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If your application calls the OpenAI API or the Anthropic Claude API, AWS recommends two Amazon Bedrock routes. OpenAI integrations should use the OpenAI-compatible Responses API or Chat Completions API on Bedrock Runtime. Anthropic integrations should use the Anthropic Messages API. Both routes keep a familiar request shape, but they are not drop-in replacements. Feature support depends on the model, the endpoint (Runtime or Mantle), and the region, so check each of those against what your application actually uses, then test against your own traffic before cutover.
Choose the Bedrock route that matches your source API
Start from the API your code already calls. That determines which compatible surface is the lowest-friction target.
| Source integration | Recommended Bedrock route | Key characteristic |
|---|---|---|
| OpenAI, conversation state kept on the API side | Bedrock Runtime OpenAI-compatible Responses API | Described by AWS as stateful |
| OpenAI, conversation history kept by your application | Bedrock Runtime OpenAI-compatible Chat Completions API | Described by AWS as stateless multi-turn chat |
| Anthropic Claude Messages API | Anthropic Messages API on Runtime (recommended for new applications) or Mantle | Uses Anthropic’s request and response format |
| Model-neutral AWS integration | Converse or Invoke on Runtime | May require more request and response adaptation than keeping an OpenAI or Anthropic shape |
Migrating an OpenAI integration
AWS identifies Bedrock Runtime’s OpenAI-compatible Responses API or Chat Completions API as the recommended route for OpenAI integrations (AWS Build with Amazon Bedrock APIs). The choice between them comes down to where conversation state lives.
Responses API for stateful conversations
AWS describes the Responses API as stateful (AWS Responses API). AWS’s API overview also recommends Responses as the long-term direction for OpenAI integrations (AWS APIs supported by Amazon Bedrock). Choose it if your application already depends on conversation state carried across turns and you want to align with that direction. Before you commit, confirm the exact endpoint and model pairing, because Runtime and Mantle differ for this API (see the endpoint section below).
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Chat Completions API for application-managed history
AWS describes Chat Completions as stateless multi-turn chat. The model sees the conversation history your application sends with each request, so this route suits code that already manages history on its side and needs the smallest change.
Migrating an Anthropic Claude integration
For Anthropic integrations, AWS identifies the Anthropic Messages API as the migration route. It uses Anthropic’s request and response format and is available through both Runtime and Mantle (AWS Inference using Anthropic Messages API). AWS recommends Runtime for new applications (AWS Endpoints supported by Amazon Bedrock).
Request model access first
AWS states that model access must be requested for Claude models. Complete this for the account and region you plan to deploy to before you test anything else, or your first calls will fail on access rather than on your code.
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Choose an authentication method
- Runtime: AWS SigV4 credentials through the AWS SDK, Bedrock API keys, or a short-term Bedrock bearer token.
- Mantle: Bedrock API key or SigV4 authentication.
Set the API version correctly for each endpoint
The version is passed differently on each endpoint. On Runtime, the InvokeModel request body carries it as anthropic_version with the value bedrock-2023-05-31:
"anthropic_version": "bedrock-2023-05-31"If you use the Anthropic SDK configured with the Runtime base URL, the SDK adds the required version for you. On Mantle, the version is a request header instead: anthropic-version: 2023-06-01.
Check regional availability for each endpoint
Runtime Messages API availability depends on Claude model availability in each region. Mantle Messages API availability depends on the regions Mantle supports. The two endpoints are governed by different criteria, so check each one separately before you pick a region.
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Runtime or Mantle: where shared API names stop matching features
Runtime and Mantle both expose the Responses, Chat Completions, and Messages APIs, but overlapping names do not mean identical capabilities (AWS Endpoints supported by Amazon Bedrock).
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|---|---|---|
| Invoke | Supported | Not listed among Mantle’s supported APIs |
| Converse | Supported | Not listed among Mantle’s supported APIs |
| Responses | Supported | Supported |
| Chat Completions | Supported | Supported |
| Messages | Supported | Supported |
AWS documents endpoint-specific differences that you should verify before implementation:
- Structured outputs are not available on Mantle’s Messages API (AWS API compatibility).
- Runtime’s Responses API is synchronous and does not support server-side tools.
- Background inference and server-side tools are the cases where AWS says Mantle may be needed (AWS Endpoints supported by Amazon Bedrock, AWS Responses API).
Check the live endpoint comparison and the per-model compatibility table for the exact model, endpoint, and API combination you plan to use. AWS updates model names, regional availability, endpoint capabilities, and authentication details, so confirm them in the current documentation at the time you implement.
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Native AWS interfaces: Converse and Invoke
If you do not need to preserve an OpenAI or Anthropic request shape, AWS offers two native options (AWS API compatibility, AWS APIs supported by Amazon Bedrock).
Converse
Converse provides a unified interface across models that support messages. It suits applications that may switch models later, since one request format covers them.
Invoke
Invoke gives direct control over model requests and responses. It supports generation beyond text, including images and embeddings.
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Either option may require more adaptation of your request and response handling than keeping an OpenAI or Anthropic shape. Plan that work as code changes, not as a configuration switch.
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Use this list to decide which route works. AWS documentation establishes these as the dimensions that differ between routes. Whether each one changes for your application is something only your code and traffic can show.
- Target model and the endpoint and API combinations it supports.
- Region, and whether you need cross-region routing.
- Streaming behavior and the event format your application parses.
- Tool calls, structured outputs, multimodal inputs, and stateful conversation behavior.
- Background or asynchronous work, and any server-side tools.
- Guardrails, logging, access control, and cost attribution.
- Authentication and model-access setup.
These are checks, not a list of changes every migration must make.
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AWS Workspaces for the Anthropic-compatible Messages API on Mantle provide application isolation, observability, access control, and cost tracking (AWS Workspaces (Anthropic-compatible)). For Runtime workloads that do not need Workspaces, AWS points to Converse or Invoke with inference profiles for isolation, tagging, and cost tracking (AWS Workspaces (Anthropic-compatible)). Decide which of these controls you need and set them up before production traffic moves, so cost data is attributable from the first request.
Cutover sequence
- Record your current request and response schemas, SDK version, prompt and tool behavior, streaming path, retry logic, and error handling. This is a recommended inventory, not an AWS-mandated checklist.
- Choose the target model, endpoint, and API route against the AWS API compatibility and AWS Endpoints supported by Amazon Bedrock pages.
- Configure access, credentials, region, and, for the Messages API, the version requirement for the endpoint you chose (AWS Inference using Anthropic Messages API).
- Adapt endpoint configuration and request and response handling so the application’s existing behavior requirements still hold.
- Run regression checks on representative traffic covering output quality, tool calls, streaming, error paths, latency, and cost. AWS documentation does not provide performance or cost figures for your workload, so these numbers must come from your own measurements.
- Roll out in stages and monitor quality, reliability, usage, and cost. Retire the source integration only after those results hold.
Comparison criteria for choosing between routes
When more than one route is viable, compare them on the same axes: API and request-shape continuity, target model availability, endpoint-only capabilities and limitations, authentication and account setup, region and routing, statefulness and tools, and observability, isolation, and cost attribution. The documentation covers each of these. Measured cost and output quality are the one axis it cannot answer for you, so measure them on your own workload before choosing.
The Bottom Line
Treat the compatible API shape as the starting point, not the finish line. Cut over only when every feature your application uses maps to a supported model, endpoint, region, and authentication combination, and your own regression run shows acceptable behavior and cost.
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