Endpoints supported by Amazon Bedrock - Amazon Bedrock
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Endpoints supported by Amazon Bedrock

Amazon Bedrock supports various endpoints for performing inference operations.

Inference operations

Amazon Bedrock supports the following primary two end points for performing inference programmatically:

Endpoint Supported APIs Description
bedrock-mantle.{region}.api.aws Responses API / Chat Completions API / Messages API Region-specific endpoints for making inference requests for models hosted in Amazon Bedrock using the OpenAI-compatible endpoints and the Anthropic Messages API.
bedrock-runtime.{region}.amazonaws.com InvokeModel / Converse / Chat Completions / Messages API Region-specific endpoints for making inference requests for models hosted in Amazon Bedrock using the InvokeModel/Converse/Chat Completions/Messages APIs. Read more on Amazon Bedrock Runtime APIs here.

For new applications, we recommend the bedrock-mantle endpoint. It supports OpenAI-compatible APIs (Responses and Chat Completions) and the Anthropic Messages API, includes built-in tool use and stateful conversation management, and lets you bring an existing OpenAI SDK codebase to Amazon Bedrock by changing only the base URL and API key. The bedrock-runtime endpoint remains fully supported and is the right choice when you're using the Bedrock-native InvokeModel or Converse APIs, or when the model you want isn't yet available on bedrock-mantle. To see which endpoint each model supports, see Endpoint availability.

The following tables compare what's available on each endpoint.

API support
API bedrock-runtime bedrock-mantle
InvokeModel
Converse / ConverseStream
Chat Completions (OpenAI-compatible)
Responses API (OpenAI-compatible)
Messages API (Anthropic-native)
Inference capabilities
Capability bedrock-runtime bedrock-mantle
Cross-region inference (geographic and global profiles)
Stateful conversation management
Asynchronous (long-running) inference
Client-side tool use
Server-side tool use
Pre-configured ready-to-use tools
Projects
Workspaces
Operational
Item bedrock-runtime bedrock-mantle
AWS SigV4 authentication
Bedrock API key (also works with OpenAI SDK)
Usage attribution IAM, per-request metadata tagging Projects, Workspaces

Throughput and quota approach

Each endpoint uses a different approach to managing throughput.

  • bedrock-runtime – In many traditional multi-tenant services, the architecture is designed around per-account quotas to manage fair-share access to shared resources. This is the approach used with bedrock-runtime. Each model has fixed throughput quotas (RPM and TPM) that you can request increases for. For details, see Quotas for the bedrock-runtime endpoint.

  • bedrock-mantle – This endpoint is architected with advanced scheduling and work-queueing mechanisms that deliver fair-share distribution while supporting higher initial throughput limits. This design also allows bedrock-mantle to host a broad set of models and deliver the full breadth of capabilities available across the model catalog. In most cases, requests are served immediately. In some cases, a request may be briefly queued while in-flight workloads complete and throughput becomes available. For details, see Quotas for the bedrock-mantle endpoint and Scaling and throughput best practices.

Pricing

Per-token pricing for the same model is identical on bedrock-runtime and bedrock-mantle. Choose an endpoint based on the APIs and capabilities you need, not cost. For current pricing, see Amazon Bedrock pricing.

When to choose each endpoint

Start with bedrock-mantle when you want to:

  • Use the Responses API, Chat Completions API, or Messages API with stateful, multi-turn conversations.

  • Bring existing OpenAI SDK code to Amazon Bedrock by changing only the base URL and API key.

  • Run asynchronous or long-running inference workloads.

  • Build agentic workflows with server-side tool use or pre-configured tools.

  • Use Projects (OpenAI-compatible) or Workspaces (Anthropic-compatible) to isolate workloads and track cost and usage at the application level.

Use bedrock-runtime when you want to:

Both endpoints can be used together from the same application — choose per use case.

Reduce data egress costs with VPC interface endpoints

If you are calling Amazon Bedrock from within a VPC, consider using VPC interface endpoints (AWS PrivateLink) to keep traffic within the AWS network and avoid data egress charges associated with NAT gateways or internet gateways.