This repository hosts a conversion of Qwen2.5-Coder-3B-Instruct for use on Rockchip RK3588 single-board computers (Orange Pi 5 plus, Radxa Rock 5b+, Banana Pi M7, etc.). Conversion was performed using the RKNN-LLM toolkit

Conversion details

RKLLM-Toolkit version: v1.2.1
NPU driver: v0.9.8
Python: 3.12
Quantization: w8a8_g128
Output: single-file .rkllm artifact
Modifications: quantization (w8a8_g128), export to .rkllm format for RK3588 SBCs.
Tokenizer: not required at runtime (UI handles prompt I/O)

⚠️ Code generation disclaimer

🛑 This model may produce incorrect, insecure, or non-optimal code.

It is intended for research, educational, and prototyping purposes only.
Always review, test, and validate any generated code before using it in production.
The model does not guarantee compliance with security best practices or coding standards.
You are responsible for ensuring outputs meet your project’s requirements and legal obligations.

Intended use

On-device deployment of a coding-focused instruction model for software development assistance on SBCs.
Qwen2.5-Coder-3B-Instruct is tuned for code generation, explanation, and debugging tasks, making it suitable for private edge inference.

Limitations

Requires 4GB free memory
Quantized build (w8a8_g128) may show small quality differences vs. full-precision upstream.
Tested on a Radxa Rock 5B+; other devices may require different drivers/toolkit versions.

Quick start (RK3588)

1) Install runtime

The RKNN-LLM toolkit and instructions can be found on the specific development board's manufacturer website or from airockchip's github page.

Download and install the required packages as per the toolkit's instructions.

2) Simple Flask server deployment

The simplest way the deploy the .rkllm converted model is using an example script provided in the toolkit in this directory: rknn-llm/examples/rkllm_server_demo

bash

python3 <TOOLKIT_PATH>/rknn-llm/examples/rkllm_server_demo/flask_server.py \
  --rkllm_model_path <MODEL_PATH>/Qwen2.5-Coder-3B-Instruct_w8a8_g128_rk3588.rkllm \
  --target_platform rk3588

3) Sending a request

A basic format for message request is:

json

{
    "model":"Qwen2.5-Coder-3B",
    "messages":[{
        "role":"user",
        "content":"<YOUR_PROMPT_HERE>"}],
    "stream":false
}

Example request using curl:

bash

curl -s -X POST <SERVER_IP_ADDRESS>:8080/rkllm_chat \
    -H 'Content-Type: application/json' \
    -d '{"model":"Qwen2.5-Coder-3B","messages":[{"role":"user","content":"Explain in one sentence  what a static method is."}],"stream":false}'

The response is formated in the following way:

json

{
    "choices":[{
        "finish_reason":"stop",
        "index":0,
        "logprobs":null,
        "message":{
            "content":"<MODEL_REPLY_HERE">,
            "role":"assistant"}}],
        "created":null,
        "id":"rkllm_chat",
        "object":"rkllm_chat",
        "usage":{
            "completion_tokens":null,
            "prompt_tokens":null,
            "total_tokens":null}
}

Example response:

{"choices":[{"finish_reason":"stop","index":0,"logprobs":null,"message":{"content":"A static method belongs to the class itself rather than any instance of the class and can be called without creating an object of the class.","role":"assistant"}}],"created":null,"id":"rkllm_chat","object":"rkllm_chat","usage":{"completion_tokens":null,"prompt_tokens":null,"total_tokens":null}}

4) UI compatibility

This server exposes an OpenAI-compatible Chat Completions API.

You can connect it to any OpenAI-compatible client or UI (for example: Open WebUI)

Configure your client with the API base: http://<SERVER_IP_ADDRESS>:8080 and use the endpoint: /rkllm_chat
Make sure the model field matches the converted model’s name, for example:

json

{
 "model": "Qwen2.5-Coder-3B-Instruct",
 "messages": [{"role":"user","content":"Hello!"}],
 "stream": false
}

License

This conversion follows the license of the source model: LICENSE · Qwen/Qwen2.5-Coder-3B-Instruct at main

jamescallander/Qwen2.5-Coder-3B-Instruct_w8a8_g128_rk3588.rkllm

Qwen2.5-Coder-3B-Instruct — RKLLM build for RK3588 boards

Built with Qwen

Conversion details

⚠️ Code generation disclaimer

Intended use

Limitations

Quick start (RK3588)

1) Install runtime

2) Simple Flask server deployment

3) Sending a request

4) UI compatibility

License

jamescallander/
Qwen2.5-Coder-3B-Instruct_w8a8_g128_rk3588.rkllm