Run Qwen2.5 Math 1.5B Instruct in your browser
Qwen2.5 Math 1.5B Instruct is a 1.5B Alibaba Cloud model. In the browser it downloads 828 MB and needs about 1.6 GB of GPU memory.
Use Qwen2.5 Math 1.5B Instruct in the browser All models Downloads once · then works offline
- Family
- Qwen
- Published by
- Alibaba Cloud
- Parameters
- 1.5B
- Quantisation
- q4f16_1 · 4-bit
- Download
- 828 MB · 30 files
- GPU memory
- 1.6 GB
- Context window
- 4k tokens
- Reasoning
- —
- Licence
- Apache 2.0
- Base model
- Qwen/Qwen2.5-Math-1.5B-Instruct
- Good at
- Chat · Maths · Multilingual
How big is the Qwen2.5 Math 1.5B Instruct download?
828 MB for the q4f16_1 build, in 30 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 Math 1.5B Instruct?
A browser with WebGPU — recent Chrome, Edge, Firefox or Safari — and about 1.6 GB of GPU memory. The tool checks your GPU, memory and free space and tells you whether Qwen2.5 Math 1.5B Instruct fits before anything downloads.
Is anything I type sent to a server?
No. Qwen2.5 Math 1.5B 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 Math 1.5B 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 Math 1.5B 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 Math 1.5B Instruct released under?
The weights are Apache 2.0, taken from the model card of Qwen/Qwen2.5-Math-1.5B-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.
