Muse Video
Muse Video is Meta’s upcoming video generation model from Meta Superintelligence Labs, previewed alongside the launch of Muse Image. The model is built on the same pretraining foundation as Muse Image and is designed to generate high-fidelity videos with native audio support. Muse Video focuses on prompt adherence, visual realism, temporal consistency, and the ability to create short scenes with clear motion, continuity, and audio context. It can generate a wide range of video styles, including cinematic footage, UGC-style ads, animal scenes, product commercials, handheld point-of-view clips, and realistic moments with sound effects, voices, and music. Meta is continuing to improve areas such as audio-video synchronization and physically accurate fast motion before broader release. Coming soon to creators and Meta AI, Muse Video is positioned as a powerful tool for generating dynamic media across Meta’s creative ecosystem.
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Seedance 2.5
Seedance 2.5 is ByteDance Seed’s new-generation video creation model for long-form storytelling, multimodal reference-based generation, and precise video editing. The model can generate high-quality 30-second audio-video clips in a single pass and supports multi-round extensions for creating longer videos with consistent characters, environments, pacing, and audiovisual style. Seedance 2.5 accepts up to 30 images, 10 video clips, and 10 audio clips as references, giving creators more control over subjects, scenes, motion, camera work, and creative direction. It improves transitions, visual consistency, audio-video synchronization, object textures, skin and eye details, lighting, color, and cinematic realism. The model also supports timestamp-level editing, green screen editing, camera perspective editing, clay render referencing, motion referencing, and reference-based editing.
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MiniMax H3
MiniMax H3 is a general-purpose omni-modal generation model that jointly understands multimodal contexts spanning text, images, video, and audio. It generates videos with native stereo sound at up to 2K resolution and 15 seconds in length, delivering content for advertising, branding, ecommerce, product design, UI/UX, gaming, and creative workflows. Users can combine reference types in one instruction, for example, transferring camera movement from a video, placing a character from an image into the scene, and matching vocals from an audio clip, while describing the relationships in natural language. H3 supports text-to-image, text-to-video with jointly generated audio, multi-shot modeling, text-to-audio, and generalized reference and editing across images, videos, and audio. Voice, sound effects, and music are modeled together. The model excels at instruction following, accurate text and brand presentation, and video-to-video motion transfer.
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Veo 3.1
Veo 3.1 builds on the capabilities of the previous model to enable longer and more versatile AI-generated videos. With this version, users can create multi-shot clips guided by multiple prompts, generate sequences from three reference images, and use frames in video workflows that transition between a start and end image, both with native, synchronized audio. The scene extension feature allows extension of a final second of a clip by up to a full minute of newly generated visuals and sound. Veo 3.1 supports editing of lighting and shadow parameters to improve realism and scene consistency, and offers advanced object removal that reconstructs backgrounds to remove unwanted items from generated footage. These enhancements make Veo 3.1 sharper in prompt-adherence, more cinematic in presentation, and broader in scale compared to shorter-clip models. Developers can access Veo 3.1 via the Gemini API or through the tool Flow, targeting professional video workflows.
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