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bytedance 的网站图标

ByteDance: Seedance 1.5 Pro

将于 2026年11月11日 下线

bytedance/seedance-1-5-pro

基准测试比较

ByteDance's next-generation audio-visual generation model with a 4.5B parameter Dual-Branch Diffusion Transformer architecture. Seedance 1.5 Pro generates video and audio simultaneously in a single unified pass — eliminating the timing issues of sequential audio dubbing. Supports multi-language lip-sync (English, Mandarin, Japanese, Korean, Spanish, and more), cinematic camera control (pan, tilt, zoom, orbit), multi-character dialogue, and character consistency across shots. Produces clips from 4–12 seconds at up to 1080p. The number of tokens is given by (height of output video * width of output video * duration * 24) / 1024

模态
价格
from US$0.02306/second
发布时间
2026年3月23日
基准测试比较
试验场基准测试提供商性能正常运行时间应用活动文档常见问题探索

Example outputs summary for ByteDance: Seedance 1.5 Pro

  • 文本生成视频: a slow cinematic push-in on a glowing neon sign that reads "OpenRouter" in the window of a cozy coffee shop on a rainy night, rain streaking down the glass, reflections rippling on wet pavement — 使用 ByteDance: Seedance 1.5 Pro 生成

试验场

基准测试

标准化评测得分,以及此模型针对共用基准测试提示词的实际输出。百分比越高越好,每项排名显示此模型在该来源所评测的模型中的位置。

基准测试得分摘要: ByteDance: Seedance 1.5 Pro (Artificial Analysis)
来源基准测试得分
Artificial AnalysisSeedance 1.5 pro Elo1,256

Benchmark outputs summary for ByteDance: Seedance 1.5 Pro

  • Traffic light: A fixed camera on a single traffic light against a plain grey sky. The light starts red, changes to green, and then changes to amber, in that exact order, each colour holding for a clearly visible moment. No other objects, no camera movement, no cuts. (在此提示词中并列第 第 18 名,共 28 名)
  • Five candles: A fixed straight-on shot of five lit candles in a row on a dark table. The candles go out one at a time from left to right until all five are out. No hand or person visible, no camera movement, no cuts. (在此提示词中并列第 第 17 名,共 28 名)
  • Wrong-way escalator: A fixed shot of an empty upward-moving escalator. A single red rubber ball bounces down the escalator steps from top to bottom, against the direction of the escalator's movement, and exits the frame at the bottom. No people, no cuts. (在此提示词中并列第 第 17 名,共 28 名)
  • Frozen crowd: A busy pedestrian plaza in daylight where every single person stands perfectly still like a statue for the entire clip. Only the flags on the buildings move in the wind. No person moves at all, not even slightly. Fixed camera, no cuts. (在此提示词中并列第 第 22 名,共 28 名)
  • Sign stays readable: A slow steady dolly toward a shop window sign reading exactly "OPEN 7 DAYS - COFFEE & BAGELS - EST. 2003". The text stays sharp, correctly spelled and unchanged for the whole clip as the camera approaches. No other text in the frame. (在此提示词中排名第 第 27 名,共 28 名)
  • Glass of water: A fixed close shot of a full glass of water on a wooden table. A rolling orange bumps into the glass. The glass tips over away from the camera, water spills across the table and spreads outward, and the empty glass rolls slightly and comes to rest. No hands, no cuts. (在此提示词中并列第 第 15 名,共 28 名)
  • Domino run: A fixed side-on shot of exactly eight upright black dominoes in a straight evenly spaced row on a white surface. The leftmost domino tips right and the whole row falls in a single left-to-right chain until all eight are flat. No hands after the start, no cuts. (在此提示词中并列第 第 23 名,共 28 名)
  • Mirror walk: A fixed shot of a large wall mirror in a bright dance studio. A man in a green t-shirt walks from left to right in front of the mirror. His reflection matches his movement exactly, mirrored, for the entire clip. No cuts. (在此提示词中并列第 第 4 名,共 28 名)
  • Behind the pillar: A fixed camera on a wide walkway with a single thick concrete pillar in the middle. A woman in a yellow raincoat walks at a steady pace from the left edge to the right edge, passing behind the pillar. She is briefly hidden, then reappears on the other side wearing exactly the same clothes, and exits frame right. No cuts. (在此提示词中并列第 第 1 名,共 28 名)
  • Steaming mug: Thin steam rises from the coffee and drifts slowly to the right. Everything else holds still: the mug and its painted design, the table, the background, the lighting and the framing stay exactly as in the reference. Static camera. No cuts. (在此提示词中排名第 第 24 名,共 27 名)
  • Walk out: The person from the reference turns and walks out of the frame to the right. Their face, hair and clothing stay exactly as in the reference until they exit. The background does not change. No cuts. (在此提示词中并列第 第 15 名,共 26 名)
  • Continuous shot: A single continuous shot, no cuts, orbiting exactly once, slowly, around a stone statue of a horse in an empty courtyard. The statue stays centred the whole time and the camera ends where it started. Nothing else enters the frame. (在此提示词中并列第 第 25 名,共 28 名)

提供商

此模型由一家提供商托管。OpenRouter 将每个请求直接转发给该提供商,无需做出路由决策。

性能

吞吐量是模型生成内容的速度(每秒 token 数,越高越好)。延迟是完整的往返时间(越低越好)。TTFT 是首个 token 的响应时间,即您看到内容出现前需要等待的时间(越低越好)。

正常运行时间

正常运行时间是指过去 3 天中至少有一家提供商响应请求的时间百分比。可用性是指成功提供推理服务的时间百分比。OpenRouter 会持续监控,并在某家提供商返回错误时使用次优提供商。

应用

向此模型发送最多流量的公开应用。这能很好地反映实际生产工作负载的情况,也能提示此模型最适合哪些用例。

活动

此模型的 token 用量和请求流量随时间的变化。

API

可直接用于调用此模型的代码。OpenRouter 的 API 与 OpenAI 兼容——大多数 SDK 只需替换基础 URL 即可使用。切换模型时,唯一需要更改的是下方的模型标识符。

目前无法通过 EU 区域内路由使用。 区域内路由文档

文档

在 OpenRouter 上使用 ByteDance: Seedance 1.5 Pro 构建应用的指南、实用教程、博客文章和工具。

  • Best Image-to-Video AI Models in 2026: Cost, Resolution, and Control博客文章

探索更多模型

具备视觉能力的 AI 模型:用于图像理解的多模态大语言模型集合视频生成模型集合视频模型排行榜排名
端到端延迟
US$2.40US$0.05184US$1.20US$0.0259246.98s
95.45%
端到端延迟
46.98秒

P50,最佳提供商

正常运行时间(3 天)模型可访问。请求已路由至提供商。
100.00%
可用性(3 天)模型通过任意提供商返回了推理结果。错误和空响应均计为失败。
99.22%

过去 3 天的可用性

最近 72 小时
可用性 99.22%
3 天前2 天前昨天现在

过去 24 小时的可用性

OpenRouter Availability
99.12%

当上游提供商发生错误时,如果您的请求筛选条件允许,我们可以通过路由到另一家健康的提供商来恢复服务。您可以通过以下接口以编程方式访问各提供商的正常运行时间数据: 端点 API。了解更多有关我们的 负载均衡和提供商路由选项。

1.
https://komrz4.mykomrz.com/ 的网站图标
komrz4
新增
0token
2.
https://shinjibot.com/ 的网站图标
ShinjiBot
新增
0token
3.
https://github.com/novastrike 的网站图标
Nova Strike asset pipeline
新增
0token
4.
https://local.studio/ 的网站图标
Writing Studio Research
新增
0token
5.
https://crelivo.local/prompt-library-ai 的网站图标
Prompt Library AI
新增
0token

暂无图表数据

常见问题

ByteDance's next-generation audio-visual generation model with a 4.5B parameter Dual-Branch Diffusion Transformer architecture. Seedance 1.5 Pro generates video and audio simultaneously in a single unified pass — eliminating the timing issues of sequential audio dubbing.

OpenRouter 上的 Seedance 1.5 Pro 文档包括 Best Image-to-Video AI Models in 2026: Cost, Resolution, and Control 博客文章。快速入门介绍了 API 密钥和您的首次请求,API 参考列出了所有参数。

Seedance 1.5 Pro 的费用为 Video (with audio) 的价格为 从 US$0.02306/second(480p)到 US$0.4666/second(4K)、Video (no audio) 的价格为 从 US$0.01153/second(480p)到 US$0.2333/second(4K)、Video Tokens (with audio) 的价格为 US$2.40/M tokens和Video Tokens (no audio) 的价格为 US$1.20/M tokens。

Seedance 1.5 Pro 支持 4–12 秒 的片段、可通过 first frame和last frame 图像进行引导和生成匹配的音轨.

Seedance 1.5 Pro 接受 文本和图像 作为输入,并返回 视频。

Seedance 2.0 Mini, Seedance 2.5, Seedance 2.0 及另外 1 个 是 ByteDance 的其他 视频 模型。

Seedance 1.5 Pro 于 2026年3月23日 发布。

更多模型,来自 bytedance

Seedance 2.0 Mini

Seedance 2.0 Mini is a video generation model from ByteDance. It supports text-to-video, image-to-video with first and last frame control, and multimodal reference-to-video with image, video, and audio inputs. It supports 480p and 720p output for 4-15 second videos. The number of tokens is given by (height of output video * width of output video * duration * 24) / 1024

视频from US$0.03363/second
Seedance 2.5

Seedance 2.5 is a video generation model from ByteDance. It is suited for long-form storytelling, multimodal reference-based generation, video editing, and video extension. It supports first-frame and first-and-last-frame control, up to 50 image, video, and audio reference assets, optional generated audio, and multilingual audiovisual generation.

视频from US$0.1028/second
Seedance 2.0 Fast

Seedance 2.0 Fast is a video generation model from ByteDance. It supports text-to-video, image-to-video with first and last frame control, and multimodal reference-to-video. It prioritizes generation speed and lower cost over maximum output quality. The number of tokens is given by (height of output video * width of output video * duration * 24) / 1024

视频from US$0.04035/second
Seedance 2.0

Seedance 2.0 is a video generation model from ByteDance. It supports text-to-video, image-to-video with first and last frame control, and multimodal reference-to-video. It is particularly strong at preserving character consistency, visual style, and camera movement from reference material. The number of tokens is given by (height of output video * width of output video * duration * 24) / 1024

视频from US$0.06726/second
Seedance 1.5 Pro

ByteDance's next-generation audio-visual generation model with a 4.5B parameter Dual-Branch Diffusion Transformer architecture. Seedance 1.5 Pro generates video and audio simultaneously in a single unified pass — eliminating the timing issues of sequential audio dubbing. Supports multi-language lip-sync (English, Mandarin, Japanese, Korean, Spanish, and more), cinematic camera control (pan, tilt, zoom, orbit), multi-character dialogue, and character consistency across shots. Produces clips from 4–12 seconds at up to 1080p. The number of tokens is given by (height of output video * width of output video * duration * 24) / 1024

视频from US$0.02306/second
Seed OSS 36B Instruct

Seed-OSS-36B-Instruct is a 36B-parameter instruction-tuned reasoning language model from ByteDance’s Seed team, released under Apache-2.0. The model is optimized for general instruction following with strong performance in reasoning, mathematics, coding, tool use/agentic workflows, and multilingual tasks, and is intended for international (i18n) use cases. It is not currently possible to control the reasoning effort.

文本131K 上下文
UI-TARS 7B

UI-TARS-1.5 is a multimodal vision-language agent optimized for GUI-based environments, including desktop interfaces, web browsers, mobile systems, and games. Built by ByteDance, it builds upon the UI-TARS framework with reinforcement learning-based reasoning, enabling robust action planning and execution across virtual interfaces.

This model achieves state-of-the-art results on a range of interactive and grounding benchmarks, including OSworld, WebVoyager, AndroidWorld, and ScreenSpot. It also demonstrates perfect task completion across diverse Poki games and outperforms prior models in Minecraft agent tasks. UI-TARS-1.5 supports thought decomposition during inference and shows strong scaling across variants, with the 1.5 version notably exceeding the performance of earlier 72B and 7B checkpoints.

文本128K 上下文US$0.10 / US$0.20