Gen-Verse/MMaDA

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1668 stars · 91 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

MMaDA is an open-source family of multimodal large diffusion language models that unify textual reasoning, multimodal understanding, and text-to-image generation under a single diffusion architecture. It includes training and inference code, mixed chain-of-thought fine-tuning, and the UniGRPO policy-gradient RL post-training algorithm.

Use cases

• generate images from text prompts with a diffusion language model
• run a diffusion-based LLM for text reasoning tasks
• fine-tune a multimodal model with mixed chain-of-thought data
• post-train diffusion foundation models with reinforcement learning
• experiment with non-autoregressive multimodal generation
• research unified understanding and generation architectures

When to choose

• you need a single model for both text reasoning and image generation
• you want to research or extend diffusion language models (dLLMs)
• you need an open-weights multimodal foundation model with RL training infrastructure

When to avoid

• you need a production-ready autoregressive LLM with mature ecosystem support
• you lack GPU resources for 8B-parameter model inference or training
• you only need standard text-to-image generation without reasoning

Facets

library · maturity active

machine-learning deep-learning llm-training llm-inference image-processing nlp large-language-models deep-learning artificial-intelligence image-processing python diffusion-language-model multimodal text-to-image block-diffusion chain-of-thought reinforcement-learning unigrpo foundation-model natural-language-processing gpu

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