Instructions to use OpenResearcher/OpenResearcher-30B-A3B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenResearcher/OpenResearcher-30B-A3B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="OpenResearcher/OpenResearcher-30B-A3B", trust_remote_code=True) messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("OpenResearcher/OpenResearcher-30B-A3B", trust_remote_code=True) model = AutoModelForCausalLM.from_pretrained("OpenResearcher/OpenResearcher-30B-A3B", trust_remote_code=True, device_map="auto") messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use OpenResearcher/OpenResearcher-30B-A3B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "OpenResearcher/OpenResearcher-30B-A3B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "OpenResearcher/OpenResearcher-30B-A3B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/OpenResearcher/OpenResearcher-30B-A3B
- SGLang
How to use OpenResearcher/OpenResearcher-30B-A3B with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "OpenResearcher/OpenResearcher-30B-A3B" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "OpenResearcher/OpenResearcher-30B-A3B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "OpenResearcher/OpenResearcher-30B-A3B" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "OpenResearcher/OpenResearcher-30B-A3B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use OpenResearcher/OpenResearcher-30B-A3B with Docker Model Runner:
docker model run hf.co/OpenResearcher/OpenResearcher-30B-A3B
| license: mit | |
| datasets: | |
| - OpenResearcher/OpenResearcher-Dataset | |
| base_model: | |
| - nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-Base-BF16 | |
| library_name: transformers | |
| <div style="display: flex; align-items: center; justify-content: center; gap: 8px;"> | |
| <img src="imgs/or-logo1.png" style="height: 84px; width: auto;"> | |
| <img src="imgs/openresearcher-title.svg" style="height: 84px; width: auto;"> | |
| </div> | |
| <div align="center"> | |
| <a href="https://arxiv.org/abs/2603.20278"><img src="https://img.shields.io/badge/arXiv-B31B1B?style=for-the-badge&logo=arXiv&logoColor=white" alt="Blog"></a> | |
| <a href="https://huggingface.co/papers/2603.20278"><img src="https://img.shields.io/badge/Paper-FFD966?style=for-the-badge&logo=huggingface&logoColor=ffffff" alt="Model"></a> | |
| <!-- <a href="https://huggingface.co/papers/2603.20278"><img src="https://img.shields.io/badge/arXiv-B31B1B?style=for-the-badge&logo=arXiv&logoColor=white" alt="Blog"></a> --> | |
| <a href="https://x.com/zhuofengli96475/status/2036475211063648414"><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> --> | |
| <a href="https://huggingface.co/datasets/OpenResearcher/OpenResearcher-Eval-Logs/tree/main"><img src="https://img.shields.io/badge/Eval%20Logs-755BB4?style=for-the-badge&logo=google-sheets&logoColor=white" alt="Eval Logs"></a> | |
| </div> | |
| </div> | |
| <div align="center" style="padding: 10px 0 -4px; display: flex; align-items: center; justify-content: center; gap: 16px;"> | |
| <div style="width: 60px; height: 2px; background: linear-gradient(90deg, transparent, #E24B4A);"></div> | |
| <span style="font-size: 22px; font-weight: 600; color: #E24B4A;">Adopted by NVIDIA's Nemotron family of models!</span> | |
| <div style="width: 60px; height: 2px; background: linear-gradient(90deg, #E24B4A, transparent);"></div> | |
| </div> | |
| <p align="center"> | |
| 🤗 <a href="https://huggingface.co/collections/TIGER-Lab/openresearcher" target="_blank">HuggingFace</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> | |
| </p> | |
| ## 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`. | |
| <div align="center"> | |
| <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);"> | |
| </div> | |
| ## Deep Research Benchmark Results | |
| <div align="center"> | |
| <img src="https://raw.githubusercontent.com/TIGER-AI-Lab/OpenResearcher/main/assets/imgs/main_table.png" alt="Deep Research Benchmark Results" width="100%"> | |
| </div> | |
| ## 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. | |
| ## Core Contributors | |
| <table> | |
| <tr> | |
| <td align="center"> | |
| <a href="https://zhuofeng-li.github.io/"> | |
| <img src="https://github.com/Zhuofeng-Li.png" width="75px;" alt="Zhuofeng Li"/> | |
| <br /> | |
| <sub><b>Zhuofeng Li</b></sub> | |
| </a> | |
| </td> | |
| <td align="center"> | |
| <a href="https://github.com/jdf-prog"> | |
| <img src="https://github.com/jdf-prog.png" width="75px;" alt="Dongfu Jiang"/> | |
| <br /> | |
| <sub><b>Dongfu Jiang</b></sub> | |
| </a> | |
| </td> | |
| </td> | |
| <td align="center"> | |
| <a href="https://mxueguang.github.io/"> | |
| <img src="https://mxueguang.github.io/images/profile.jpg" width="75px;" alt="Xueguang"/> | |
| <br /> | |
| <sub><b>Xueguang Ma</b></sub> | |
| </a> | |
| </td> | |
| <td align="center"> | |
| <a href="https://isaacghx.github.io/about/"> | |
| <img src="https://github.com/IsaacGHX.png" width="75px;" alt="Haoxiang Zhang"/> | |
| <br /> | |
| <sub><b>Haoxiang Zhang</b></sub> | |
| </a> | |
| </td> | |
| <td align="center"> | |
| <a href="https://github.com/erenup"> | |
| <img src="https://github.com/erenup.png" width="75px;" alt="Ping Nie"/> | |
| <br /> | |
| <sub><b>Ping Nie</b></sub> | |
| </a> | |
| </td> | |
| </tr> | |
| </table> | |
| ## Advisors | |
| <table> | |
| <tr> | |
| <td align="center"> | |
| <a href="https://github.com/wenhuchen"> | |
| <img src="https://github.com/wenhuchen.png" width="75px;" alt="Wenhu Chen"/> | |
| <br /> | |
| <sub><b>Wenhu Chen</b></sub> | |
| </a> | |
| </td> | |
| <td align="center"> | |
| <a href="https://yuzhimanhua.github.io/"> | |
| <img src="https://yuzhimanhua.github.io/profile_pic.jpg" width="75px;" alt="Yu Zhang"/> | |
| <br /> | |
| <sub><b>Yu Zhang</b></sub> | |
| </a> | |
| </td> | |
| </tr> | |
| </table> | |
| ## Acknowledgements | |
| <div align="center"> | |
| <img src="https://raw.githubusercontent.com/TIGER-AI-Lab/OpenResearcher/main/assets/imgs/ack.png" alt="Deep Research Benchmark Results" width="100%"> | |
| </div> | |
| ## Citation | |
| ```bibtex | |
| @article{li2026openresearcher, | |
| title={{OpenResearcher: A Fully Open Pipeline for Long-Horizon Deep Research Trajectory Synthesis}}, | |
| author={Li, Zhuofeng and Jiang, Dongfu and Ma, Xueguang and Zhang, Haoxiang and Nie, Ping and Zhang, Yuyu and Zou, Kai and Xie, Jianwen and Zhang, Yu and Chen, Wenhu}, | |
| journal={arXiv preprint arXiv:2603.20278}, | |
| year={2026} | |
| } | |
| ``` |