An awesome list tracking advances in unified multimodal models that handle both image and text inputs and outputs. It categorizes diffusion-based, autoregressive (MLLM), and hybrid architectures, with benchmarks and datasets for evaluating multimodal comprehension and generation. Designed to help researchers and practitioners explore, compare, and build state-of-the-art unified multimodal systems.