FLUX 3 Model Overview: Multimodal Flow Models for Image, Video, Audio, and Action Prediction

FLUX 3, developed by Black Forest Labs, is a multimodal flow matching foundation model that leverages a diffusion transformer architecture to integrate images, video, audio, and action prediction within a unified framework. The model is trained using the Self-Flow framework, which enhances both generation and representation quality by optimizing for self-supervised feature reconstruction. With video as the dominant training signal, FLUX 3 can generate up to 20-second video clips with synchronized audio, supporting various generation modes like text-to-video and image-to-video. It boasts significant improvements over previous models, particularly in action prediction, demonstrated through its application in robotics with the FLUX-mimic collaboration. Despite its promising capabilities, the model's implementation details, such as parameter count and license terms, remain undisclosed, and its training data composition is not publicly detailed. Early evaluations indicate high human preference rates in video generation, and while the model is currently in early access, further improvements are anticipated during this phase.

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