---
license: mit
datasets:
- OpenResearcher/OpenResearcher-Dataset
base_model:
- nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-Base-BF16
---
<div style="display: flex; align-items: center; justify-content: center; gap: 8px;">
  <img src="https://raw.githubusercontent.com/TIGER-AI-Lab/OpenResearcher/main/assets/imgs/or-logo1.png" style="height: 84px; width: auto;">
  <img src="https://raw.githubusercontent.com/TIGER-AI-Lab/OpenResearcher/refs/heads/main/assets/imgs/openresearcher-title.svg" style="height: 84px; width: auto;">
</div>

<div align="center">
    <a href="https://x.com/DongfuJiang/status/2020946549422031040"><img src="https://img.shields.io/badge/Twitter-000000?style=for-the-badge&logo=X&logoColor=white" alt="Blog"></a>
  <a href="https://boiled-honeycup-4c7.notion.site/OpenResearcher-A-Fully-Open-Pipeline-for-Long-Horizon-Deep-Research-Trajectory-Synthesis-2f7e290627b5800cb3a0cd7e8d6ec0ea?source=copy_link"><img src="https://img.shields.io/badge/Blog-4285F4?style=for-the-badge&logo=google-chrome&logoColor=white" alt="Blog"></a>
    <a href="https://github.com/TIGER-AI-Lab/OpenResearcher"><img src="https://img.shields.io/badge/Github-181717?style=for-the-badge&logo=github&logoColor=white" alt="Blog"></a>
  <a href="https://huggingface.co/datasets/OpenResearcher/OpenResearcher-Dataset"><img src="https://img.shields.io/badge/Dataset-FFB7B2?style=for-the-badge&logo=huggingface&logoColor=ffffff" alt="Dataset"></a>
  <a href="https://huggingface.co/OpenResearcher/Nemotron-3-Nano-30B-A3B"><img src="https://img.shields.io/badge/Model-FFD966?style=for-the-badge&logo=huggingface&logoColor=ffffff" alt="Model"></a>
  <a href="https://huggingface.co/spaces/OpenResearcher/OpenResearcher"><img src="https://img.shields.io/badge/Demo-F97316.svg?style=for-the-badge&logo=gradio&logoColor=white" alt="Demo"></a>
  <!-- <a href="https://wandb.ai/dongfu/nano-v3-sft-search"><img src="https://img.shields.io/badge/WandB%20Logs-48B5A3?style=for-the-badge&logo=weightsandbiases&logoColor=white" alt="WandB Logs"></a> -->
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</div>
<p align="center">
  🤗 <a href="https://huggingface.co/collections/TIGER-Lab/openresearcher" target="_blank">HuggingFace</a> ｜

  <img src="https://raw.githubusercontent.com/TIGER-AI-Lab/OpenResearcher/main/assets/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="https://raw.githubusercontent.com/TIGER-AI-Lab/OpenResearcher/main/assets/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="https://raw.githubusercontent.com/TIGER-AI-Lab/OpenResearcher/main/assets/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>
</p>

## Overview 
**OpenResearcher** is a fully open agentic large language model (30B-A3B) designed for **long-horizon deep research** scenarios. It 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`. It also demonstrates **leading performance** across a range of deep research benchmarks, including BrowseComp, GAIA, WebWalkerQA, and xbench-DeepSearch. We **fully open-source** the training and evaluation recipe—including data, model, training methodology, and evaluation framework for everyone to progress deep research.

## OpenResearcher-30B-A3B-GGUF
**Note: For the best performance, we recommend using [OpenResearcher-30B-A3B](https://huggingface.co/OpenResearcher/OpenResearcher-30B-A3B).**

To support efficient deployment, we release several quantized versions of [OpenResearcher-30B-A3B](https://huggingface.co/OpenResearcher/OpenResearcher-30B-A3B), including `Q4_K_M`, `Q5_0`, `Q5_K_M`, `Q6_K`, and `Q8_0`.                                                                                                                                      
| Quantization | File Size | BPW | PPL | +/- | Tokens/sec |                                                                                       
|---|---|---|---|---|---|
| BF16 | 58.84 GiB | 16.00 | 8.4522 | 0.06489 | 4,117.90 |                                                                                        
| Q8_0 | 31.27 GiB | 8.51 | 8.4654 | 0.06499 | 7,490.81 |                                                                                       
| Q6_K | 31.20 GiB | 8.49 | 8.4784 | 0.06510 | 7,389.76 |
| Q5_0 | 20.37 GiB | 5.54 | 8.5462 | 0.06558 | 7,534.66 |
| Q4_K_M | 22.82 GiB | 6.21 | 8.5970 | 0.06610 | 7,046.96 |
| Q5_K_M | 24.24 GiB | 6.60 | 8.6074 | 0.06625 | 6,661.48 |


## 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}
}
```