Adan is a PyTorch-native optimization algorithm that adaptively adjusts momentum for faster convergence when training deep learning models. It is integrated into major ML frameworks including PyTorch, NeMo, TIMM, and PaddlePaddle. The optimizer is the default choice for training text-to-3D models (DreamFusion, Consistent3D), diffusion transformers (MDT), and language models.