通義深度研究技術報告

Tongyi DeepResearch Technical Report

October 28, 2025

作者: Tongyi DeepResearch Team, Baixuan Li, Bo Zhang, Dingchu Zhang, Fei Huang, Guangyu Li, Guoxin Chen, Huifeng Yin, Jialong Wu, Jingren Zhou, Kuan Li, Liangcai Su, Litu Ou, Liwen Zhang, Pengjun Xie, Rui Ye, Wenbiao Yin, Xinmiao Yu, Xinyu Wang, Xixi Wu, Xuanzhong Chen, Yida Zhao, Zhen Zhang, Zhengwei Tao, Zhongwang Zhang, Zile Qiao, Chenxi Wang, Donglei Yu, Gang Fu, Haiyang Shen, Jiayin Yang, Jun Lin, Junkai Zhang, Kui Zeng, Li Yang, Hailong Yin, Maojia Song, Ming Yan, Peng Xia, Qian Xiao, Rui Min, Ruixue Ding, Runnan Fang, Shaowei Chen, Shen Huang, Shihang Wang, Shihao Cai, Weizhou Shen, Xiaobin Wang, Xin Guan, Xinyu Geng, Yingcheng Shi, Yuning Wu, Zhuo Chen, Zijian Li, Yong Jiang

cs.AI

摘要

我們推出通義深度研究（Tongyi DeepResearch）——一款專為長時程深度資訊探索研究任務設計的智能體大型語言模型。為激發自主深度研究能力，該模型通過結合智能體中期訓練與智能體後期訓練的端到端訓練框架開發，實現跨複雜任務的可擴展推理與資訊探索。我們設計了高度可擴展的全自動數據合成管線，無需依賴高成本人工標註，即可支撐所有訓練階段。通過為每個階段構建定制化環境，我們的系統能實現全流程穩定一致的交互。通義深度研究模型總參數量達305億，每令牌僅激活33億參數，在包括「人類終極考試」、BrowseComp、BrowseComp-ZH、WebWalkerQA、xbench-DeepSearch、FRAMES及xbench-DeepSearch-2510在內的一系列智能體深度研究基準測試中均達到頂尖性能。我們將開源模型、框架及完整解決方案，以賦能研究社群。

English

We present Tongyi DeepResearch, an agentic large language model, which is specifically designed for long-horizon, deep information-seeking research tasks. To incentivize autonomous deep research agency, Tongyi DeepResearch is developed through an end-to-end training framework that combines agentic mid-training and agentic post-training, enabling scalable reasoning and information seeking across complex tasks. We design a highly scalable data synthesis pipeline that is fully automatic, without relying on costly human annotation, and empowers all training stages. By constructing customized environments for each stage, our system enables stable and consistent interactions throughout. Tongyi DeepResearch, featuring 30.5 billion total parameters, with only 3.3 billion activated per token, achieves state-of-the-art performance across a range of agentic deep research benchmarks, including Humanity's Last Exam, BrowseComp, BrowseComp-ZH, WebWalkerQA, xbench-DeepSearch, FRAMES and xbench-DeepSearch-2510. We open-source the model, framework, and complete solutions to empower the community.