Seedance 2.5
An AI video generation model released by ByteDance, demonstrating advanced video synthesis capabilities.
Core Facts
Seedance 2.0是字节跳动旗下的AI视频生成模型
Diffusion-model-based face swapping and driving technology requires only a small number of reference images to transfer a target person's facial features onto arbitrary video footage.
Jimeng is a series of video generation models launched by ByteDance, and Seedance 2.5 shows significant improvements over its predecessor in motion fluidity, image detail, and long-shot coherence.
Timeline (last 90 days)
A developer systematically tested mainstream video editing models including Kling, Higgsfield, MiniMax, and Seedance 2.5 while building the AI video generation tool Genjutsu AI.
Cloud platform credit conversion pricing: Seedance 2.5 averages approximately 2 yuan per second, Seedance 2.0 approximately 1 yuan, and H3 and the Gemini series approximately 0.6 to 0.8 yuan.
Among T0-tier models, Seedance 2.5 has the highest visual quality, with H3, the Gemini series, and other leading models following closely behind.
Taking Seedance 2.5 as an example, if the duration and resolution are maxed out at 30 seconds and 1080P, a single generation may cost nearly 170 yuan.
ByteDance's Seedance 2.5 has introduced a "draft mode" that first uses 480p low-resolution for quick shot previews, and only proceeds to the 1080p final production stage after confirmation of satisfaction.
In Seedance 2.5's draft mode, generation speed is doubled and cost reductions range between 30% and 77%.
The AI workflow demonstrated by Bilibili UP host Jax consists of four tools in series: GPT-6 Astra, Blender, Higgs Field, and Seedance 2.5.
In the video, the spoken name for Seedance 2.5 is inconsistently mixed among Cedence 2.5, Seedance 2.5, and C-Dance 2.5.
Diffusion-model-based face swapping and driving technology requires only a small number of reference images to transfer a target person's facial features onto arbitrary video footage.
The core idea of this workflow is to extract depth information and character motion from the original video, then use AI to replace the protagonist and background, achieving a video remake with consistent motion and entirely new visuals.
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All Facts (20)
Seedance 2.0是字节跳动旗下的AI视频生成模型
80%VerifiedDiffusion-model-based face swapping and driving technology requires only a small number of reference images to transfer a target person's facial features onto arbitrary video footage.
65%VerifiedJimeng is a series of video generation models launched by ByteDance, and Seedance 2.5 shows significant improvements over its predecessor in motion fluidity, image detail, and long-shot coherence.
65%UnverifiedTaking Seedance 2.5 as an example, if the duration and resolution are maxed out at 30 seconds and 1080P, a single generation may cost nearly 170 yuan.
50%UnverifiedAmong T0-tier models, Seedance 2.5 has the highest visual quality, with H3, the Gemini series, and other leading models following closely behind.
50%UnverifiedCloud platform credit conversion pricing: Seedance 2.5 averages approximately 2 yuan per second, Seedance 2.0 approximately 1 yuan, and H3 and the Gemini series approximately 0.6 to 0.8 yuan.
50%UnverifiedIn Seedance 2.5's draft mode, generation speed is doubled and cost reductions range between 30% and 77%.
50%UnverifiedIn the video, the spoken name for Seedance 2.5 is inconsistently mixed among Cedence 2.5, Seedance 2.5, and C-Dance 2.5.
50%UnverifiedThe AI workflow demonstrated by Bilibili UP host Jax consists of four tools in series: GPT-6 Astra, Blender, Higgs Field, and Seedance 2.5.
50%UnverifiedAsset association is the key to the success or failure of this workflow, as incorrect association will directly lead to chaotic generation results.
50%UnverifiedThe core idea of this workflow is to extract depth information and character motion from the original video, then use AI to replace the protagonist and background, achieving a video remake with consistent motion and entirely new visuals.
50%UnverifiedThe second step of the workflow uses the tool's image generation feature (referred to in the video as the "small circle" function) to generate three-view images of the protagonist character and background images.
50%UnverifiedThis modular workflow breaks tasks down into three steps—motion extraction, asset generation, and intelligent compositing—and is better suited for scenarios requiring precise motion reproduction such as dance replication, multi-person group shots, and continuous long takes.
50%UnverifiedVideo-to-video models are constrained by the input video and can reliably preserve camera angles and motion trajectories; text-to-video models are entirely text-driven and offer lower camera control precision.
50%UnverifiedThe workflow in this article involves first using GPT-6 Astra to rapidly build a 3D environment and previsualization animation from a single prompt, then using Higgsfield AI together with Seedance 2.5 to convert the rough previz into a photorealistic cinematic final cut while retaining the same camera angles and motion.
50%UnverifiedWhite model rendering was one of the capabilities prominently promoted when Seedance 2.5 launched
50%UnverifiedWhen the scene is simple and a single successful generation is expected, direct generation is more cost-effective, but as soon as multiple attempts are needed (even just two), the cost exceeds the approach that uses a gray-model reference.
50%UnverifiedThe signal flow of this workflow is: phone sensors capture 6DoF motion data → 3D software drives the virtual camera in real time → renders CG base frames and depth channel → ComfyUI receives the conditional signal → Seedance 2.5 generates the final image under the constraint conditions.
50%UnverifiedThe Seedance 2.5 model running inside ComfyUI is responsible for the final AI rendering in this workflow.
50%Unverified文生视频模型运动不可控的根源在于文本描述的歧义性，属于欠约束问题，用3D block-out约束可提供解法
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