LongCat-Flash-Omni Technical Report
Authors: name: Meituan LongCat Team, name: Bairui Wang, name: Bayan, name: Bin Xiao, name: Bo Zhang, name: Bolin Rong, name: Borun Chen, name: Chang Wan, name: Chao Zhang, name: Chen Huang, name: Chen Chen, name: Chen Chen, name: Chengxu Yang, name: Chengzuo Yang, name: Cong Han, name: Dandan Peng, name: Delian Ruan, name: Detai Xin, name: Disong Wang, name: Dongchao Yang, name: Fanfan Liu, name: Fengjiao Chen, name: Fengyu Yang, name: Gan Dong, name: Gang Huang, name: Gang Xu, name: Guanglu Wan, name: Guoqiang Tan, name: Guoqiao Yu, name: Haibo Qiu, name: Hao Lu, name: Hongbo Liu, name: Hongyu Xiang, name: Jiaheng Wu, name: Jian Yang, name: Jiaxing Liu, name: Jing Huang, name: Jingang Wang, name: Jinrui Ding, name: Juchao Jiang, name: Jun Kuang, name: Jun Wang, name: Junhui Mei, name: Ke Ding, name: Kefeng Zhang, name: Lei Chen, name: Liang Shi, name: Limeng Qiao, name: Liming Zheng, name: Lin Ma, name: Liuyang Guo, name: Liya Ma, name: Luying Sun, name: Man Gao, name: Mengshen Zhu, name: Miao Cao, name: Minliang Lin, name: Nuo Xu, name: Peng Shi, name: Qi Zhang, name: Qian Fang, name: Qian Wang, name: Qian Yang, name: Quanxiu Wang, name: Rongxiang Weng, name: Rongxin Guo, name: Ruoxuan Liang, name: Senbin Yang, name: Shanbo Xu, name: Shanglin Lei, name: Shengze Ye, name: Shimin Chen, name: Shuaiqi Chen, name: Shujie Hu, name: Shuo Li, name: Siqi Yang, name: Siyu Xu, name: Siyu Ren, name: Song Li, name: Songxiang Liu, name: Tianhao Bai, name: Tianye Dai, name: Wei Hong, name: Wei Wang, name: Weixiao Zhao, name: Wengang Cao, name: Wenlong Zhu, name: Wenlong He, name: Xi Su, name: Xi Nan, name: Xiaohan Zhao, name: Xiaohao Wang, name: Xiaoyu Zhao, name: Xiaoyu Wang, name: Xiaoyu Li, name: Xin Pan, name: Xin Chen, name: Xiusong Sun, name: Xu Xiang, name: Xudong Xing, name: Xuezhi Cao, name: Xunliang Cai, name: Yang Yang, name: Yanli Tan, name: Yao Yao, name: Yerui Sun, name: Yi Chen, name: Yifan Lu, name: Yin Gong, name: Yining Zhang, name: Yitian Chen, name: Yiyang Gan, name: Yuchen Tang, name: Yuchen Xie, name: Yueqian Wang, name: Yuewen Zheng, name: Yufei Zhang, name: Yufeng Zhong, name: Yulei Qian, name: Yuqi Peng, name: Yuwei Jiang, name: Zeyang Hu, name: Zheng Zhang, name: Zhengkun Tian, name: Zhiqing Hong, name: Zhixiong Zeng, name: Zhuqi Mi, name: Ziran Li, name: Ziwen Wang, name: Ziyi Zhao, name: Ziyuan Zhuang, name: Zizhe Zhao
Published: 2025-10-31 21:58:15

We introduce LongCat-Flash-Omni, a state-of-the-art open-source omni-modal
model with 560 billion parameters, excelling at real-time audio-visual
interaction. By adopting a curriculum-inspired progressive training strategy
that transitions from simpler to increasingly complex modality sequence
modeling tasks, LongCat-Flash-Omni attains comprehensive multimodal
capabilities while maintaining strong unimodal capability. Building upon
LongCat-Flash, which adopts a high-performance Shortcut-connected
Mixture-of-Experts (MoE) architecture with zero-computation experts,
LongCat-Flash-Omni integrates efficient multimodal perception and speech
reconstruction modules. Despite its immense size of 560B parameters (with 27B
activated), LongCat-Flash-Omni achieves low-latency real-time audio-visual
interaction. For training infrastructure, we developed a modality-decoupled
parallelism scheme specifically designed to manage the data and model
heterogeneity inherent in large-scale multimodal training. This innovative
approach demonstrates exceptional efficiency by sustaining over 90% of the
throughput achieved by text-only training. Extensive evaluations show that
LongCat-Flash-Omni achieves state-of-the-art performance on omni-modal
benchmarks among open-source models. Furthermore, it delivers highly
competitive results across a wide range of modality-specific tasks, including
text, image, and video understanding, as well as audio understanding and
generation. We provide a comprehensive overview of the model architecture
design, training procedures, and data strategies, and open-source the model to
foster future research and development in the community.