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---
license: mit
datasets:
- OpenResearcher/OpenResearcher-Dataset
base_model:
- nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-Base-BF16
---
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🤗 <a href="https://huggingface.co/collections/TIGER-Lab/openresearcher" target="_blank">HuggingFace</a> |
<img src="imgs/notion.svg" width="15px" style="display:inline;"> <a href="https://boiled-honeycup-4c7.notion.site/OpenResearcher-A-Fully-Open-Pipeline-for-Long-Horizon-Deep-Research-Trajectory-Synthesis-2f7e290627b5800cb3a0cd7e8d6ec0ea?source=copy_link" target="_blank">Blog</a> | <img src="imgs/slack.png" width="14px" style="display:inline;"> <a href="https://join.slack.com/t/openresearcher/shared_invite/zt-3p0r32cky-PqtZkVjjWIAI14~XwcRMfQ" target="_blank">Slack</a> | <img src="imgs/wechat.svg" width="14px" style="display:inline;"> <a href="https://github.com/TIGER-AI-Lab/OpenResearcher/blob/main/assets/imgs/wechat_group.jpg" target="_blank">WeChat</a>
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## OpenResearcher-30B-A3B Overview
OpenResearcher-30B-A3B is an agentic large language model designed for long-horizon deep research fine-tuned from [NVIDIA-Nemotron-3-Nano-30B-A3B-Base-BF16](https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-Base-BF16) on 96K [OpenResearcher dataset](https://huggingface.co/datasets/OpenResearcher/OpenResearcher-Dataset) with **100+** turns. The dataset is derived by distilling GPT-OSS-120B with [native browser tools](https://docs.vllm.ai/projects/recipes/en/latest/OpenAI/GPT-OSS.html#usage:~:text=Limitation%20section%20below.-,Tool%20Use,-%C2%B6). More info can be found on the dataset card at [OpenResearcher dataset](https://huggingface.co/datasets/OpenResearcher/OpenResearcher-Dataset).
The model achieves an impressive **54.8%** accuracy on [BrowseComp-Plus](https://huggingface.co/spaces/Tevatron/BrowseComp-Plus), surpassing performance of `GPT-4.1`, `Claude-Opus-4`, `Gemini-2.5-Pro`, `DeepSeek-R1` and `Tongyi-DeepResearch`.
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<img src="imgs/teaser.png" alt="OpenResearcher Teaser" width="100%" style="max-width: 850px; border-radius: 8px; box-shadow: 0 4px 10px rgba(0,0,0,0.1);">
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## Deep Research Benchmark Results
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<img src="imgs/main_table.png" alt="Deep Research Benchmark Results" width="100%">
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## Evaluate OpenResearcher-30B-A3B
We evaluate OpenResearcher-30B-A3B across a range of deep research benchmarks, including BrowseComp-Plus, BrowseComp, GAIA, xbench-DeepSearch. Please find more details in [GitHub](https://github.com/TIGER-AI-Lab/OpenResearcher?tab=readme-ov-file#-benchmark-openresearcher).
## Quick Start
We provide a [quick-start](https://github.com/TIGER-AI-Lab/OpenResearcher?tab=readme-ov-file#-quick-start) in GitHub that demonstrates how to use `OpenResearcher-30B-A3B` for deep research.
## Citation
```bibtex
@misc{li2025openresearcher,
title={OpenResearcher: A Fully Open Pipeline for Long-Horizon Deep Research Trajectory Synthesis},
author={Zhuofeng Li and Dongfu Jiang and Xueguang Ma and Haoxiang Zhang and Ping Nie and Yuyu Zhang and Kai Zou and Jianwen Xie and Yu Zhang and Wenhu Chen},
year={2025},
howpublished={\url{https://www.notion.so/OpenResearcher-A-Fully-Open-Pipeline-for-Long-Horizon-Deep-Research-Trajectory-Synthesis-2f7e290627b5800cb3a0cd7e8d6ec0ea}},
note={Notion Blog}
}
```