Instructions to use HanzoHuang/Qwen3-4B-RKLLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- RKLLM
How to use HanzoHuang/Qwen3-4B-RKLLM with RKLLM:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
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🚀 Deploy with reComputer AI Lab
Explore and deploy AI models on Rockchip RK3576 and RK3588 devices with reComputer AI Lab.
⚡ Run with one command
With Docker installed, choose your model and board in reComputer AI Lab, copy the deployment command, and run it in your device’s terminal.
Explore Models & Deployment Guides →
Qwen3-4B · RKLLM
- Max context length: 4096
Text generation on Rockchip RK3576 and RK3588, converted from Qwen/Qwen3-4B.
- Conversion toolkit: RKLLM Toolkit 1.2.3.
- Inputs / output: text → text.
- License:
apache-2.0; the upstream model card describes its terms and intended use.
Choose your files
Use the files for your board’s exact SoC. w4a16 uses 4-bit weights and 16-bit activations; w4a16_g128 adds a weight group size of 128. w8a8 uses 8-bit weights and activations. File size below is download size, not total runtime RAM.
| Board | Quantization | Size | Language model |
|---|---|---|---|
| RK3576 | w4a16 |
2.84 GiB | Qwen3-4B_RK3576_w4a16.rkllm |
| RK3576 | w4a16_g128 |
3.06 GiB | Qwen3-4B_RK3576_w4a16_g128.rkllm |
| RK3576 | w8a8 |
4.53 GiB | Qwen3-4B_RK3576_w8a8.rkllm |
| RK3588 | w8a8 |
4.51 GiB | Qwen3-4B_RK3588_w8a8.rkllm |
Run on your board
With Docker installed on a matching Rockchip board, this example starts the RK3576 w4a16_g128 model and its API on port 8001:
sudo docker run --rm -d --name rkllm \
--privileged -v /dev:/dev -p 8001:8001 \
ghcr.io/hanzo-huang/rkllm-docker/llm/qwen3-4b:rk3576-w4a16-g128
The image includes its model file. See rkllm-docker for API requests, other board variants, and configuration.
To download the files separately instead:
hf download HanzoHuang/Qwen3-4B-RKLLM \
RK3576/Qwen3-4B_RK3576_w4a16_g128.rkllm \
--local-dir ./models
These are native RKLLM/RKNN artifacts. Use a compatible RKLLM runtime and the model’s correct chat template when integrating them in another application.
Release notes
No per-variant board benchmark is published here. Quantized output may differ from the original model; check responses on your own workloads. Use the toolkit version listed above when checking runtime compatibility.
SHA-256 checksums
07b25e01a16b50c0f76c777826aea602e485395a77df4c62428cf9fa532f509e RK3576/Qwen3-4B_RK3576_w4a16.rkllm
66b8dbc941a7fc9864583082013a2d765be9839f19e98763abfd5ec2bca166a2 RK3576/Qwen3-4B_RK3576_w4a16_g128.rkllm
7f40a9c638360b1ce51dc03d2fe5005c4ded9804d13304de3c52244634e7ed26 RK3576/Qwen3-4B_RK3576_w8a8.rkllm
6f53a7b5ec8430f95a9fb6e6279e8a4744c9952d8ec59c4a7303b92ebc8b50d5 RK3588/Qwen3-4B_RK3588_w8a8.rkllm
Credits
Original model: Qwen/Qwen3-4B. Conversion tools: Rockchip RKLLM.
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