---
license: apache-2.0
base_model: Qwen/Qwen2-0.5B-Instruct
pipeline_tag: text-generation
library_name: rkllm
tags:
- rkllm
- rockchip
- rk3576
- rk3588
- qwen
- qwen2
---

# Qwen2-0.5B-Instruct-RKLLM

RKLLM-converted Qwen2-0.5B-Instruct language-model artifacts for Rockchip RK3576 and RK3588 NPUs.

These hardware-specific `.rkllm` files require a compatible Rockchip RKLLM runtime. They are not Transformers checkpoints and cannot be loaded directly with Transformers, llama.cpp, or Ollama.

## Base model

- Upstream model: [Qwen/Qwen2-0.5B-Instruct](https://huggingface.co/Qwen/Qwen2-0.5B-Instruct)
- License: Apache-2.0
- Model type: LLM (text only)

## Conversion and variants

### Toolkit version

**RKLLM Toolkit: v1.3.0**

Use a file built for the exact target SoC.

| Target | Quantization | File | SHA256 |
| --- | --- | --- | --- |
| RK3576 | W4A16 (g128) | [Qwen2-0.5B-Instruct_RK3576_w4a16_g128.rkllm](RK3576/Qwen2-0.5B-Instruct_RK3576_w4a16_g128.rkllm) | `a166cdcff5d8a2e33423d01d8bac6f7a6ad1e1130fbd0bfefdb8b69082113e87` |
| RK3576 | W8A8 | [Qwen2-0.5B-Instruct_RK3576_w8a8.rkllm](RK3576/Qwen2-0.5B-Instruct_RK3576_w8a8.rkllm) | `cdccb51e23131352823af8becf9ac4acb15cb30f0f961e89d16cb0fabd003414` |
| RK3588 | W8A8 | [Qwen2-0.5B-Instruct_RK3588_w8a8.rkllm](RK3588/Qwen2-0.5B-Instruct_RK3588_w8a8.rkllm) | `24e99eeea1512d6e7f3f120f3344a510933301dfcb72bd64b24a9724ab48e1d8` |

The repository also includes `Qwen2-0.5B-Instruct_data_quant.json`, used as calibration data during conversion.

## Usage

```bash
hf download HanzoHuang/Qwen2-0.5B-Instruct-RKLLM \
  RK3576/Qwen2-0.5B-Instruct_RK3576_w4a16_g128.rkllm \
  --local-dir Qwen2-0.5B-Instruct-RKLLM
```

Use the Qwen2 Instruct chat template with the RKLLM runtime. For Docker deployment, see [Hanzo-Huang/rkllm-docker](https://github.com/Hanzo-Huang/rkllm-docker).

## Limitations

These are target-specific converted artifacts. Validate quality and runtime compatibility on your Rockchip device.

## Acknowledgements

Thanks to the Qwen Team, Rockchip, and the RKLLM community.