Paper Detail
GLM-V Team, :, Wenyi Hong, Xiaotao Gu, Ziyang Pan, Zhen Yang, Yuting Wang, Yue Wang, Yuanchang Yue, Yu Wang, Yanling Wang, Yan Wang, Xijun Liu, Wenmeng Yu, Weihan Wang, Wei Li, Shuaiqi Duan, Sheng Yang, Ruiliang Lv, Mingdao Liu, Lihang Pan, Ke Ning, Junhui Ji, Jinjiang Wang, Jing Chen, Jiazheng Xu, Jiale Zhu, Jiale Cheng, Ji Qi, Guobing Gan, Guo Wang, Cong Yao, Zijun Dou, Zihao Zhou, Zihan Wang, Zhiqi Ge, Zhijie Li, Zhenyu Hou, Zhao Xue, Zehui Wang, Zehai He, Yusen Liu, Yukuo Cen, Yuchen Li, Yuan Wang, Yijian Lu, Yanzi Wang, Yadong Xue, Xinyu Zhang, Xinyu Liu, Wenkai Li, Tianyu Tong, Tianshu Zhang, Shengdong Yan, Qinkai Zheng, Mingde Xu, Licheng Bao, Jiaxing Xu, Jiaxin Fan, Jiawen Qian, Jiali Chen, Jiahui Lin, Haozhi Zheng, Haoran Wang, Haochen Li, Fan Yang, Dan Zhang, Chuangxin Zhao, Chengcheng Wu, Boyan Shi, Bowei Jia, Baoxu Wang, Peng Zhang, Debing Liu, Bin Xu, Juanzi Li, Minlie Huang, Yuxiao Dong, Jie Tang, V Team
We present GLM-5V-Turbo, a step toward native foundation models for multimodal agents. As foundation models are increasingly deployed in real environments, agentic capability depends not only on language reasoning, but also on the ability to perceive, interpret, and act over heterogeneous contexts such as images, videos, webpages, documents, GUIs. GLM-5V-Turbo is built around this objective: multimodal perception is integrated as a core component of reasoning, planning, tool use, and execution, rather than as an auxiliary interface to a language model. This report summarizes the main improvements behind GLM-5V-Turbo across model design, multimodal training, reinforcement learning, toolchain expansion, and integration with agent frameworks. These developments lead to strong performance in multimodal coding, visual tool use, and framework-based agentic tasks, while preserving competitive text-only coding capability. More importantly, our development process offers practical insights for building multimodal agents, highlighting the central role of multimodal perception, hierarchical optimization, and reliable end-to-end verification.
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@article{team2026glm,
title = {GLM-5V-Turbo: Toward a Native Foundation Model for Multimodal Agents},
author = {GLM-V Team and : and Wenyi Hong and Xiaotao Gu and Ziyang Pan and Zhen Yang and Yuting Wang and Yue Wang and Yuanchang Yue and Yu Wang and Yanling Wang and Yan Wang and Xijun Liu and Wenmeng Yu and Weihan Wang and Wei Li and Shuaiqi Duan and Sheng Yang and Ruiliang Lv and Mingdao Liu and Lihang Pan and Ke Ning and Junhui Ji and Jinjiang Wang and Jing Chen and Jiazheng Xu and Jiale Zhu and Jiale Cheng and Ji Qi and Guobing Gan and Guo Wang and Cong Yao and Zijun Dou and Zihao Zhou and Zihan Wang and Zhiqi Ge and Zhijie Li and Zhenyu Hou and Zhao Xue and Zehui Wang and Zehai He and Yusen Liu and Yukuo Cen and Yuchen Li and Yuan Wang and Yijian Lu and Yanzi Wang and Yadong Xue and Xinyu Zhang and Xinyu Liu and Wenkai Li and Tianyu Tong and Tianshu Zhang and Shengdong Yan and Qinkai Zheng and Mingde Xu and Licheng Bao and Jiaxing Xu and Jiaxin Fan and Jiawen Qian and Jiali Chen and Jiahui Lin and Haozhi Zheng and Haoran Wang and Haochen Li and Fan Yang and Dan Zhang and Chuangxin Zhao and Chengcheng Wu and Boyan Shi and Bowei Jia and Baoxu Wang and Peng Zhang and Debing Liu and Bin Xu and Juanzi Li and Minlie Huang and Yuxiao Dong and Jie Tang and V Team},
year = {2026},
abstract = {We present GLM-5V-Turbo, a step toward native foundation models for multimodal agents. As foundation models are increasingly deployed in real environments, agentic capability depends not only on language reasoning, but also on the ability to perceive, interpret, and act over heterogeneous contexts such as images, videos, webpages, documents, GUIs. GLM-5V-Turbo is built around this objective: multimodal perception is integrated as a core component of reasoning, planning, tool use, and execution, },
url = {https://arxiv.org/abs/2604.26752},
keywords = {cs.CV, multimodal agents, multimodal perception, foundation models, visual tool use, hierarchical optimization, end-to-end verification, code available, huggingface daily},
eprint = {2604.26752},
archiveprefix = {arXiv},
}
{}