchmarks on this site report measured memory. How the estimate works. Compare all models in the model fit chart.

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