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Cataloged from tencent/UI-Mate-9B
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Tencent HY Frontier
Project Page · GitHub · arXiv
UI-Mate-9B is an open-weight foundation GUI agent for long-horizon work across applications and operating systems. It observes live screenshots, reasons over the visible state, and produces structured keyboard and mouse actions for native desktop interaction.
It executes a task from a natural-language instruction and live screenshots alone, planning from what is currently on screen and re-planning as the interface changes.
UI-Mate is an agent checkpoint rather than a standalone visual-chat model. We recommend using the official prompt, response parser, and interaction harness from the UI-Mate repository.
pyautogui.See the project page for evaluation details and updates.
vLLM automatically downloads the checkpoint from Hugging Face Hub on first launch.
The default agent retains five screenshots in context. The server must therefore admit at least six images because the newest screenshot arrives before the oldest one is collapsed.
Confirm that the endpoint exposes the expected model name:
Run a complete recorded trajectory:
Or provide your own screenshot:
UI-Mate-9B is intended for research and development of screenshot-based GUI agents in controlled desktop environments.
Its behavior can be affected by application versions, screen layouts, display scaling, latency, and unexpected UI state. Benchmark performance does not guarantee reliable execution in arbitrary environments, and the model requires an external runtime to execute its predicted actions.
Computer-use agents can make mistakes, encounter prompt injection, or trigger consequential actions.
UI-Mate is released under the Apache License 2.0. Third-party components remain subject to their respective licenses. See the repository LICENSE for details.
pip install -U vllm openai pillow
vllm serve tencent/UI-Mate-9B \ --trust-remote-code \ --served-model-name UI_Mate \ --port 8000 \ --tensor-parallel-size 1 \ --gpu-memory-utilization 0.85 \ --mm-encoder-tp-mode data \ --chat-template-content-format openai \ --limit-mm-per-prompt '{"image":6,"video":0}'curl -s http://127.0.0.1:8000/v1/modelsgit clone https://github.com/Tencent/UI-Mate.gitcd UI-Mate
python examples/run_agent.py \ --base-url http://127.0.0.1:8000/v1python examples/run_agent.py \ --replay \ --base-url http://127.0.0.1:8000/v1python examples/run_agent.py \ --image /path/to/screen.png \ --instruction "Export this spreadsheet as HTML and open it in Chrome"from agents.ui_mate_agent import UIMateAgent
agent = UIMateAgent( base_url="http://127.0.0.1:8000/v1", model="UI_Mate",)
with open("screen.png", "rb") as f: response, actions = agent.predict( "Install the autoDocstring extension in VS Code.", {"screenshot": f.read()}, )
print(response)print(actions)
# Reset the interaction history before starting a new task.agent.reset()@article{uimate2026, title = {UI-Mate: Advancing Open-Weight Foundation GUI Agents with In-Context Demonstrations}, author = {Tencent HY Frontier Team}, journal = {arXiv preprint arXiv:2608.15930}, year = {2026},}