Lavida-O, a novel unified Masked Diffusion Model (MDM) designed for both multi-modal understanding and generation tasks, which surpasses previous MDMs in capability and performance. Unlike earlier models that were limited to simple image tasks or low-resolution output, Lavida-O leverages a single framework to handle complex tasks like high-resolution text-to-image synthesis (1024px), object grounding, and sophisticated image editing. A key innovation is the Elastic Mixture-of-Transformers (Elastic-MoT) architecture, which efficiently couples a smaller generation branch with a larger understanding branch, allowing for scalable training and flexible task-specific parameter loading. Furthermore, Lavida-O explicitly uses its understanding capabilities to enhance generation quality through pla ...