TwelveLabs Pegasus 1.5 available on Amazon Bedrock
An AWS Machine Learning Blog post says TwelveLabs' Pegasus 1.5 is available on Amazon Bedrock in the US West (Oregon) Region, and that availability was announced on Oct 9, 2026. According to AWS, the video language model turns long-form video into structured, timestamped metadata: users describe the segments they care about and the model returns every match as JSON. AWS says it adds video segmentation, multimodal prompting with reference images and on-the-fly processing with no pre-indexing. A single request can analyze up to two hours of video, up from one hour in Pegasus 1.2, and the model is billed through AWS Marketplace under TwelveLabs rather than Amazon Bedrock. The supplied text does not include independent benchmarks.
AWS says most video remains unsearchable and underutilized. It presents Pegasus 1.5 as producing segment-level timestamped metadata without a pre-indexing step, for news and broadcast archives, sports highlights and streaming metadata.
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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