TwelveLabs Pegasus 1.5 在 Amazon Bedrock 上线
AWS 机器学习博客称，TwelveLabs 的 Pegasus 1.5 已在 Amazon Bedrock 上线，目前在美国西部（俄勒冈）区域提供；帖子称其可用性于 2026 年 10 月 9 日公布。AWS 表示，该视频语言模型可将长视频转为结构化、带时间戳的元数据：用户描述关注的片段类型，模型以 JSON 返回所有匹配片段。AWS 称，该模型新增视频分段、结合参考图像的多模态提示以及无需预先建立索引的即时处理。单次请求最长可分析两小时视频（Pegasus 1.2 为一小时），且通过 AWS Marketplace 计费，费用计入 TwelveLabs 名下而非 Amazon Bedrock。所提供文本未包含独立基准测试。
AWS 表示大部分视频仍难以检索且未被充分利用。其将 Pegasus 1.5 描述为无需预索引即可生成片段级时间戳元数据，用于新闻与广播存档、体育集锦和流媒体元数据。
On Oct 9, 2026 we announced the availability of TwelveLabs’ Pegasus 1.5 on Amazon Bedrock. Pegasus 1.5 is a video language model that turns long-form video into structured, timestamped metadata. You describe the moments that matter to your workflow, and the model returns every matching segment as JSON.
Video represents a significant and complex category of unstructured data, yet most of it remains unsearchable and underutilized. Extracting structured, actionable insights from that content has historically required labor-intensive manual review or fragmented toolchains.
With earlier versions of Pegasus, you can point the model at a clip, ask a question, and get an answer. Now, Pegasus 1.5 analyzes the entire video, finds every segment that matches user-defined criteria, and returns structured, timestamped metadata. It also introduces video segmentation, multimodal prompting with reference images, and on-the-fly processing.
With Pegasus 1.5 on Amazon Bedrock, you can analyze videos directly from an Amazon Simple Storage Service (Amazon S3) URI or a base64 string with no pre-indexing required, and your data remains within the AWS data boundary.
In this post, we cover what’s new in Pegasus 1.5, how the model is packaged on Amazon Bedrock, and how to send your first request. We then walk through video segmentation, structured JSON output, and multimodal prompting.
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