Services or capabilities described in AWS documentation might vary by Region. To see the differences applicable to the AWS European Sovereign Cloud Region, see the AWS European Sovereign Cloud User Guide.

GPT-5.5

OpenAI — GPT-5.5

Model Details

GPT-5.5 is OpenAI's most capable model, designed for advanced coding, research, analysis, software operation, document workflows, and long-running agentic tasks. GPT-5.5 can understand open-ended goals, use tools, reason across longer workflows, navigate ambiguity, and carry complex tasks through to completion with less orchestration. For more information about model development and performance, see the model/service card.

Endpoints and APIs supported

The following tables show which endpoints and APIs are supported for GPT-5.5. For more information, see APIs supported by Amazon Bedrock and Inference endpoints supported by Amazon Bedrock.

Endpoint support

APIs supported on bedrock-runtime endpoint

APIs supported on bedrock-mantle endpoint

Capabilities and Features

Bedrock Features

Features supported using bedrock-runtime endpoint

Features supported using bedrock-mantle endpoint

Converse content blocks

On the bedrock-runtime endpoint, Converse accepts text and image content blocks in user messages. This model doesn't accept document content blocks, and it doesn't accept an image content block inside a toolResult. A request that includes either is rejected with a ValidationException. To send a document to this model, use the Responses API with an input_file content part instead.

Pricing

All prices are in USD per 1 million tokens for the Standard tier.

The Input — 30-minute cache write column is the price per 1 million tokens written to the prompt cache. The 30-minute figure is how long a cached prompt prefix is retained, not a quantity of tokens. For more information, see prompt caching.

Commercial In-Region prices include a 10% fee over OpenAI rates. You do not need to add this fee.

Long-context rates apply to all input and output tokens, not just tokens above 272K.

Priority and Flex tiers are not supported for this model.

Commercial Regions — short context (272K input tokens or fewer)

Commercial Regions — long context (more than 272K input tokens)

Programmatic Access

Use the following model IDs and endpoint URLs to access this model programmatically. For more information about the available APIs and endpoints, see APIs supported and Endpoints supported.

For example, if region is us-east-1 (N. Virginia), then the bedrock-mantle endpoint URL will be "https://bedrock-mantle.us-east-1.api.aws/openai/v1". On bedrock-runtime, the base URL is "https://bedrock-runtime.{region}.amazonaws.com/openai/v1" and requests must name a cross-Region inference ID — us.openai.gpt-5.5 or global.openai.gpt-5.5 — as the model.

Service Tiers

Amazon Bedrock offers multiple service tiers to match your workload requirements. Standard provides pay-per-token access with no commitment (set "service_tier": "default" or omit the field). Priority delivers the fastest response times for a price premium (set "service_tier": "priority"). Flex provides lower-cost access for flexible, non-time-sensitive workloads (set "service_tier": "flex"). Reserved provides dedicated throughput with a term commitment for predictable workloads; it is set at the account level rather than per request (contact your AWS account team to enable). For more information, see service tiers.

Regional Availability

Regional availability at a glance

Amazon Bedrock offers three inference options: In-Region keeps requests within a single Region for strict compliance, Geo Cross-Region routes across Regions within a geography (such as US, EU, and APAC) while respecting data residency, and Global Cross-Region routes anywhere worldwide when there are no residency constraints. Refer to the Regional availability by models page for more details.

Availability differs by endpoint.

Availability using the bedrock-mantle endpoint

Availability using the bedrock-runtime endpoint

Quotas and Limits

Your AWS account has default quotas to maintain the performance of the service and to ensure appropriate usage of Amazon Bedrock. The default quotas assigned to an account might be updated depending on regional factors, payment history, fraudulent usage, and/or approval of a quota increase request. For more information, see Quotas for Amazon Bedrock documentation and see the limits for the model.

Sample Code

Step 1 - AWS Account: If you have an AWS account already, skip this step. If you are new to AWS, sign up for an AWS account.

Step 2 - API key: Go to the Amazon Bedrock console and generate a long-term API key.

Step 3 - Get the SDK: To use this getting started guide, you must have Python already installed. Then install the relevant software depending on the APIs you are using.

For both APIs, choose the OpenAI SDK tab.

OpenAI SDK

pip install openai

Step 4 - Set environment variables

Configure your environment to use the API key for authentication.

bedrock-runtime

OPENAI_API_KEY="<provide your Bedrock API key>"
OPENAI_BASE_URL="https://bedrock-runtime.us-east-2.amazonaws.com/openai/v1"

bedrock-mantle

OPENAI_API_KEY="<provide your Bedrock API key>"
OPENAI_BASE_URL="https://bedrock-mantle.us-east-2.api.aws/openai/v1"

Step 5 - Run your first inference request

Save the file as bedrock-first-request.py

bedrock-mantle

Use the settings from Step 4 - Set environment variables. Choose the bedrock-mantle tab. The Chat tab uses the Chat Completions API.

Responses API

from openai import OpenAI

client = OpenAI()

response = client.responses.create(
    model="openai.gpt-5.5",
    input="Can you explain the features of Amazon Bedrock?"
)
print(response)

Chat

from openai import OpenAI

client = OpenAI()

response = client.chat.completions.create(
    model="openai.gpt-5.5",
    messages=[{"role": "user", "content": "Can you explain the features of Amazon Bedrock?"}]
)
print(response)