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This paper introduces Chimera, a hybrid visual diffusion backbone with a principled scaling recipe, combining Kimi Delta Attention, Multi-head Latent Attention, and sparse Mixture-of-Experts to efficiently handle long-context image and video generation. It also presents HeteroP, a module-wise hyperparameter transfer scheme, and Chinchilla-style scaling laws to train an 11B-parameter model with 2B activated parameters.