Inductive Moment Matching (IMM) is an advanced generative model technology primarily used for high-quality image generation. This technology, through an innovative inductive moment matching method, significantly improves the quality and diversity of generated images. Its main advantages include efficiency, flexibility, and robust modeling capabilities for complex data distributions. IMM was developed by Luma AI and a research team at Stanford University, aiming to advance the field of generative models and provide powerful technical support for applications such as image generation, data augmentation, and creative design. This project open-sources the code and pre-trained models, facilitating quick adoption and application by researchers and developers.