Moebius: 0.2B image inpainting model with 10B-level performance

Overall pipeline of Moebius. We adopt the Latent Diffusion Model (LDM) framework equipped with Latent Categories Guidance (LCG). To achieve extreme architectural efficiency, the denoising U-Net is systematically restructured using our proposed LλM I blocks (detailed in Sec. 3.2). Furthermore, an adaptive multi-granularity distillation strategy (Sec. 3.3) is applied during training to align our lightweight specialist with the high-capacity teacher, successfully mitigating the capacity drop caused by extreme structural compression. @misc{DuanAndXu2026Moebius, title={Moebius: 0.2B Lightweight Image Inpainting Framework with 10B-Level Performance}, author={Kangsheng Duan and Ziyang Xu and Wenyu Liu and Xiaohu Ruan and Xiaoxin Chen and Xinggang Wang}, year={2026}, eprint={2606.19195}, archivePrefix={arXiv}, primaryClass={cs.CV}, url={https://arxiv.org/abs/2606.19195}, }