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Qwen3.8 27B

Vision

QwenQwen · 27.8B · Dense

Qwen3.8 27B is a 27.8B model from Qwen with a 256K-token context. At Q4_K_M with an 8K context it needs about 17 GB; 23 GB leaves room for longer chats.

Hugging Face GGUF

Quantization options

QuantMemoryOn your hardware
Q2_K—…
Q3_K_M—…
Q4_K_M—…
Q5_K_M—…
Q6_K—…
Q8_0—…
F16—…

Memory by context length

At Q4_K_M. The context cache grows with every token the model keeps in mind.

ContextContext cacheTotal
4K0.3 GB16.8 GB
8K0.5 GB17 GB
32K2 GB18.5 GB
128K8 GB24.5 GB
256K16 GB32.5 GB

Share a measured speed

Run one of these and paste the whole output below (or just the tokens per second):

llama-bench -m model.gguf
ollama run model --verbose

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Next steps

Smaller alternatives

Models that need less memory than Qwen3.8 27B and score about as well or better.

No scored model is both smaller and about as intelligent as Qwen3.8 27B.

Can I run Qwen3.8 27B locally?

Can I run Qwen3.8 27B locally?

Yes, if your GPU or Mac has about 17 GB free for it at Q4_K_M. Open this page on that computer to see the grade for your exact hardware, then start it with llama.cpp, Ollama or LM Studio.

How much memory does Qwen3.8 27B need?

About 17 GB at Q4_K_M with an 8K context and 27.9 GB at Q8_0. Lower quantizations fit smaller cards with some loss in quality; longer contexts add to the total.