The adoption and implementation of generative AI inference has increased with organizations building more operational workloads that use AI capabilities in production at scale. To help customers achieve the scale of their generative AI applications, Amazon Bedrock offers cross-Region inference (CRIS) profiles. CRIS is a powerful feature that organizations can use to seamlessly distribute inference processing across multiple AWS Regions. This capability helps you get higher throughput while you’re building at scale and helps keep your generative AI applications responsive and reliable even under heavy load.
We are excited to introduce Global cross-Region inference for Amazon Bedrock and bring Anthropic Claude models in India. Amazon Bedrock now offers Anthropic’s Claude Opus 4.6, Claude Sonnet 4.6, and Claude Haiku 4.5 through Amazon Bedrock Global cross-Region inference (CRIS) for customers operating in India. These frontier models deliver a massive 1-million token context window and advanced agentic capabilities, allowing your applications to process vast datasets and complex workflows with unprecedented speed and intelligence. With this launch, customers using ap-south-1 (Mumbai) and ap-south-2 (Hyderabad) can access Anthropic’s latest Claude models on Amazon Bedrock while benefiting from global inference capacity and highly available inference managed by Amazon Bedrock. With global CRIS, customers can scale inference workloads seamlessly, improve resiliency, and reduce operational complexity. In this post, you will discover how to use Amazon Bedrock’s Global cross-Region Inference for Claude models in India. We will guide you through the capabilities of each Claude model variant and how to get started with a code example to help you start building generative AI applications immediately.
Core functionality of Global cross-Region inference
Global cross-Region inference helps organizations manage unplanned traffic bursts by using compute resources across inference capacity across commercial AWS Regions (Regions other than the AWS GovCloud (US) Regions and the China Regions) globally. This section explores how the Global cross-Region inference feature works and the technical mechanisms that power its functionality.
Understanding inference profiles
Global cross-Region inference is offered through Inference profiles. Inference profiles operate on two key concepts:
- Source Region – The Region from which the API request is made
- Destination Region – A Region to which Amazon Bedrock can route the request for inference
To use Anthropic models, Amazon Bedrock offers out of the box Global Inference profiles. For example:
- Opus 4.6:
- Sonnet 4.6:
- Opus 4.5: <0/>
- <0/>
- <0/>
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