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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
[NeurIPS 2025 Spotlight] OpenCUA: Open Foundations for Computer-Use Agents
| Date | Stars |
|---|---|
| 2026-07-24 | 804 |
| 2026-07-25 | 804 |
| 2026-07-28 | 806 |
| 2026-07-30 | 806 |
| 2026-08-06 | 806 |
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<h1 style=" font-family:-apple-system,BlinkMacSystemFont,'Segoe UI',Helvetica,Arial,sans-serif; font-size:48px; font-weight:700; line-height:1.25; text-align:center; margin:0 0 24px;"> OpenCUA: Open Foundations for Computer-Use Agents </h1> <p align="center">   🌐 <a href="https://opencua.xlang.ai/">Website</a>   |   📑 <a href="https://arxiv.org/abs/2508.09123">Paper</a>   |   🤗 <a href="https://huggingface.co/datasets/xlangai/AgentNet">Dataset</a>   |   🔎 <a href="https://agentnet_data_viewer.xlang.ai/">Data Viewer</a>   |   🤖 <a href="https://huggingface.co/collections/xlangai/opencua-open-foundations-for-computer-use-agents-6882014ebecdbbe46074a68d">Model</a>   |   🔧 <a href="https://agentnet-tool.xlang.ai/">Tool</a>   |   🎮 <a href="https://huggingface.co/spaces/xlangai/OpenCUA-demo">Model Demo</a>   </p> <div align="center"> <img src="assets/images/main_fig.png" width="600" alt="OpenCUA-7B Performance Scaling"> </div> <div style="max-width:900px;margin:0 auto;"> ## 📢 Updates - 2026-01-17: 🎉 **vLLM now fully supports OpenCUA-7B, OpenCUA-32B, and OpenCUA-72B!** Thanks to the [Meituan EvoCUA Team](https://github.com/meituan/EvoCUA) for their contributions to vLLM integration. See [vLLM Serve](model/README.md) for usage instructions. - 2025-12-17: You can now view AgentNet dataset trajectories online via [AgentNet Data Viewer](https://agentnet_data_viewer.xlang.ai/), or use the code in `data/vis/` to visualize your own trajectory data. See [vis/README.md](./data/vis/README.md) for usage instructions. We also summarized the metadata of AgentNet here [Metadata json](https://huggingface.co/datasets/xlangai/AgentNet/blob/main/meta_data_merged.jsonl). - 2025-11-28: VLLM support of OpenCUA is available at [[Model] Add OpenCUA-7B support #29068](https://github.com/vllm-project/vllm/pull/29068). Super grateful to [lim4349](https://github.com/lim4349) ! - 2025-10-12: <span style="font-weight:bold">[OpenCUA-7B-exl2](https://huggingface.co/sujitvasanth/OpenCUA-7B-exl2) is now live!</span> ⚡️ Thanks to [Sujit Vasanth](https://huggingface.co/sujitvasanth) for producing a quantized **exllamav2** version of OpenCUA-7B — enabling much faster inference with lower VRAM usage. - 2025-10-03: <span style="color:red; font-weight:bold">New OpenCUA model!</span>🔥 [OpenCUA-72B](https://huggingface.co/xlangai/OpenCUA-72B-preview) now ranks #1 on the [OSWorld-Verified leaderboard](https://os-world.github.io/). It also has strong grounding ability, 37.3% (SOTA) on UI-Vision and 60.8% on ScreenSpot-Pro. - 2025-08-13: We released our [paper](https://arxiv.org/abs/2508.09123) and [project page](https://opencua.xlang.ai/). Check it out! # Introduction <div style=" max-width: 880px; /* 可按需调节整体宽度 */ margin: 0 auto; /* 居中容器 */ text-align: justify; /* 关键：两端对齐 */ text-justify: inter-word; /* 优化英文对齐效果 */ line-height: 1.6;"> <b>OpenCUA</b> is a comprehensive open-source framework for scaling CUA data and foundation models, consisting of: - <b>[AgentNet](https://huggingface.co/datasets/xlangai/AgentNet)</b>: the first large-scale computer-use task dataset spanning 3 operating systems and 200+ applications and websites; - **[AgentNetTool](https://agentnet-tool.xlang.ai/)**: an annotation infrastructure that seamlessly captures human computer-use demonstrations; - <b>[AgentNetBench](https://github.com/xlang-ai/OpenCUA/tree/main/AgentNetBench)</b>: an offline evaluator that benchmarks model-predicted low-level actions against ground-truth trajectories. - **[OpenCUA Models](https://huggingface.co/collections/xlangai/opencua-open-foundations-for-computer-use-agents-6882014ebecdbbe46074a68d")**: end-to-end computer-use foundation models than can produce executable actions in the computer environments with great planning and grounding capabilities. With the help o
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matched fp:856eab62d2f871ee, topic:dataset, readme:dataset, readme:datasets
matched fp:856eab62d2f871ee, topic:foundation-models
matched fp:856eab62d2f871ee, topic:vision-language-model
matched fp:856eab62d2f871ee, topic:benchmark, readme:leaderboard