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arXiv · 2505.07062

Seed1.5-VL Technical Report

Dong Guo·Faming Wu·Feida Zhu·Fuxing Leng·Guang Shi·Haobin Chen·Haoqi Fan·Jian Wang·Jianyu Jiang·Jiawei Wang·Jingji Chen·Jingjia Huang·Kang Lei·Liping Yuan·Lishu Luo·Pengfei Liu·Qinghao Ye·Rui Qian·Shen Yan·Shixiong Zhao·Shuai Peng·Shuangye Li·Sihang Yuan·Sijin Wu·Tianheng Cheng·Weiwei Liu·Wenqian Wang·Xianhan Zeng·Xiao Liu·Xiaobo Qin·Xiaohan Ding·Xiaojun Xiao·Xiaoying Zhang·Xuanwei Zhang·Xuehan Xiong·Yanghua Peng·Yangrui Chen·Yanwei Li·Yanxu Hu·Yi Lin·Yiyuan Hu·Yiyuan Zhang·Youbin Wu·Yu Li·Yudong Liu·Yue Ling·Yujia Qin·Zanbo Wang·Zhiwu He·Aoxue Zhang·Bairen Yi·Bencheng Liao·Can Huang·Can Zhang·Chaorui Deng·Chaoyi Deng·Cheng Lin·Cheng Yuan·Chenggang Li·Chenhui Gou·Chenwei Lou·Chengzhi Wei·Chundian Liu·Chunyuan Li·Deyao Zhu·Donghong Zhong·Feng Li·Feng Zhang·Gang Wu·Guodong Li·Guohong Xiao·Haibin Lin·Haihua Yang·Haoming Wang·Heng Ji·Hongxiang Hao·Hui Shen·Huixia Li·Jiahao Li·Jialong Wu·Jianhua Zhu·Jianpeng Jiao·Jiashi Feng·Jiaze Chen·Jianhui Duan·Jihao Liu·Jin Zeng·Jingqun Tang·Jingyu Sun·Joya Chen·Jun Long·Junda Feng·Junfeng Zhan·Junjie Fang·Junting Lu·Kai Hua·Kai Liu·Kai Shen·Kaiyuan Zhang·Ke Shen
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Abstract

We present Seed1.5-VL, a vision-language foundation model designed to advance general-purpose multimodal understanding and reasoning. Seed1.5-VL is composed with a 532M-parameter vision encoder and a Mixture-of-Experts (MoE) LLM of 20B active parameters. Despite its relatively compact architecture, it delivers strong performance across a wide spectrum of public VLM benchmarks and internal evaluation suites, achieving the state-of-the-art performance on 38 out of 60 public benchmarks. Moreover, in agent-centric tasks such as GUI control and gameplay, Seed1.5-VL outperforms leading multimodal systems, including OpenAI CUA and Claude 3.7. Beyond visual and video understanding, it also demonstrates strong reasoning abilities, making it particularly effective for multimodal reasoning challenges such as visual puzzles. We believe these capabilities will empower broader applications across diverse tasks. In this report, we mainly provide a comprehensive review of our experiences in building Seed1.5-VL across model design, data construction, and training at various stages, hoping that this report can inspire further research. Seed1.5-VL is now accessible at https://www.volcengine.com/ (Volcano Engine Model ID: doubao-1-5-thinking-vision-pro-250428)

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Dong Guo, Faming Wu, Feida Zhu, Fuxing Leng, Guang Shi, Haobin Chen, Haoqi Fan, Jian Wang, Jianyu Jiang, Jiawei Wang, Jingji Chen, Jingjia Huang, Kang Lei, Liping Yuan, Lishu Luo, Pengfei Liu, Qinghao Ye, Rui Qian, Shen Yan, Shixiong Zhao, Shuai Peng, Shuangye Li, Sihang Yuan, Sijin Wu, Tianheng Cheng, Weiwei Liu, Wenqian Wang, Xianhan Zeng, Xiao Liu, Xiaobo Qin, Xiaohan Ding, Xiaojun Xiao, Xiaoying Zhang, Xuanwei Zhang, Xuehan Xiong, Yanghua Peng, Yangrui Chen, Yanwei Li, Yanxu Hu, Yi Lin, Yiyuan Hu, Yiyuan Zhang, Youbin Wu, Yu Li, Yudong Liu, Yue Ling, Yujia Qin, Zanbo Wang, Zhiwu He, Aoxue Zhang, Bairen Yi, Bencheng Liao, Can Huang, Can Zhang, Chaorui Deng, Chaoyi Deng, Cheng Lin, Cheng Yuan, Chenggang Li, Chenhui Gou, Chenwei Lou, Chengzhi Wei, Chundian Liu, Chunyuan Li, Deyao Zhu, Donghong Zhong, Feng Li, Feng Zhang, Gang Wu, Guodong Li, Guohong Xiao, Haibin Lin, Haihua Yang, Haoming Wang, Heng Ji, Hongxiang Hao, Hui Shen, Huixia Li, Jiahao Li, Jialong Wu, Jianhua Zhu, Jianpeng Jiao, Jiashi Feng, Jiaze Chen, Jianhui Duan, Jihao Liu, Jin Zeng, Jingqun Tang, Jingyu Sun, Joya Chen, Jun Long, Junda Feng, Junfeng Zhan, Junjie Fang, Junting Lu, Kai Hua, Kai Liu, Kai Shen, Kaiyuan Zhang, Ke Shen. 2025-05-11. Seed1.5-VL Technical Report. https://arxiv.org/abs/2505.07062

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