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arXiv · 2508.15763

Intern-S1: A Scientific Multimodal Foundation Model

Lei Bai·Zhongrui Cai·Yuhang Cao·Maosong Cao·Weihan Cao·Chiyu Chen·Haojiong Chen·Kai Chen·Pengcheng Chen·Ying Chen·Yongkang Chen·Yu Cheng·Pei Chu·Tao Chu·Erfei Cui·Ganqu Cui·Long Cui·Ziyun Cui·Nianchen Deng·Ning Ding·Nanqing Dong·Peijie Dong·Shihan Dou·Sinan Du·Haodong Duan·Caihua Fan·Ben Gao·Changjiang Gao·Jianfei Gao·Songyang Gao·Yang Gao·Zhangwei Gao·Jiaye Ge·Qiming Ge·Lixin Gu·Yuzhe Gu·Aijia Guo·Qipeng Guo·Xu Guo·Conghui He·Junjun He·Yili Hong·Siyuan Hou·Caiyu Hu·Hanglei Hu·Jucheng Hu·Ming Hu·Zhouqi Hua·Haian Huang·Junhao Huang·Xu Huang·Zixian Huang·Zhe Jiang·Lingkai Kong·Linyang Li·Peiji Li·Pengze Li·Shuaibin Li·Tianbin Li·Wei Li·Yuqiang Li·Dahua Lin·Junyao Lin·Tianyi Lin·Zhishan Lin·Hongwei Liu·Jiangning Liu·Jiyao Liu·Junnan Liu·Kai Liu·Kaiwen Liu·Kuikun Liu·Shichun Liu·Shudong Liu·Wei Liu·Xinyao Liu·Yuhong Liu·Zhan Liu·Yinquan Lu·Haijun Lv·Hongxia Lv·Huijie Lv·Qitan Lv·Ying Lv·Chengqi Lyu·Chenglong Ma·Jianpeng Ma·Ren Ma·Runmin Ma·Runyuan Ma·Xinzhu Ma·Yichuan Ma·Zihan Ma·Sixuan Mi·Junzhi Ning·Wenchang Ning·Xinle Pang·Jiahui Peng·Runyu Peng·Yu Qiao
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Abstract

In recent years, a plethora of open-source foundation models have emerged, achieving remarkable progress in some widely attended fields, with performance being quite close to that of closed-source models. However, in high-value but more challenging scientific professional fields, either the fields still rely on expert models, or the progress of general foundation models lags significantly compared to those in popular areas, far from sufficient for transforming scientific research and leaving substantial gap between open-source models and closed-source models in these scientific domains. To mitigate this gap and explore a step further toward Artificial General Intelligence (AGI), we introduce Intern-S1, a specialized generalist equipped with general understanding and reasoning capabilities with expertise to analyze multiple science modal data. Intern-S1 is a multimodal Mixture-of-Experts (MoE) model with 28 billion activated parameters and 241 billion total parameters, continually pre-trained on 5T tokens, including over 2.5T tokens from scientific domains. In the post-training stage, Intern-S1 undergoes offline and then online reinforcement learning (RL) in InternBootCamp, where we propose Mixture-of-Rewards (MoR) to synergize the RL training on more than 1000 tasks simultaneously. Through integrated innovations in algorithms, data, and training systems, Intern-S1 achieved top-tier performance in online RL training. On comprehensive evaluation benchmarks, Intern-S1 demonstrates competitive performance on general reasoning tasks among open-source models and significantly outperforms open-source models in scientific domains, surpassing closed-source state-of-the-art models in professional tasks, such as molecular synthesis planning, reaction condition prediction, predicting thermodynamic stabilities for crystals. Our models are available at https://huggingface.co/internlm/Intern-S1.

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Lei Bai, Zhongrui Cai, Yuhang Cao, Maosong Cao, Weihan Cao, Chiyu Chen, Haojiong Chen, Kai Chen, Pengcheng Chen, Ying Chen, Yongkang Chen, Yu Cheng, Pei Chu, Tao Chu, Erfei Cui, Ganqu Cui, Long Cui, Ziyun Cui, Nianchen Deng, Ning Ding, Nanqing Dong, Peijie Dong, Shihan Dou, Sinan Du, Haodong Duan, Caihua Fan, Ben Gao, Changjiang Gao, Jianfei Gao, Songyang Gao, Yang Gao, Zhangwei Gao, Jiaye Ge, Qiming Ge, Lixin Gu, Yuzhe Gu, Aijia Guo, Qipeng Guo, Xu Guo, Conghui He, Junjun He, Yili Hong, Siyuan Hou, Caiyu Hu, Hanglei Hu, Jucheng Hu, Ming Hu, Zhouqi Hua, Haian Huang, Junhao Huang, Xu Huang, Zixian Huang, Zhe Jiang, Lingkai Kong, Linyang Li, Peiji Li, Pengze Li, Shuaibin Li, Tianbin Li, Wei Li, Yuqiang Li, Dahua Lin, Junyao Lin, Tianyi Lin, Zhishan Lin, Hongwei Liu, Jiangning Liu, Jiyao Liu, Junnan Liu, Kai Liu, Kaiwen Liu, Kuikun Liu, Shichun Liu, Shudong Liu, Wei Liu, Xinyao Liu, Yuhong Liu, Zhan Liu, Yinquan Lu, Haijun Lv, Hongxia Lv, Huijie Lv, Qitan Lv, Ying Lv, Chengqi Lyu, Chenglong Ma, Jianpeng Ma, Ren Ma, Runmin Ma, Runyuan Ma, Xinzhu Ma, Yichuan Ma, Zihan Ma, Sixuan Mi, Junzhi Ning, Wenchang Ning, Xinle Pang, Jiahui Peng, Runyu Peng, Yu Qiao. 2025-08-24. Intern-S1: A Scientific Multimodal Foundation Model. https://arxiv.org/abs/2508.15763

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