Any-to-any models are the endgame of multimodal AI — a single architecture that can accept and generate any combination of text, images, audio, and video. GPT-4o (2024) was the first production model to natively process and generate across modalities in real time, and Gemini 2.0 pushed this further with interleaved multimodal outputs. The technical challenge is enormous: unifying tokenization across modalities, preventing mode collapse where the model favors text over other outputs, and maintaining quality competitive with specialist models in each domain. Meta's Chameleon and open efforts like NExT-GPT explored this space, but true any-to-any generation at frontier quality remains the province of the largest labs.
Evaluates any-to-any multimodal models across diverse modality combinations
Leading models on DEMON Bench.
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