# Amazon — Pegasus 1.5 from TwelveLabs is now available in Amazon Bedrock

- Company: Amazon (amazon.com)
- Announced: 2026-10-19T16:49:19+00:00
- Category: availability-change
- Coverage: not counted
- Announcement: yes
- Group: announcements
- Source: https://aws.amazon.com/blogs/machine-learning/pegasus-1-5-from-twelvelabs-is-now-available-in-amazon-bedrock/
- Record: https://forck.live/items/24663-pegasus-1-5-from-twelvelabs-is-now-available-in-amazon-bedrock
- Subject: Bedrock / Nova
- Models affected: Pegasus 1.5, Pegasus 1.2

Amazon made TwelveLabs' Pegasus 1.5 video language model available in Amazon Bedrock, letting customers turn long-form video into structured, timestamped metadata without building an ingestion pipeline. The model analyzes an entire video, finds every segment matching user-defined criteria, and returns each match as JSON with start and end times and the requested fields. It adds video segmentation, multimodal prompting with reference images, and on-the-fly processing, and it handles videos up to two hours long in a single request, up from one hour in Pegasus 1.2. Videos can be sent from an Amazon S3 URI or as a base64 string of up to 25 MB, with no pre-indexing required, and Amazon says the data remains within the AWS data boundary. Customers call it on the bedrock-runtime endpoint with the InvokeModel API or InvokeModelWithResponseStream, and can tag an application inference profile to track cost by application. Pegasus 1.5 keeps the earlier model's video-to-text generation, temporal grounding and multimodal understanding, with full English support and partial support for twelve other languages.

## Evidence

Verbatim from https://aws.amazon.com/blogs/machine-learning/pegasus-1-5-from-twelvelabs-is-now-available-in-amazon-bedrock/:

> 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.

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