MiniMax H3 AI Video Generator

Unified Multimodal Creation

The model supports a unified workflow for text-to-image, text-to-video, and text-to-audio generation, as well as reference-based generation and editing with images, video, and audio. It can use subject, motion, and style references, while jointly treating voice, sound effects, and music. This foundation is intended to support complex multimodal requests through strong instruction following, accurate text and brand rendering, and video-to-video motion transfer.

For example, the prompt for the shot below is: "Reference the Hitchcock camera movement from Video 1, have the character in Image 2 sing, with the vocals matching Audio 3." Just describe the relationship between the context and the target video in words. H3 handles the complex, full-modality understanding on its own.

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Native 2K Audiovisual Video

Enabled by its H3-VAE architecture, the model produces high-resolution video directly rather than relying solely on conventional post-generation upscaling. Its native multi-shot modeling and integrated stereo sound help maintain visual continuity and coordinated audiovisual output across a sequence.

Context-Aware Detail Recovery

This in-context regeneration approach lets the model revisit its low-resolution output together with the original text, image, video, and audio inputs. By using the full multimodal context during regeneration, it restores fine visual details—such as small text, product features, and subtle textures—more accurately than conventional super-resolution methods.

Open Ecosystem Support

The open-weight release supports the open-source community, broadens compatibility across AI hardware platforms, and enables developers to build customized versions of H3 for their own use cases. Hardware adaptability was considered from the earliest stages of the model’s design, helping lower deployment barriers and expand access to advanced video-generation capabilities.

MiniMax H3 vs Gemini Omni Flash vs Seedance 2.5