Claude Sonnet 5

Anthropic — Claude Sonnet 5

Model Details

Claude Sonnet 5 is the most capable Sonnet model from Anthropic, built for coding, agents, and professional work at scale. It brings near-Opus intelligence to the model teams run every day, with the same balance of capability, cost, and speed teams already rely on Sonnet for.

Endpoints and APIs supported

The following tables show which endpoints and APIs are supported for Claude Sonnet 5. For more information, see APIs supported by Amazon Bedrock and 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

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, see 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 the Region is us-east-1 (N. Virginia), the bedrock-runtime endpoint URL is "https://bedrock-runtime.us-east-1.amazonaws.com" and the bedrock-mantle endpoint URL is "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 (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:

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

Data residency

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.

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: Open 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 aws-bedrock-token-generator

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 Anthropic
from aws_bedrock_token_generator import provide_token

token = provide_token(region="us-east-1")

client = Anthropic(
    base_url="https://bedrock-runtime.us-east-1.amazonaws.com/anthropic",
    api_key=token,
)

response = client.messages.create(
    model="global.anthropic.claude-sonnet-5",
    max_tokens=1024,
    messages=[{"role": "user", "content": "Can you explain the features of Amazon Bedrock?"}],
)

print(response)

Invoke API

import json
import boto3

client = boto3.client('bedrock-runtime', region_name='us-east-1')
response = client.invoke_model(
    modelId='anthropic.claude-sonnet-5',
    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-sonnet-5',
    messages=[
        {
            'role': 'user',
            'content': [{'text': 'Can you explain the features of Amazon Bedrock?'}]
        }
    ]
)
print(response)