license: apache-2.0
base_model: Qwen/Qwen3-VL-4B-Instruct
tags:
- rkllm
- rknn
- rk3588
- rockchip
- npu
- quantized
- vision-language
- multimodal
- qwen3
language:
- en
- zh
pipeline_tag: image-text-to-text
Qwen3-VL-4B-Instruct — RKLLM v1.2.3 (w8a8, RK3588)
RKLLM/RKNN conversion of Qwen/Qwen3-VL-4B-Instruct for Rockchip RK3588 NPU inference.
Converted with RKLLM Toolkit v1.2.3 (language model) and RKNN Toolkit (vision encoder). This is a multimodal vision-language model — it accepts both images and text as input.
Key Details
| Property | Value |
|---|---|
| Base Model | Qwen/Qwen3-VL-4B-Instruct |
| Toolkit Version | RKLLM Toolkit v1.2.3 / RKNN Toolkit |
| Runtime Version | RKLLM Runtime ≥ v1.2.1 + RKNN Runtime |
| Quantization | w8a8 (8-bit weights, 8-bit activations) |
| Target Platform | RK3588 |
| NPU Cores | 3 |
| Thinking Mode | ❌ Disabled |
| Model Type | Vision-Language (VLM) |
| Languages | English, Chinese (multilingual) |
Why This Model?
Qwen3-VL-4B-Instruct is Alibaba's 4B vision-language model. It handles image understanding, visual QA, document analysis, and chart reading with strong multilingual support. Running on the RK3588 NPU enables fully local, GPU-free multimodal inference.
Compared to the smaller Qwen3-VL-2B, the 4B variant offers meaningfully better image understanding and text extraction.
Hardware Tested
- Orange Pi 5 Plus — RK3588, 16GB RAM, Armbian Linux
- RKNPU driver 0.9.8
- RKLLM Runtime v1.2.3
Usage
With the RKLLM API Server (VLM mode)
mkdir -p ~/models/qwen3-vl-4b
cd ~/models/qwen3-vl-4b
git lfs install && git clone https://huggingface.co/GatekeeperZA/Qwen3-VL-4B-Instruct-RKLLM-v1.2.3 .
Use with GatekeeperZA/RKLLM-API-Server — the server loads both the .rkllm and .rknn files automatically when placed in the same directory.
File Listing
| File | Description |
|---|---|
qwen3-vl-4b-instruct_w8a8_rk3588.rkllm |
Language model weights for RK3588 NPU |
qwen3-vl-4b-vision_rk3588.rknn |
Vision encoder for RK3588 NPU |
Compatibility Notes
- Minimum runtime: RKLLM Runtime v1.2.1 + RKNN Runtime v2.x. v1.2.3 recommended.
- RKNPU driver: ≥ 0.9.6
- SoCs: RK3588 / RK3588S. Not compatible with RK3576 without reconversion.
- RAM: ~5.5GB loaded. Requires 8GB+ board (16GB recommended).
Acknowledgements
- Alibaba Qwen Team for Qwen3-VL
- Rockchip / airockchip for the RKLLM and RKNN toolkits
- Converted by GatekeeperZA