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[2025-01-12] 🚀🚀🚀 We have open-sourced AgentCPM-Explore, the first open-source agent model with 4B parameters to appear on 8 widely used long-horizon agent benchmarks.

Overview

AgentCPM is a series of open-source large language model agents jointly developed by the THUNLP, Renmin University of China, ModelBest, and the OpenBMB Community. The AgentCPM team has focused on systematically building agents’ deep research capabilities and released AgentCPM-Explore, a deep-search LLM agent.

Model List

Model	Download Links	Resources	Technical Report
AgentCPM-Explore	🤗 Hugging Face 🤖 ModelScope	AgentDock: An unified tool sandbox management and scheduling platform AgentRL: An asynchronous agent reinforcement learning training framework AgentToLeaP: An one-click evaluation platform for agent tool-learning capabilities	Coming Soon...

AgentCPM-Explore

AgentCPM-Explore is the first open-source agent model with 4B parameters to appear on 8 widely used long-horizon agent benchmarks such as GAIA, XBench, etc.

Key highlights of AgentCPM-Explore include:

SOTA at 4B Scale: Best-in-class among same-size models, matches or surpasses 8B models, rivals some 30B+ and closed-source LLMs.
Deep Exploration: 100+ turns of continuous interaction with multi-source cross-validation and dynamic strategy adjustment.
End-to-End Open Source: Complete training and evaluation infrastructure for community development and custom extensions.

License

The code in this repository is released under the Apache-2.0 license.

Citation

If AgentCPM-Explore is useful for your research, please cite the codebase:

@software{AgentCPMExplore2026,
  title  = {AgentCPM-Explore: An End-to-End Infrastructure for Training and Evaluating LLM Agents},
  author = {Haotian Chen, Xin Cong, Shengda Fan, Yuyang Fu, Ziqin Gong, Yaxi Lu, Yishan Li, Boye Niu, Chengjun Pan, Zijun Song, Huadong Wang, Yesai Wu, Yueying Wu, Zihao Xie, Yukun Yan, Zhong Zhang, Yankai Lin, Zhiyuan Liu, Maosong Sun},
  year   = {2026},
  url    = {https://github.com/OpenBMB/AgentCPM-Explore}
}