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Welcome to the official repository of Muddit — a next-generation foundation model in the Meissonic family, built upon discrete diffusion for unified and efficient multimodal generation.

Unlike traditional autoregressive methods, Muddit leverages discrete diffusion (a.k.a. MaskGIT-style masking) as its core mechanism — enabling fast, parallel decoding across modalities.

While most unified models are still rooted in language priors, Muddit is developed from a visual-first perspective for scalable and flexible generation.

Muddit (512) and Muddit Plus (1024) aim to handle diverse tasks across modalities -- such as text generation, image generation, and vision-language reasoning -- within a single architecture and decoding paradigm.

Please refer to github link.

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