Introducing cross-Region inference for OpenAI GPT-5.6 models on Amazon Bedrock

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This post is co-written with Chris Dickens from OpenAI. Amazon Bedrock now offers OpenAI GPT-5.6 models on Amazon Bedrock in more than 25 AWS Regions, with cross-Region inference. Three GPT-5.6 variants support cross-Region inference, Sol, Terra, and Luna, each tuned for a different balance of capability and cost. Cross-Region inference (CRIS) in Amazon Bedrock works through inference profiles, which define a model and the AWS Regions to which Amazon Bedrock can route a request. You call the profile from a source Region, and Amazon Bedrock routes the request to a destination Region using compute in that Region. CRIS is primarily a capacity mechanism. By allowing requests to draw on a broader pool of compute rather than being bound to one Region’s available capacity, it improves throughput and helps maintain consistent performance under load. A geographic inference profile routes requests within a single geography, so you can scale while keeping data processed within that geography. For GPT-5.6, this launch introduces US geographic (US cross-Region inference) and global CRIS. A global inference profile routes across all supported AWS commercial Regions where the model is deployed, based on real-time capacity, giving you broad access to Amazon Bedrock capacity. In this post, we walk through an overview of GPT-5.6 models on Amazon Bedrock, how geographic and global cross-Region inference work for these models, and how to call them from the Amazon Bedrock console and in code with the OpenAI Responses API, the OpenAI Chat Completions API, and the Amazon Bedrock Converse API. …

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