Seedance2

Guide

Seedance 2.0 Technical Architecture

This page summarizes technical aspects of Seedance 2.0 from public sources (e.g. official blog, third-party API docs). It is not an official specification and may not reflect the latest implementation.

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Source basis and reading boundary

These guides are written as third-party reference summaries, not official product documentation or support content.

Source basis

Model and inputs

Public technical descriptions refer to a unified multimodal audio-video joint generation architecture. Inputs: text plus up to 9 images, 3 video clips, and 3 audio tracks (subject to platform limits). Text drives scene, action, and style; images/videos/audio provide reference for composition, motion, camera, and sound. The @ tag system in prompts lets you assign roles to each asset.

Outputs

Video: typically 4–15 seconds selectable; resolution up to 2K (2048×1080); aspect ratios often include 16:9, 9:16, 1:1, 4:3, 3:4, 21:9 and adaptive. Audio: native stereo, generated jointly with video (not post-dubbed); lip-sync supported for multiple languages in public reports. Video extension and in-place editing are supported in many workflows.

Audio-video joint generation

Third-party technical write-ups describe a dual-branch diffusion transformer that processes visual and audio streams in a single inference, enabling lip-sync, sound effects, and music to be aligned with the picture from the start. Consistency across shots is achieved by reusing the same reference image(s) and referring to them in the prompt.

Frequently asked questions

Is there an API?

Yes. BytePlus/Volcano Engine and third-party providers (e.g. fal.ai, Seedance2API-style docs) offer API access. Workflow is often async: submit job, poll status, download result. Check the official Seedance project page and your provider’s developer docs for current API offerings and pricing.

What resolution does Seedance 2.0 support?

According to public reports, native output goes up to 2K (2048×1080), with common aspect ratios including 16:9, 9:16, 1:1, and others. See our comparison guide for how this compares to other tools.

How does the model handle multi-modal inputs?

According to public technical descriptions, the model uses a unified text-image-video-audio joint architecture. A single request can combine up to 9 images, 3 videos, and 3 audio tracks plus text; the @ tag system in prompts assigns roles to each asset. See our multimodal guide for more.

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