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Claude Sonnet 5.5 available on Amazon Bedrock and Claude Platform on AWS

Amazon Bedrock has added Claude Sonnet 5.5 to its lineup, along with Claude Platform on AWS. The new model is positioned as a smarter, more efficient version of the Sonnet family, aimed at focused coding and knowledge work. The release comes with lower cost per task for most work and faster speed, according to the post.

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Key points

  • Claude Sonnet 5.5 released on Amazon Bedrock and Claude Platform on AWS
  • Model offers lower cost per task and faster speed for coding and knowledge work
  • Users can access via Amazon Bedrock console or programmatically with Anthropic SDK and AWS CLI

Sonnet 5.5 improves on Sonnet 5 by producing more polished documents and visuals, such as one‑pager summaries, architecture diagrams, and slide decks. It also checks results against stated requirements and is suited for workloads that run continuously or at scale, including first‑response alerts, monitoring of agents, SQL generation, UI/UX testing, and fast coding agents in IDEs with a fixed spend cap. Across the enterprise it supports scoped analysis, short spreadsheet edits, and routine document tasks for large user populations.

To try the model, users can open the Amazon Bedrock console, go to Test Playground, and select Sonnet 5.5. Programmatically, the model can be called via the Anthropic Messages API against bedrock‑runtime through the Anthropic SDK, or via the Invoke and Converse APIs on bedrock‑runtime using the AWS CLI or AWS SDK. Prerequisites include an active AWS account with Amazon Bedrock access, AWS CLI installed and configured, Python 3.10+, Boto3 installed, and IAM permissions bedrock:InvokeModel and bedrock:InvokeModelWithResponseStream. Usage, performance, and costs can be monitored through Amazon CloudWatch and AWS Cost Explorer.

Model pages: Claude Sonnet 5.5 → · Claude Opus 5.5 →

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Full story from AWS Machine Learning Blog · by Dani Mitchell primary sourceOpen source ↗

Introducing Claude Sonnet 5.5 on AWS

AWS Machine Learning Blog · 28 September 2026

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This text was published by AWS Machine Learning Blog and written by Dani Mitchell. It is reproduced here with attribution so you can read it in full; the rights remain with the publisher. Read it at the source ↗

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