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Qwen3.5 4B

Vision

QwenQwen · 4.7B · Dense

Qwen3.5 4B is a 4.7B model from Qwen with a 256K-token context. At Q4_K_M with an 8K context it needs about 3.1 GB; 5 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
4K0.1 GB3 GB
8K0.3 GB3.1 GB
32K1 GB3.9 GB
128K4 GB6.9 GB
256K8 GB10.9 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 Qwen3.5 4B and score about as well or better.

No scored model is both smaller and about as intelligent as Qwen3.5 4B.

Can I run Qwen3.5 4B locally?

Can I run Qwen3.5 4B locally?

Yes, if your GPU or Mac has about 3.1 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 Qwen3.5 4B need?

About 3.1 GB at Q4_K_M with an 8K context and 4.7 GB at Q8_0. Lower quantizations fit smaller cards with some loss in quality; longer contexts add to the total.