Run Qwen2.5 Coder 0.5B Instruct in your browser
Qwen2.5 Coder 0.5B Instruct is a 0.5B Alibaba Cloud model. In the browser it downloads 265 MB and needs about 945 MB of GPU memory.
Use Qwen2.5 Coder 0.5B Instruct in the browser All models Downloads once · then works offline
- Family
- Qwen
- Published by
- Alibaba Cloud
- Parameters
- 0.5B
- Quantisation
- q4f16_1 · 4-bit
- Download
- 265 MB · 8 files
- GPU memory
- 945 MB
- Context window
- 4k tokens
- Reasoning
- —
- Licence
- Apache 2.0
- Base model
- Qwen/Qwen2.5-Coder-0.5B-Instruct
- Good at
- Chat · Code · Multilingual
How big is the Qwen2.5 Coder 0.5B Instruct download?
265 MB for the q4f16_1 build, in 8 files. It downloads once and stays in your browser cache, so every later visit starts straight away and works offline.
What does my device need to run Qwen2.5 Coder 0.5B Instruct?
A browser with WebGPU — recent Chrome, Edge, Firefox or Safari — and about 945 MB of GPU memory. The tool checks your GPU, memory and free space and tells you whether Qwen2.5 Coder 0.5B Instruct fits before anything downloads.
Is anything I type sent to a server?
No. Qwen2.5 Coder 0.5B Instruct runs on your own GPU inside the browser tab. The only network traffic is the one-time download of the model files from Hugging Face; your prompts and the answers never leave the device, and the chats are stored in this browser.
Which build of Qwen2.5 Coder 0.5B Instruct should I choose?
Start with q4f16_1 — it is the smallest download and the fastest to run. The f32 builds are larger and use more memory, but they run on GPUs without 16-bit shader support. Builds marked 1k hold a shorter conversation in exchange for less memory.
How long a conversation can Qwen2.5 Coder 0.5B Instruct hold?
Its context window is 4k tokens. Longer conversations keep working — the oldest turns are dropped with a notice when the conversation no longer fits.
What licence is Qwen2.5 Coder 0.5B Instruct released under?
The weights are Apache 2.0, taken from the model card of Qwen/Qwen2.5-Coder-0.5B-Instruct. Check the licence yourself before using it commercially.
Figures read from the WebLLM 0.2.84 catalog and the model card on 2026-09-03.
