Instructions to use HanzoHuang/Qwen3.5-2B-RKLLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- RKLLM
How to use HanzoHuang/Qwen3.5-2B-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
Download README.md from HanzoHuang/Qwen3.5-2B-RKLLM: direct link, hf CLI and curl.
- Browser
- Download file 3.58 kB
-
https://huggingface.co/HanzoHuang/Qwen3.5-2B-RKLLM/resolve/main/README.md
- Command line
-
hf download hf://HanzoHuang/Qwen3.5-2B-RKLLM/README.md
-
curl -L -o README.md https://huggingface.co/HanzoHuang/Qwen3.5-2B-RKLLM/resolve/main/README.md
license: apache-2.0
base_model: Qwen/Qwen3.5-2B
pipeline_tag: image-text-to-text
library_name: rkllm
tags:
- rkllm
- rockchip
- rk3576
- rk3588
- qwen
- qwen3.5
- multimodal
Qwen3.5-2B · RKLLM
- Max context length: 4096
Image and text on Rockchip RK3576 and RK3588, converted from Qwen/Qwen3.5-2B.
- Conversion toolkit: RKLLM Toolkit 1.3.0.
- Inputs / output: text or image + 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_g128 |
2.21 GiB | Qwen3.5-2B_RK3576_w4a16_g128.rkllm |
| RK3576 | w8a8 |
2.76 GiB | Qwen3.5-2B_RK3576_w8a8.rkllm |
| RK3588 | w8a8 |
2.74 GiB | Qwen3.5-2B_RK3588_w8a8.rkllm |
For image input, also download the vision encoder for the same SoC. Keep the language model and vision encoder from this release together.
| Board | Size | Vision encoder |
|---|---|---|
| RK3576 | 0.67 GiB | Qwen3.5-2B_vision_RK3576.rknn |
| RK3588 | 0.65 GiB | Qwen3.5-2B_vision_RK3588.rknn |
ONNX files are export intermediates; they are not needed to run these RKNN/RKLLM models.
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/vlm/qwen3.5-2b:rk3576-w4a16-g128
The image includes its model files. See rkllm-docker for API requests, image inputs, other board variants, and configuration.
To download the files separately instead:
hf download HanzoHuang/Qwen3.5-2B-RKLLM \
RK3576/Qwen3.5-2B_RK3576_w4a16_g128.rkllm \
RK3576/Qwen3.5-2B_vision_RK3576.rknn \
--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
76f40bbbc559615767e49a9408d28a1afc16c3a12aa3764a11e13f52acd868e9 RK3576/Qwen3.5-2B_RK3576_w4a16_g128.rkllm
95f4c10bf5d8880a4697c9c4e06508559930a9e379c4b154012daa94018ce8ae RK3576/Qwen3.5-2B_RK3576_w8a8.rkllm
946daf4377bbf5913d8d5226180991b8e6b4a3068d8b5959bdc81a9492311a09 RK3588/Qwen3.5-2B_RK3588_w8a8.rkllm
c752c9ddec5ad0415cff7d5b2cd645c00273d7f75cfb034182126309911c051b RK3576/Qwen3.5-2B_vision_RK3576.rknn
9077bfd3f4a0a3846af7fd1609175aaaba07858d00acdc31459ae9f2dc66716a RK3588/Qwen3.5-2B_vision_RK3588.rknn
Credits
Original model: Qwen/Qwen3.5-2B. Conversion tools: Rockchip RKLLM.