1. Introduction Introducing DeepSeek VL2, an advanced series of large Mixture of Experts (MoE) Vision Language Models that significantly improves upon its predecessor, DeepSeek VL. DeepSeek VL2 demonstrates superior capabilities across various tasks, including but not limited to visual question answering, optical character recognition, document/table/chart understanding, and visual grounding. Our model series is composed of three variants: DeepSeek VL2 Tiny, DeepSeek VL2 Small and DeepSeek VL2, with 1.0B, 2.8B and 4.5B activated parameters respectively. DeepSeek VL2 achieves competitive or state of the art performance with similar or fewer activated parameters compared to existing open source dense and MoE based models. DeepSeek VL2: Mixture of Experts Vision Language Models for Advanced Multimodal Understanding Github Repository Zhiyu Wu , Xiaokang Chen , Zizheng Pan , Xingchao Liu , Wen Liu , Damai Dai, Huazuo Gao, Yiyang Ma, Chengyue Wu, Bingxuan Wang, Zhenda Xie, Yu Wu, Kai Hu, Jiawei Wang, Yaofeng Sun, Yukun Li, Yishi Piao, Kang Guan, Aixin Liu, Xin Xie, Yuxiang You, Kai Dong, Xingkai Yu, Haowei Zhang, Liang Zhao, Yisong Wang, Chong Ruan ( Equal Contribution, Project Lead, Cor…
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