LongCat-Next: Lexicalizing Modalities as Discrete Tokens
Abstract
The prevailing Next-Token Prediction (NTP) paradigm has driven the success of large language models through discrete autoregressive modeling. However, contemporary multimodal systems remain language-centric, often treating non-linguistic modalities as external attachments, leading to fragmented architectures and suboptimal integration. To transcend this limitation, we introduce Discrete Native Autoregressive (DiNA), a unified framework that represents multimodal information within a shared discrete space, enabling a consistent and principled autoregressive modeling across modalities. A key innovation is the Discrete Native Any-resolution Visual Transformer (dNaViT), which performs tokenization and de-tokenization at arbitrary resolutions, transforming continuous visual signals into hierarchical discrete tokens. Building on this foundation, we develop LongCat-Next, a native multimodal model that processes text, vision, and audio under a single autoregressive objective with minimal modality-specific design. As an industrial-strength foundation model, it excels at seeing, painting, and talking within a single framework, achieving strong performance across a wide range of multimodal benchmarks. In particular, LongCat-Next addresses the long-standing performance ceiling of discrete vision modeling on understanding tasks and provides a unified approach to effectively reconcile the conflict between understanding and generation. As an attempt toward native multimodality, we open-source the LongCat-Next and its tokenizers, hoping to foster further research and development in the community. GitHub: https://github.com/meituan-longcat/LongCat-Next
Cite
@article{arxiv.2603.27538,
title = {LongCat-Next: Lexicalizing Modalities as Discrete Tokens},
author = {Meituan LongCat Team and Bin Xiao and Chao Wang and Chengjiang Li and Chi Zhang and Chong Peng and Hang Yu and Hao Yang and Haonan Yan and Haoze Sun and Haozhe Zhao and Hong Liu and Hui Su and Jiaqi Zhang and Jiawei Wang and Jing Li and Kefeng Zhang and Manyuan Zhang and Minhao Jing and Peng Pei and Quan Chen and Taofeng Xue and Tongxin Pan and Xiaotong Li and Xiaoyang Li and Xiaoyu Zhao and Xing Hu and Xinyang Lin and Xunliang Cai and Yan Bai and Yan Feng and Yanjie Li and Yao Qiu and Yerui Sun and Yifan Lu and Ying Luo and Yipeng Mei and Yitian Chen and Yuchen Xie and Yufang Liu and Yufei Chen and Yulei Qian and Yuqi Peng and Zhihang Yu and Zhixiong Han and Changran Wang and Chen Chen and Dian Zheng and Fengjiao Chen and Ge Yang and Haowei Guo and Haozhe Wang and Hongyu Li and Huicheng Jiang and Jiale Hong and Jialv Zou and Jiamu Li and Jianping Lin and Jiaxing Liu and Jie Yang and Jing Jin and Jun Kuang and Juncheng She and Kunming Luo and Kuofeng Gao and Lin Qiu and Linsen Guo and Mianqiu Huang and Qi Li and Qian Wang and Rumei Li and Siyu Ren and Wei Wang and Wenlong He and Xi Chen and Xiao Liu and Xiaoyu Li and Xu Huang and Xuanyu Zhu and Xuezhi Cao and Yaoming Zhu and Yifei Cao and Yimeng Jia and Yizhen Jiang and Yufei Gao and Zeyang Hu and Zhenlong Yuan and Zijian Zhang and Ziwen Wang},
journal= {arXiv preprint arXiv:2603.27538},
year = {2026}
}
Comments
LongCat-Next Technical Report