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Introducing LongCat-Flash-Thinking: A Technical Report

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Main Authors:	Meituan LongCat Team, Gui, Anchun, Li, Bei, Tao, Bingyang, Zhou, Bole, Chen, Borun, Zhang, Chao, Han, Chengcheng, Yang, Chenhui, Zhang, Chi, Peng, Chong, Zhang, Chuyu, Chen, Cong, Li, Fengcun, Xu, Gang, Lin, Guoyuan, Jiang, Hao, Liang, Hao, Fu, Haomin, Ma, Haoxiang, Liu, Hong, Hao, Hongyan, Tang, Hongyin, Zang, Hongyu, Ni, Hongzhi, Su, Hui, Liu, Jiahao, Li, Jiahuan, Liu, Jialin, Zhang, Jianfei, Xu, Jianhao, Wang, Jianing, Sun, Jiaqi, Zhang, Jiaqi, Shi, Jiarong, Yang, Jiawei, Wang, Jingang, Ding, Jinrui, Kuang, Jun, Xu, Jun, He, Ke, Zhang, Kefeng, Wang, Keheng, He, Keqing, Wei, Li, Shi, Liang, Qiu, Lin, Kong, Lingbin, Liu, Lingchuan, Guo, Linsen, An, Longfei, Xia, Mai, Zhou, Meng, Zhu, Mengshen, Pei, Peng, Jia, Pengcheng, Gu, Qi, Guo, Qi, Huang, Qiong, Chen, Quan, Weng, Quanchi, Weng, Rongxiang, Shao, Ruichen, Li, Rumei, Lei, Shanglin, Du, Shuai, Liu, Shuaikang, Zhou, Shuang, Hu, Shuhao, Xu, Siyu, Gong, Songshan, Liang, Tao, Hu, Tianhao, He, Wei, Shi, Wei, Wang, Wei, Wu, Wei, Zhuo, Wei, Tang, Weifeng, Shi, Wenjie, Zhu, Wenlong, Su, Xi, Liu, Xiangcheng, Xi, Xiangyu, Huang, Xiangzhou, Liu, Xiao, Jiang, Xiaochen, Shi, Xiaowei, Shi, Xiaowen, Li, Xiaoyu, Chen, Xin, Zhao, Xinyue, Huang, Xuan, Zhang, Xuemiao, Cao, Xuezhi, Cai, Xunliang, Zhang, Yajie, Chen, Yang, Liu, Yang, Zheng, Yang, Wang, Yaoming, Huo, Yaqi, Sun, Yerui, Lu, Yifan, Li, Yiyang, Xiao, Youshao, Lei, Yuanzhe, Xie, Yuchen, Sun, Yueqing, Zhang, Yufei, Wei, Yuhuai, Qian, Yulei, Zhao, Yunke, Ding, Yuqing, Jiang, Yuwei, Yang, Zhaohua, Chen, Zhengyu, Liu, Zhijian, Xia, Zhikang, Su, Zhongda, Li, Ziran, Wang, Ziwen, Zhuang, Ziyuan, Wang, Zongyu, Yang, Zunyuan
Format:	Preprint
Published:	2025
Subjects:	Artificial Intelligence
Online Access:	Acceder al recurso
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author	Meituan LongCat Team Gui, Anchun Li, Bei Tao, Bingyang Zhou, Bole Chen, Borun Zhang, Chao Zhang, Chao Han, Chengcheng Yang, Chenhui Zhang, Chi Peng, Chong Zhang, Chuyu Chen, Cong Li, Fengcun Xu, Gang Lin, Guoyuan Jiang, Hao Liang, Hao Fu, Haomin Ma, Haoxiang Liu, Hong Hao, Hongyan Tang, Hongyin Zang, Hongyu Ni, Hongzhi Su, Hui Liu, Jiahao Li, Jiahuan Liu, Jialin Zhang, Jianfei Xu, Jianhao Wang, Jianing Sun, Jiaqi Zhang, Jiaqi Shi, Jiarong Yang, Jiawei Wang, Jingang Ding, Jinrui Kuang, Jun Xu, Jun He, Ke Zhang, Kefeng Wang, Keheng He, Keqing Wei, Li Shi, Liang Qiu, Lin Kong, Lingbin Liu, Lingchuan Guo, Linsen An, Longfei Xia, Mai Zhou, Meng Zhu, Mengshen Pei, Peng Jia, Pengcheng Gu, Qi Guo, Qi Huang, Qiong Chen, Quan Weng, Quanchi Weng, Rongxiang Shao, Ruichen Li, Rumei Lei, Shanglin Du, Shuai Liu, Shuaikang Zhou, Shuang Hu, Shuhao Xu, Siyu Gong, Songshan Liang, Tao Hu, Tianhao He, Wei Shi, Wei Wang, Wei Wu, Wei Zhuo, Wei Tang, Weifeng Shi, Wenjie Zhu, Wenlong Su, Xi Liu, Xiangcheng Xi, Xiangyu Huang, Xiangzhou Liu, Xiao Jiang, Xiaochen Shi, Xiaowei Shi, Xiaowen Li, Xiaoyu Chen, Xin Zhao, Xinyue Huang, Xuan Zhang, Xuemiao Cao, Xuezhi Cai, Xunliang Zhang, Yajie Chen, Yang Liu, Yang Liu, Yang Zheng, Yang Wang, Yaoming Huo, Yaqi Sun, Yerui Lu, Yifan Li, Yiyang Xiao, Youshao Lei, Yuanzhe Xie, Yuchen Sun, Yueqing Zhang, Yufei Wei, Yuhuai Qian, Yulei Zhao, Yunke Ding, Yuqing Jiang, Yuwei Yang, Zhaohua Chen, Zhengyu Liu, Zhijian Xia, Zhikang Su, Zhongda Li, Ziran Wang, Ziwen Zhuang, Ziyuan Wang, Zongyu Yang, Zunyuan
author_facet	Meituan LongCat Team Gui, Anchun Li, Bei Tao, Bingyang Zhou, Bole Chen, Borun Zhang, Chao Zhang, Chao Han, Chengcheng Yang, Chenhui Zhang, Chi Peng, Chong Zhang, Chuyu Chen, Cong Li, Fengcun Xu, Gang Lin, Guoyuan Jiang, Hao Liang, Hao Fu, Haomin Ma, Haoxiang Liu, Hong Hao, Hongyan Tang, Hongyin Zang, Hongyu Ni, Hongzhi Su, Hui Liu, Jiahao Li, Jiahuan Liu, Jialin Zhang, Jianfei Xu, Jianhao Wang, Jianing Sun, Jiaqi Zhang, Jiaqi Shi, Jiarong Yang, Jiawei Wang, Jingang Ding, Jinrui Kuang, Jun Xu, Jun He, Ke Zhang, Kefeng Wang, Keheng He, Keqing Wei, Li Shi, Liang Qiu, Lin Kong, Lingbin Liu, Lingchuan Guo, Linsen An, Longfei Xia, Mai Zhou, Meng Zhu, Mengshen Pei, Peng Jia, Pengcheng Gu, Qi Guo, Qi Huang, Qiong Chen, Quan Weng, Quanchi Weng, Rongxiang Shao, Ruichen Li, Rumei Lei, Shanglin Du, Shuai Liu, Shuaikang Zhou, Shuang Hu, Shuhao Xu, Siyu Gong, Songshan Liang, Tao Hu, Tianhao He, Wei Shi, Wei Wang, Wei Wu, Wei Zhuo, Wei Tang, Weifeng Shi, Wenjie Zhu, Wenlong Su, Xi Liu, Xiangcheng Xi, Xiangyu Huang, Xiangzhou Liu, Xiao Jiang, Xiaochen Shi, Xiaowei Shi, Xiaowen Li, Xiaoyu Chen, Xin Zhao, Xinyue Huang, Xuan Zhang, Xuemiao Cao, Xuezhi Cai, Xunliang Zhang, Yajie Chen, Yang Liu, Yang Liu, Yang Zheng, Yang Wang, Yaoming Huo, Yaqi Sun, Yerui Lu, Yifan Li, Yiyang Xiao, Youshao Lei, Yuanzhe Xie, Yuchen Sun, Yueqing Zhang, Yufei Wei, Yuhuai Qian, Yulei Zhao, Yunke Ding, Yuqing Jiang, Yuwei Yang, Zhaohua Chen, Zhengyu Liu, Zhijian Xia, Zhikang Su, Zhongda Li, Ziran Wang, Ziwen Zhuang, Ziyuan Wang, Zongyu Yang, Zunyuan
contents	We present LongCat-Flash-Thinking, an efficient 560-billion-parameter open-source Mixture-of-Experts (MoE) reasoning model. Its advanced capabilities are cultivated through a meticulously crafted training process, beginning with long Chain-of-Thought (CoT) data cold-start and culminating in large-scale Reinforcement Learning (RL). We first employ a well-designed cold-start training strategy, which significantly enhances the reasoning potential and equips the model with specialized skills in both formal and agentic reasoning. Then, a core innovation is our domain-parallel training scheme, which decouples optimization across distinct domains (e.g., STEM, Code, Agentic) and subsequently fuses the resulting expert models into a single, nearly Pareto-optimal model. This entire process is powered by our Dynamic ORchestration for Asynchronous rollout (DORA) system, a large-scale RL framework that delivers a greater than threefold training speedup over synchronous methods on tens of thousands of accelerators. As a result, LongCat-Flash-Thinking achieves state-of-the-art performance among open-source models on a suite of complex reasoning tasks. The model exhibits exceptional efficiency in agentic reasoning, reducing average token consumption by 64.5% (from 19, 653 to 6, 965) on AIME-25, without degrading task accuracy. We release LongCat-Flash-Thinking to promote further advances in reasoning systems and agentic AI research.
format	Preprint
id	arxiv_https___arxiv_org_abs_2509_18883
institution	arXiv
publishDate	2025
record_format	arxiv
spellingShingle	Introducing LongCat-Flash-Thinking: A Technical Report Meituan LongCat Team Gui, Anchun Li, Bei Tao, Bingyang Zhou, Bole Chen, Borun Zhang, Chao Zhang, Chao Han, Chengcheng Yang, Chenhui Zhang, Chi Peng, Chong Zhang, Chuyu Chen, Cong Li, Fengcun Xu, Gang Lin, Guoyuan Jiang, Hao Liang, Hao Fu, Haomin Ma, Haoxiang Liu, Hong Hao, Hongyan Tang, Hongyin Zang, Hongyu Ni, Hongzhi Su, Hui Liu, Jiahao Li, Jiahuan Liu, Jialin Zhang, Jianfei Xu, Jianhao Wang, Jianing Sun, Jiaqi Zhang, Jiaqi Shi, Jiarong Yang, Jiawei Wang, Jingang Ding, Jinrui Kuang, Jun Xu, Jun He, Ke Zhang, Kefeng Wang, Keheng He, Keqing Wei, Li Shi, Liang Qiu, Lin Kong, Lingbin Liu, Lingchuan Guo, Linsen An, Longfei Xia, Mai Zhou, Meng Zhu, Mengshen Pei, Peng Jia, Pengcheng Gu, Qi Guo, Qi Huang, Qiong Chen, Quan Weng, Quanchi Weng, Rongxiang Shao, Ruichen Li, Rumei Lei, Shanglin Du, Shuai Liu, Shuaikang Zhou, Shuang Hu, Shuhao Xu, Siyu Gong, Songshan Liang, Tao Hu, Tianhao He, Wei Shi, Wei Wang, Wei Wu, Wei Zhuo, Wei Tang, Weifeng Shi, Wenjie Zhu, Wenlong Su, Xi Liu, Xiangcheng Xi, Xiangyu Huang, Xiangzhou Liu, Xiao Jiang, Xiaochen Shi, Xiaowei Shi, Xiaowen Li, Xiaoyu Chen, Xin Zhao, Xinyue Huang, Xuan Zhang, Xuemiao Cao, Xuezhi Cai, Xunliang Zhang, Yajie Chen, Yang Liu, Yang Liu, Yang Zheng, Yang Wang, Yaoming Huo, Yaqi Sun, Yerui Lu, Yifan Li, Yiyang Xiao, Youshao Lei, Yuanzhe Xie, Yuchen Sun, Yueqing Zhang, Yufei Wei, Yuhuai Qian, Yulei Zhao, Yunke Ding, Yuqing Jiang, Yuwei Yang, Zhaohua Chen, Zhengyu Liu, Zhijian Xia, Zhikang Su, Zhongda Li, Ziran Wang, Ziwen Zhuang, Ziyuan Wang, Zongyu Yang, Zunyuan Artificial Intelligence We present LongCat-Flash-Thinking, an efficient 560-billion-parameter open-source Mixture-of-Experts (MoE) reasoning model. Its advanced capabilities are cultivated through a meticulously crafted training process, beginning with long Chain-of-Thought (CoT) data cold-start and culminating in large-scale Reinforcement Learning (RL). We first employ a well-designed cold-start training strategy, which significantly enhances the reasoning potential and equips the model with specialized skills in both formal and agentic reasoning. Then, a core innovation is our domain-parallel training scheme, which decouples optimization across distinct domains (e.g., STEM, Code, Agentic) and subsequently fuses the resulting expert models into a single, nearly Pareto-optimal model. This entire process is powered by our Dynamic ORchestration for Asynchronous rollout (DORA) system, a large-scale RL framework that delivers a greater than threefold training speedup over synchronous methods on tens of thousands of accelerators. As a result, LongCat-Flash-Thinking achieves state-of-the-art performance among open-source models on a suite of complex reasoning tasks. The model exhibits exceptional efficiency in agentic reasoning, reducing average token consumption by 64.5% (from 19, 653 to 6, 965) on AIME-25, without degrading task accuracy. We release LongCat-Flash-Thinking to promote further advances in reasoning systems and agentic AI research.
title	Introducing LongCat-Flash-Thinking: A Technical Report
topic	Artificial Intelligence
url	https://arxiv.org/abs/2509.18883