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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Seedance
Seedance 1.0 API is officially live, giving creators and developers direct access to the world’s most advanced generative video model. Ranked #1 globally on the Artificial Analysis benchmark, Seedance delivers unmatched performance in both text-to-video and image-to-video generation. It supports multi-shot storytelling, allowing characters, styles, and scenes to remain consistent across transitions. Users can expect smooth motion, precise prompt adherence, and diverse stylistic rendering across photorealistic, cinematic, and creative outputs. The API provides a generous free trial with 2 million tokens and affordable pay-as-you-go pricing from just $1.8 per million tokens. With scalability and high concurrency support, Seedance enables studios, marketers, and enterprises to generate 5–10 second cinematic-quality videos in seconds.
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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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FLUX 3
FLUX 3 is a multimodal foundation model that jointly learns from images, video, and audio within one unified architecture, building a representation of how objects hold together, how things move, and how events sound. Built on the Self-Flow approach, it aligns multimodal generation and understanding in the same backbone so each modality constrains the others, sound matches impact, motion follows physical properties, and future events follow from the past. FLUX 3 can mix modalities and jointly generate images, video, and native audio from text prompts or references such as images, video, and audio. Its video capabilities include text-to-video, image-to-video animation, video-to-video transformation, generative video-and-audio continuation, keyframe-controlled transitions, multilingual dialogue, animated typography, diverse styles and aspect ratios, and agentic chaining into longer multi-shot sequences.
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