OpenAI models in Amazon Bedrock

Amazon Bedrock makes supported OpenAI models available through AWS-managed infrastructure. This deployment path is useful when your organization wants to keep procurement, identity, regional controls, and related cloud operations in AWS.

Amazon Bedrock availability differs from the OpenAI API. Confirm the supported model, AWS Region, feature set, and pricing path for your workload before you deploy.

How Bedrock availability works

OpenAI models in Amazon Bedrock run through an AWS-managed deployment path with Responses API compatibility for supported models and capabilities. Your application still uses OpenAI model behavior, but AWS owns the surrounding cloud control plane, including account access, regional availability, and billing.

Use Bedrock when you need:

• AWS-native procurement and billing.
• AWS-managed identity, access, and account controls.
• Deployment in supported AWS Regions for customers with cloud-location requirements.

Use the OpenAI API directly when you need the broadest feature coverage, the latest first-party platform capabilities, or functionality unavailable in Bedrock.

Make Responses API requests

To send OpenAI SDK requests through Amazon Bedrock, use the Bedrock-aware SDK client and select the AWS Region and model ID for your deployment:

• Instantiate BedrockOpenAI instead of the default OpenAI client. The client derives the regional Mantle base URL from the AWS Region.
• This guide's examples use us-east-2, which resolves to https://bedrock-mantle.us-east-2.api.aws/openai/v1.
• Use a Bedrock model ID with the openai. prefix, such as openai.gpt-5.6-sol.

This example uses openai.gpt-5.6-sol in us-east-2. Use a supported model and AWS Region combination for your Bedrock deployment.

The following example uses a Bedrock API key stored as AWS_BEARER_TOKEN_BEDROCK. See Amazon Bedrock API keys for information about generating and using a Bedrock API key. The SDK reads the token from your environment.

Send a Responses API request through Amazon Bedrock

import { BedrockOpenAI } from "openai";

const client = new BedrockOpenAI({
  awsRegion: "us-east-2",
});

const response = await client.responses.create({
  model: "openai.gpt-5.6-sol",
  input: "Write a haiku about cloud infrastructure.",
});

console.log(response.output_text);

from openai import BedrockOpenAI

client = BedrockOpenAI(aws_region="us-east-2")

response = client.responses.create(
    model="openai.gpt-5.6-sol",
    input="Write a haiku about cloud infrastructure.",
)

print(response.output_text)

curl "https://bedrock-mantle.us-east-2.api.aws/openai/v1/responses" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $AWS_BEARER_TOKEN_BEDROCK" \
  -d '{
    "model": "openai.gpt-5.6-sol",
    "input": "Write a haiku about cloud infrastructure."
  }'

For long-running applications, pass a token provider instead of a static API key. The SDK calls the provider before each request. The AWS token-generator packages return a cached short-term key when the current key is valid and generate a new key when needed. They use the AWS credential chain, which can include credentials configured with aws login.

Install the token-generator package for your SDK:

npm install @aws/bedrock-token-generator
pip install aws-bedrock-token-generator

Send a request with refreshable Bedrock credentials

import { getTokenProvider } from "@aws/bedrock-token-generator";
import { BedrockOpenAI } from "openai";

const client = new BedrockOpenAI({
  awsRegion: "us-east-2",
  bedrockTokenProvider: getTokenProvider(),
});

const response = await client.responses.create({
  model: "openai.gpt-5.6-sol",
  input: "Write a haiku about cloud infrastructure.",
});

console.log(response.output_text);

from aws_bedrock_token_generator import provide_token
from openai import BedrockOpenAI

client = BedrockOpenAI(
    aws_region="us-east-2",
    bedrock_token_provider=provide_token,
)

response = client.responses.create(
    model="openai.gpt-5.6-sol",
    input="Write a haiku about cloud infrastructure.",
)

print(response.output_text)

Availability and operations

Availability depends on AWS Region and model. The initial launch scope is more limited than the OpenAI API, so check model support by AWS Region before rollout.

Amazon Bedrock provides Responses API-compatible inference for supported OpenAI models in supported AWS Regions. AWS manages authentication, account access, procurement, and billing.

AWS Regions are physical deployment locations, which differ from OpenAI data residency jurisdictions. Teams with residency requirements should evaluate the Bedrock Region itself and the corresponding AWS terms.

Data access and retention

Amazon Bedrock uses separate controls for operator access and data retention:

• Zero operator access (ZOA) means AWS operators have no technical mechanism to sign in to Mantle's underlying compute systems or access customer data, including inference prompts and completions.
• Zero data retention (ZDR) means AWS does not write model inputs or outputs to durable storage when the effective retention mode is none.

For OpenAI models in Amazon Bedrock, AWS does not share request or response content with OpenAI when the effective retention mode is default or none.

Configure Bedrock data retention for your AWS account or project.

Under the default retention mode, retention depends on the model and request settings. For specific OpenAI GPT models, AWS retains classifier-flagged traffic for up to 30 days for automated offline abuse detection. Responses API requests use store: true by default. AWS retains the response, including its input and output, for 30 days so you can retrieve it or reference it in a later request. See Amazon Bedrock abuse detection for the current model list and retention details.

If you need full ZDR for a model that requires retention, contact your AWS account manager to discuss eligibility. AWS evaluates ZDR access for each account and model. If AWS approves access, confirm that none appears in the model's allowed_modes, then set the account or project retention mode to none. Setting store: false does not guarantee ZDR. When the effective retention mode is none, AWS rejects store: true, and background mode is unavailable.

If AWS detects apparent CSAM in an image input, AWS may move the flagged input or output outside the ZOA environment and store and review it only to determine whether it is CSAM. AWS may also file a report with national authorities.

Responses API feature availability

Amazon Bedrock supports a subset of Responses API capabilities available through the OpenAI API. This table describes feature availability as of the date below. It excludes transient availability and service status.

The information below represents feature availability as of July 13, 2026. Model and Region availability can also change. For the latest information, see the AWS documentation for OpenAI models in Amazon Bedrock and model support by AWS Region.

Client-side tool_search is distinct from hosted tools and remote MCP server support. Hosted tools run through OpenAI-operated service infrastructure and are unavailable on Amazon Bedrock.

GPT-5.4, GPT-5.5, and GPT-5.6 have a 272,000-token context window on Amazon Bedrock. Amazon Bedrock rejects requests that exceed this limit. See the AWS model cards for current model-specific limits.

Treat feature parity as workload-specific. If your application depends on a specific tool, response mode, or service tier, test that behavior through Bedrock before you commit to the deployment path.

Authentication and operations

Amazon Bedrock uses AWS-managed access controls. Your AWS administrator controls which accounts, roles, or temporary credentials can reach the supported model deployment. The exact authentication flow depends on the Bedrock configuration your organization uses.

Plan for AWS-owned operational checks such as:

• Account and model access configuration.
• Region-specific deployment approval.
• Temporary credential or token validity.
• AWS quota, logging, and support workflows.

Pricing

AWS bills Amazon Bedrock usage. Bedrock-specific pricing can differ from direct OpenAI API pricing, including regional processing premiums or other AWS-specific commercial terms.

See API pricing for direct OpenAI API pricing. For Bedrock pricing, use the AWS pricing materials published for the Bedrock deployment you plan to use.

Next steps

• Confirm your supported model and AWS Region in Amazon Bedrock.
• Verify the exact API features your workload needs.
• Compare Bedrock pricing and direct API pricing before launch.
• For setup in ChatGPT Work and Codex, see Use ChatGPT Work and Codex with Amazon Bedrock.