Qwen3.8 27B VRAM requirements

VRAM by quantization

Weights plus the KV cache for 8,192 tokens in FP16 and the runtime overhead (0.5 GB plus 10%). Each row opens the calculator with that setting. What the GGUF names mean.

KV cache at long context

16 of its 64 layers use full attention and 48 are linear-attention layers with no growing cache. Each extra token of context adds 64 KB of FP16 cache per request. How the KV cache works.

Which GPUs can run Qwen3.8 27B

With 8,192 tokens of context. Several GPUs means one tensor-parallel group of 2, 4 or 8 cards.

How fast Qwen3.8 27B writes

Tokens per second for one request with 8,192 tokens of context, estimated from memory bandwidth. A dash means it does not fit on one card. Try other settings in the speed calculator.

Longest context on one GPU

How many tokens of context fit on a single card with one request and an FP16 KV cache. "Full" means the model's whole context window fits.

Model details

Parameters

27.8B (27,781,427,952)

Layers

16 of its 64 layers use full attention and 48 are linear-attention layers with no growing cache

Attention cache

4 KV heads × 256

Context length

262,144 tokens

Published weights

51.7 GB (BF16)

On Hugging Face

Qwen/Qwen3.8-27B

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