Wan-Image: Pushing the Boundaries of Generative Visual Intelligence
Abstract
We present Wan-Image, a unified visual generation system explicitly engineered to paradigm-shift image generation models from casual synthesizers into professional-grade productivity tools. While contemporary diffusion models excel at aesthetic generation, they frequently encounter critical bottlenecks in rigorous design workflows that demand absolute controllability, complex typography rendering, and strict identity preservation. To address these challenges, Wan-Image features a natively unified multi-modal architecture by synergizing the cognitive capabilities of large language models with the high-fidelity pixel synthesis of diffusion transformers, which seamlessly translates highly nuanced user intents into precise visual outputs. It is fundamentally powered by large-scale multi-modal data scaling, a systematic fine-grained annotation engine, and curated reinforcement learning data to surpass basic instruction following and unlock expert-level professional capabilities. These include ultra-long complex text rendering, hyper-diverse portrait generation, palette-guided generation, multi-subject identity preservation, coherent sequential visual generation, precise multi-modal interactive editing, native alpha-channel generation, and high-efficiency 4K synthesis. Across diverse human evaluations, Wan-Image exceeds Seedream 5.0 Lite and GPT Image 1.5 in overall performance, reaching parity with Nano Banana Pro in challenging tasks. Ultimately, Wan-Image revolutionizes visual content creation across e-commerce, entertainment, education, and personal productivity, redefining the boundaries of professional visual synthesis.
Cite
@article{arxiv.2604.19858,
title = {Wan-Image: Pushing the Boundaries of Generative Visual Intelligence},
author = {Chaojie Mao and Chen-Wei Xie and Chongyang Zhong and Haoyou Deng and Jiaxing Zhao and Jie Xiao and Jinbo Xing and Jingfeng Zhang and Jingren Zhou and Jingyi Zhang and Jun Dan and Kai Zhu and Kang Zhao and Keyu Yan and Minghui Chen and Pandeng Li and Shuangle Chen and Tong Shen and Yu Liu and Yue Jiang and Yulin Pan and Yuxiang Tuo and Zeyinzi Jiang and Zhen Han and Ang Wang and Bang Zhang and Baole Ai and Bin Wen and Boang Feng and Feiwu Yu and Gang Wang and Haiming Zhao and He Kang and Jianjing Xiang and Jianyuan Zeng and Jinkai Wang and Junjie Zhou and Ke Sun and Linqian Wu and Pei Gong and Pingyu Wu and Ruiwen Wu and Tongtong Su and Wenmeng Zhou and Wenting Shen and Wenyuan Yu and Xianjun Xu and Xiaoming Huang and Xiejie Shen and Xin Xu and Yan Kou and Yangyu Lv and Yifan Zhai and Yitong Huang and Yun Zheng and Yuntao Hong and Zhe Zhang and Zhicheng Zhang},
journal= {arXiv preprint arXiv:2604.19858},
year = {2026}
}