[![Demo](https://img.shields.io/badge/Demo-FFB300?style=for-the-badge&logo=airplayvideo&logoColor=white)](https://dr.miromind.ai/) [![Models](https://img.shields.io/badge/Models-5EDDD2?style=for-the-badge&logo=huggingface&logoColor=ffffff&labelColor)](https://huggingface.co/collections/miromind-ai/mirothinker-v01-689301b6d0563321862d44a1) [![Data](https://img.shields.io/badge/Data-0040A1?style=for-the-badge&logo=huggingface&logoColor=ffffff&labelColor)](https://huggingface.co/datasets/miromind-ai/MiroVerse-v0.1) [![Blog](https://img.shields.io/badge/Blog-4285F4?style=for-the-badge&logo=google-chrome&logoColor=white)](https://miromind.ai/blog/miromind-research-agent) [![Github](https://img.shields.io/badge/GitHub-24292F?style=for-the-badge&logo=github&logoColor=white)](https://github.com/MiroMindAI/MiroThinker) [![Discord](https://img.shields.io/badge/Discord-5865F2?style=for-the-badge&logo=discord&logoColor=white)](https://discord.com/invite/GPqEnkzQZd) [![WeChat](https://img.shields.io/badge/WeChat-07C160?style=for-the-badge&logo=wechat&logoColor=white)](https://huggingface.co/datasets/miromind-ai/MiroFlow-Benchmarks/resolve/main/assets/wechat.png) [![RedNote](https://img.shields.io/badge/RedNote-FF2442?style=for-the-badge&logo=revoltdotchat&logoColor=white)](https://www.xiaohongshu.com/user/profile/5e353bd80000000001000239) [![Website](https://img.shields.io/badge/Website-4285F4?style=for-the-badge&logo=monster&logoColor=white)](https://miromind.ai/)

## Introduction MiroThinker is an open-source agentic model series built on top of Qwen3. Designed for deep research and 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, making it suitable for a wide range of real-world applications. We have released the MiroThinker-v0.1 series, including both SFT and DPO variants at parameter scales of 8B, 14B, and 32B. Notably, MiroThinker v0.1 achieves state-of-the-art performance among open-source models on the [GAIA benchmark](https://huggingface.co/datasets/gaia-benchmark/GAIA), a rigorous evaluation suite for advanced agentic capabilities, demonstrating its strength in long-context, decision-intensive, and real-world task scenarios. ## 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. >

### GAIA Benchmark | **Method** | Text-103
Best Pass@1 | Text-103
Pass@1 (Avg@8) | Val-165
Best Pass@1 | Val-165
Pass@1 (Avg@8) | | ----------------------------------------------------------------- | :--: | :--: | :--: | :--: | | Search-o1-7B | 17.5 | - | - | - | | R1-Searcher-7B | 20.4 | - | - | - | | WebDancer-7B | 31.0 | - | - | - | | WebSailor-7B | 37.9 | - | - | - | | CK-Pro-8B | 43.7 | - | 35.2 | - | | MiroThinker-8B-SFT-v0.1 | 44.7 | 40.1 | 34.6 | 31.8 | | + Commercial Tools | 46.6 | 42.1 | 37.6 | 33.9 | | MiroThinker-8B-DPO-v0.1 | 46.6 | 44.8 | 37.0 | 35.4 | | + Commercial Tools | 50.5 | 46.7 | 38.2 | 35.9 | | | | | | | | Search-o1-32B | 28.2 | - | - | - | | WebThinker-32B-RL | 48.5 | - | - | - | | WebDancer-QwQ-32B | 51.5 | - | - | - | | WebSailor-32B | 53.2 | - | - | - | | WebShaper-QwQ-32B | 53.3 | - | - | - | | WebShaper-72B | 60.1 | - | - | - | | MiroThinker-14B-SFT-v0.1 | 47.6 | 44.4 | 37.0 | 34.4 | | + Commercial Tools | 49.5 | 47.5 | 41.8 | 39.8 | | MiroThinker-14B-DPO-v0.1 | 48.5 | 46.6 | 42.4 | 39.2 | | + Commercial Tools | 52.4 | 48.5 | 45.5 | 42.0 | | MiroThinker-32B-SFT-v0.1 | 55.3 | 51.3 | 44.9 | 42.7 | | + Commercial Tools | 58.3 | 54.2 | 48.5 | 45.8 | | MiroThinker-32B-DPO-v0.1 | 57.3 | 54.1 | 48.5 | 45.9 | | + Commercial Tools | **60.2** | **57.9** | **50.9** | **48.9** | 1. Following the practices of WebThinker, WebAgents, and CognitiveKernel, we report the Best Pass@1, the highest score across three runs, which often reflects stronger performance, though it may exhibit some variability. To provide a more stable measure, we additionally report Pass@1 (Avg@8), which offers greater consistency at the cost of slightly lower scores. 2. For consistency with prior open-source works, we evaluate GAIA-Text-103 using the WebAgents LLM-as-judge template, and report results on GAIA-Val-165 using the official GAIA scorer script. 3. By default, we use open-source tools wherever possible, except for the code tool [E2B](https://github.com/e2b-dev/E2B) and the Google search tool [Serper](https://serper.dev/). We use [Whisper](https://huggingface.co/openai/whisper-large-v3-turbo), [Qwen2.5-VL-72B-Instruct](https://huggingface.co/Qwen/Qwen2.5-VL-72B-Instruct), and [Qwen3-235B-A22B-Thinking-2507](https://huggingface.co/Qwen/Qwen3-235B-A22B-Thinking-2507) in our implementation. The framework can be easily extended to other open-source tools of your choice. 4. Commercial tools were mainly used for multimodal capabilities and certain complex reasoning subtasks. The majority of tasks, including planning, browsing, refinement, navigation, and more, were handled by our models. ### More Benchmarks | Method | HLE
Pass@1 | Frames
Pass@1 | BrowseComp
Pass@1 | BrowseComp-ZH
Pass@1 | WebWalkerQA
Pass@1 | |-------------------------------------------------------------------|:-------------:|:----------------:|:--------------------:|:----------------------------------------------------------------:|:---------------------:| | OpenAI Deep Research | 26.6 | - | 51.5 | 42.9 | - | | Gemini Deep Research | 26.9 | - | - | - | - | | Kimi-Researcher | 26.9 | 78.8 | - | - | - | | | | | | | | | WebDancer-7B | - | - | - | - | 36.0 | | WebSailor-7B | - | - | 6.7 | 14.2 | - | | MiroThinker-8B-SFT-v0.1 | - | 58.0 | 5.5 | 9.3 | 41.3 | | MiroThinker-8B-DPO-v0.1 | - | 64.4 | 8.7 | 13.5 | 45.7 | | | | | | | | | WebThinker-32B-RL | - | - | - | - | 46.5 | | WebDancer-QwQ-32B | - | - | 3.8 | 18.0 | 47.9 | | WebSailor-32B | - | - | 10.5 | 25.5 | - | | WebShaper-32B | - | - | - | - | 51.4 | | MiroThinker-32B-SFT-v0.1 | 10.2 | 70.4 | 10.6 | 13.8 | 45.7 | | MiroThinker-32B-DPO-v0.1 | 11.8 | 71.7 | 13.0 | 17.0 | 49.3 | 1. MiroThinker’s performance was tested with [this repository](https://github.com/MiroMindAI/MiroThinker) and open-source tools; other models’ results are from their papers and official sites. 2. As [MiroVerse-v0.1](https://huggingface.co/datasets/miromind-ai/MiroVerse-v0.1) mainly contains English data, the model’s Chinese capability is limited. We plan to add more Chinese data in the next version. ## Quick Start MiroThinker-v0.1 is trained on our large-scale, high-quality trajectory and preference datasets [MiroVerse-v0.1](https://huggingface.co/datasets/miromind-ai/MiroVerse-v0.1), 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-v0.1 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 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.