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.

Claude Opus 4.8

Anthropic — Claude Opus 4.8

Model Details

Claude Opus 4.8 is an Anthropic Opus model optimized for coding, agents, and deeper reasoning in enterprise workflows.

Capabilities and Features

Bedrock Features

Features supported using bedrock-mantle endpoint

Features supported using bedrock-runtime endpoint

Prompt caching

For more information, see Prompt caching for faster model inference.

Computer use using bedrock-runtime and bedrock-mantle endpoints

For more information, see Computer use.

Pricing

For pricing, please refer to the Amazon Bedrock Pricing page.

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-runtime endpoint URL will be "https://bedrock-runtime.us-east-1.amazonaws.com" and for bedrock-mantle will be "https://bedrock-mantle.us-east-1.api.aws/anthropic/v1/messages".

Service Tiers

Amazon Bedrock offers multiple service tiers to match your workload requirements. Standard provides pay-per-token access with no commitment. Priority offers higher throughput with a time-based commitment. Flex provides lower-cost access for flexible, non-time-sensitive workloads. Reserved provides dedicated throughput with a term commitment for predictable workloads. For more information, see service tiers.

Regional Availability

Regional availability at a glance

Bedrock offers three inference options:

For more details, see the Regional availability by models page.

Geo inference details

Geo: US

Geo Inference ID: us.anthropic.claude-opus-4-8

Geo: EU

Geo Inference ID: eu.anthropic.claude-opus-4-8

Geo: JP

Geo Inference ID: jp.anthropic.claude-opus-4-8

Geo: AU

Geo Inference ID: au.anthropic.claude-opus-4-8

Global inference details

Quotas and Limits

Your AWS account has default quotas for Amazon Bedrock. These quotas might change depending on regional factors, payment history, or approval of a quota increase request. For more details, see Quotas for Amazon Bedrock and the limits for the model.

Default quotas for Claude Opus 4.8 are 20M input TPM and 4M output TPM on bedrock-mantle and 30M TPM on bedrock-runtime for each supported region. Claude Opus 4.8 does not have a requests-per-minute (RPM) quota; throttling is governed solely by the token-per-minute (TPM) quotas above.

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.

Messages API

pip install -U "anthropic[bedrock]"

Invoke/Converse API

pip install boto3

Step 4 - Set environment variables: Configure your environment to use the API key for authentication.

Messages API

AWS_BEARER_TOKEN_BEDROCK="<provide your Bedrock API key>"

Invoke/Converse API

AWS_BEARER_TOKEN_BEDROCK="<provide your Bedrock API key>"

Step 5 - Run your first inference request: Save the file as bedrock-first-request.py

Messages API

from anthropic import AnthropicBedrockMantle

client = AnthropicBedrockMantle(aws_region="us-east-1")

message = client.messages.create(
    model="anthropic.claude-opus-4-8",
    max_tokens=1024,
    messages=[{"role": "user", "content": "Can you explain the features of Amazon Bedrock?"}],
)

print(message.content[0].text)

Invoke API

import json
import boto3

client = boto3.client('bedrock-runtime', region_name='us-east-1')
response = client.invoke_model(
    modelId='anthropic.claude-opus-4-8',
    body=json.dumps({
            'anthropic_version': 'bedrock-2023-05-31',
            'messages': [{ 'role': 'user', 'content': 'Can you explain the features of Amazon Bedrock?'}],
            'max_tokens': 1024
    })
)
print(json.loads(response['body'].read()))

Converse API

import boto3

client = boto3.client('bedrock-runtime', region_name='us-east-1')
response = client.converse(
    modelId='anthropic.claude-opus-4-8',
    messages=[
        {
            'role': 'user',
            'content': [{'text': 'Can you explain the features of Amazon Bedrock?'}]
        }
    ]
)
print(response)