Claude Fable 5

Anthropic — Claude Fable 5

Model Details

Claude Fable 5 is Anthropic's next-generation model for complex knowledge work and coding, capable of sustained autonomous operation across multi-day tasks. It plans across stages, delegates to sub-agents, and self-verifies its work.

• Model launch date: June 9, 2026

• Model EOL date: N/A

• End User License Agreements and Terms of Use: View

• Model lifecycle: Active

• Context window: 1M tokens

• Max output tokens: 128K

• Sampling parameters: temperature must be 1.0 or unset; top_p must be ≥ 0.99 and < 1.0, or unset; top_k is not supported

• Reasoning: Supported (adaptive thinking is always on and cannot be disabled; effort level is configurable)

• Knowledge cutoff: January 2026

• Marketplace product ID: prod-h6swdfybvty7y

Input Modalities	Output Modalities	APIs supported	Endpoints supported
Audio	Embedding	Responses	bedrock-runtime
Image	Image	Chat Completions	bedrock-mantle
Speech	Speech	Invoke
Text	Text	Converse
Video	Video	Messages

Capabilities and Features

Bedrock Features

Features supported using bedrock-runtime endpoint

Supported	Not Supported
Response streaming Abuse detection Guardrails Prompt optimization Knowledge base Model evaluation Prompt management Flows Agents Count tokens	Intelligent prompt routing

Bedrock Features

Features supported using bedrock-mantle endpoint

Supported	Not Supported
Response streaming Abuse detection Count tokens	Guardrails Prompt optimization Knowledge base Model evaluation Prompt management Flows Agents Intelligent prompt routing

Prompt caching

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

Prompt caching supported	Min tokens per cache checkpoint	Max cache checkpoints per request	Supported TTL	Fields that accept prompt cache checkpoint
Yes	1,024	4	5 minutes, 1 hour	system, messages, and tools

Content Restrictions

Claude Fable 5 includes blocking classifiers for dual-use content in cybersecurity and biology. When a classifier blocks a request, the API returns a standard HTTP 200 response with stop_reason: "refusal" and a stop_details object containing the restriction category. Refusal rates on this model are materially higher than on previous Claude models.

Customers should handle stop_reason: "refusal" as a primary response path. Prompt-stage refusals (blocked before inference begins) are not billed. Mid-stream refusals (blocked after partial output) are billed for tokens generated before the block.

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.

Endpoint	Model ID	In-Region endpoint URL	Geo inference ID	Global inference ID
bedrock-runtime	anthropic.claude-fable-5	https://bedrock-runtime.{region}.amazonaws.com	us.anthropic.claude-fable-5 eu.anthropic.claude-fable-5	global.anthropic.claude-fable-5
bedrock-mantle	anthropic.claude-fable-5	https://bedrock-mantle.{region}.api.aws/anthropic/v1/messages	N/A	N/A

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".

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.

Standard	Priority	Flex	Reserved

Regional Availability

Regional availability at a glance

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 (US, EU, etc.) for higher throughput while respecting data residency, and Global Cross-Region routes anywhere worldwide for maximum throughput when there are no residency constraints. Refer to the Regional availability page for more details.

Region	In-Region	Geo	Global
us-east-1 (N. Virginia)
us-east-2 (Ohio)
us-west-1 (N. California)
us-west-2 (Oregon)
ca-central-1 (Canada)
ca-west-1 (Calgary)
eu-central-1 (Frankfurt)
eu-central-2 (Zurich)
eu-north-1 (Stockholm)
eu-south-1 (Milan)
eu-south-2 (Spain)
eu-west-1 (Ireland)
eu-west-2 (London)
eu-west-3 (Paris)
ap-east-2 (Taipei)
ap-northeast-1 (Tokyo)
ap-northeast-2 (Seoul)
ap-northeast-3 (Osaka)
ap-south-1 (Mumbai)
ap-south-2 (Hyderabad)
ap-southeast-1 (Singapore)
ap-southeast-2 (Sydney)
ap-southeast-3 (Jakarta)
ap-southeast-4 (Melbourne)
ap-southeast-5 (Malaysia)
ap-southeast-6 (New Zealand)
ap-southeast-7 (Thailand)
il-central-1 (Tel Aviv)
me-central-1 (UAE)
me-south-1 (Bahrain)
af-south-1 (Cape Town)
sa-east-1 (São Paulo)
mx-central-1 (Mexico)

Data Retention

To use this model, you must opt in to provider data sharing by setting your data retention mode to provider_data_share via the Data Retention API. There is no console UI for this setting at launch. For more information, see Amazon Bedrock abuse detection.

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 details, please refer to 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.

Invoke & Converse

pip install boto3

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

AWS_BEARER_TOKEN_BEDROCK="<provide your Bedrock API key>"

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

import json
import boto3

client = boto3.client('bedrock-runtime', region_name='us-east-1')
response = client.invoke_model(
    modelId='anthropic.claude-fable-5',
    body=json.dumps({
        'messages': [{'role': 'user', 'content': 'Can you explain the features of Amazon Bedrock?'}],
        'max_tokens': 1024
    })
)
print(json.loads(response['body'].read()))

Messages

pip install -U "anthropic[bedrock]"

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

AWS_BEARER_TOKEN_BEDROCK="<provide your Bedrock API key>"

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

from anthropic import AnthropicBedrockMantle

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

message = client.messages.create(
    model="anthropic.claude-fable-5",
    max_tokens=1024,
    messages=[{"role": "user", "content": "Hello, Claude"}],
)

print(message.content[0].text)