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## Introduction MiroThinker is an open-source agentic model series. Designed as a research agent for complex, long-horizon problem solving, it integrates strong capabilities in task decomposition, multi-hop reasoning, retrieval-augmented generation, code execution, web browsing, and document/file processing, enabling a wide range of real-world applications. In MiroThinker-v0.2, we introduced three key improvements: - **Richer training data** from both English and Chinese sources, yielding significant gains in benchmark performance and generalization. - **Unified DPO training** with a single preference dataset across all models. - **Extended context length** from 40k to 64k for more challenging multi-turn tool-use tasks. Compared to v0.1, MiroThinker-v0.2 delivers consistent gains across benchmarks. For example, scores improved from **57.3 → 64.1** on **GAIA-Text-103** and from **17.0 → 29.4** on **BrowseComp-ZH**, reflecting substantial advancements in the model’s general research agent capabilities.

## Online Demo Welcome to try out our online demo [here](https://dr.miromind.ai/). ## Performance > [!IMPORTANT] >

> To prevent data leakage during searches, we block Hugging Face domains to ensure the model doesn't access answers through shortcuts. >

### Comparison with SOTA Research Agents

### GAIA Benchmark

## Quick Start MiroThinker-v0.2 is trained on our large-scale, high-quality trajectory and preference datasets MiroVerse-v0.2, utilizing the efficient training framework [MiroTrain](https://github.com/MiroMindAI/MiroTrain), and enhanced with tool-use capabilities through our agentic framework [MiroFlow](https://github.com/MiroMindAI/MiroFlow). To promote reproducibility and benefit the community, we decided to open-source the entire suite mentioned above. For more technical details, evaluation results, and usage tutorials, please visit our [GitHub repository](https://github.com/MiroMindAI/MiroThinker). ## License MiroThinker-v0.2 is licensed under Apache 2.0. ## Citation If you find this project useful in your research, please consider citing: ``` @article{miromind2025mirothinker, title={MiroThinker: Pushing the Performance Boundaries of Open-Source Research Agents via Model, Context, and Interactive Scaling}, author={MiroMind Team and Bai, Song and Bing, Lidong and Chen, Carson and Chen, Guanzheng and Chen, Yuntao and Chen, Zhe and Chen, Ziyi and Dai, Jifeng and Dong, Xuan and others}, journal={arXiv preprint arXiv:2511.11793}, year={2025} } ``` ## Contact Us MiroThinker is developed by the MiroMind Foundation Model Team. If you would like to leave us a message, feel free to get in touch. In addition to [GitHub](https://github.com/MiroMindAI/), [Discord](https://discord.com/invite/GPqEnkzQZd), [WeChat](https://huggingface.co/datasets/miromind-ai/MiroFlow-Benchmarks/resolve/main/assets/wechat.png), and [RedNote](https://www.xiaohongshu.com/user/profile/5e353bd80000000001000239), you can also reach us via email at service@miromind.ai.