OpAgent-32B-Q4

OpAgent-32B-Q4 is the 4-bit quantized version of OpAgent-32B， optimized to run efficiently on a single 24GB GPU. OpAgent-32B is a powerful, open-source Vision-Language Model (VLM) specifically fine-tuned for autonomous web navigation. It serves as the core single-model engine within the broader OpAgent project.

Model Details

Model Description

• Base Model: Qwen3-VL-32B-Thinking
• Fine-tuning Strategy: Hierarchical Multi-Task SFT followed by Online Agentic RL with a Hybrid Reward mechanism.
• Primary Task: Autonomous web navigation and task execution.
• Input: A combination of a natural language task description and a webpage screenshot.
• Output: A JSON-formatted action (e.g., click, type, scroll) or a final answer.

Model Sources [optional]

• Repository: [https://github.com/codefuse-ai/OpAgent]

Uses

This model is designed to be used as a web agent. The primary way to run it is through a high-performance inference engine like vLLM, as demonstrated in our single-model usage guide. For a complete, interactive agent implementation, please see the code in the opagent_single_model directory of our repository.

Citation

If you use OpAgent-32B or the OAgent framework in your research, please cite our work:

@misc{opagent2026,
  author = {CodeFuse-AI Team},
  title = {OpAgent: Operator Agent for Web Navigation},
  year = {2026},
  publisher = {GitHub},
  howpublished = {\url{https://github.com/codefuse-ai/OpAgent}},
  url = {https://github.com/codefuse-ai/OpAgent}
}