strands-agents · zastrowm · Jul 15, 2025 · Jul 15, 2025
diff --git a/docs/examples/deploy_to_eks/README.md b/docs/examples/deploy_to_eks/README.md
@@ -17,7 +17,7 @@ The example deploys a weather forecaster application that runs as a containerize
 - Either:
     - [Podman](https://podman.io/) installed and running
     - (or) [Docker](https://www.docker.com/) installed and running
-- Amazon Bedrock Anthropic Claude 3.7 model enabled in your AWS environment   
+- Amazon Bedrock Anthropic Claude 4 model enabled in your AWS environment   
   You'll need to enable model access in the Amazon Bedrock console following the [AWS documentation](https://docs.aws.amazon.com/bedrock/latest/userguide/model-access-modify.html)
 
 ## Project Structure

diff --git a/docs/user-guide/concepts/model-providers/amazon-bedrock.md b/docs/user-guide/concepts/model-providers/amazon-bedrock.md
@@ -100,7 +100,7 @@ session = boto3.Session(
 
 # Create a Bedrock model with the custom session
 bedrock_model = BedrockModel(
-    model_id="us.anthropic.claude-3-7-sonnet-20250219-v1:0",
+    model_id="anthropic.claude-sonnet-4-20250514-v1:0",
     boto_session=session
 )
 ```
@@ -109,7 +109,7 @@ For complete details on credential configuration and resolution, see the [boto3
 
 ## Basic Usage
 
-The [`BedrockModel`](../../../api-reference/models.md#strands.models.bedrock) provider is used by default when creating a basic Agent, and uses the [Claude 3.7 Sonnet](https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters-anthropic-claude-37.html) model by default. This basic example creates an agent using this default setup:
+The [`BedrockModel`](../../../api-reference/models.md#strands.models.bedrock) provider is used by default when creating a basic Agent, and uses the [Claude 4 Sonnet](https://aws.amazon.com/blogs/aws/claude-opus-4-anthropics-most-powerful-model-for-coding-is-now-in-amazon-bedrock/) model by default. This basic example creates an agent using this default setup:
 
 ```python
 from strands import Agent
@@ -125,7 +125,7 @@ You can specify which Bedrock model to use by passing in the model ID string dir
 from strands import Agent
 
 # Create an agent with a specific model by passing the model ID string
-agent = Agent(model="us.anthropic.claude-3-7-sonnet-20250219-v1:0")
+agent = Agent(model="anthropic.claude-sonnet-4-20250514-v1:0")
 
 response = agent("Tell me about Amazon Bedrock.")
 ```
@@ -156,7 +156,7 @@ The [`BedrockModel`](../../../api-reference/models.md#strands.models.bedrock) su
 
 | Parameter                                                                                                                                                                                             | Description                                                                                                    | Default                                                                                              |
 | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------- |
-| [`model_id`](https://docs.aws.amazon.com/bedrock/latest/userguide/models-supported.html)                                                                                                              | The Bedrock model identifier                                                                                   | "us.anthropic.claude-3-7-sonnet-20250219-v1:0"                                                       |
+| [`model_id`](https://docs.aws.amazon.com/bedrock/latest/userguide/models-supported.html)                                                                                                              | The Bedrock model identifier                                                                                   | "anthropic.claude-sonnet-4-20250514-v1:0"                                                       |
 | [`boto_session`](https://boto3.amazonaws.com/v1/documentation/api/latest/reference/core/session.html)                                                                                                 | Boto Session to use when creating the Boto3 Bedrock Client                                                     | Boto Session with region: "us-west-2"                                                                |
 | [`boto_client_config`](https://botocore.amazonaws.com/v1/documentation/api/latest/reference/config.html)                                                                                              | Botocore Configuration used when creating the Boto3 Bedrock Client                                             | -                                                                                                    |
 | [`region_name`](https://docs.aws.amazon.com/general/latest/gr/bedrock.html)                                                                                                                           | AWS region to use for the Bedrock service                                                                      | "us-west-2"                                                                                          |
@@ -195,7 +195,7 @@ boto_config = BotocoreConfig(
 
 # Create a configured Bedrock model
 bedrock_model = BedrockModel(
-    model_id="us.anthropic.claude-3-7-sonnet-20250219-v1:0",
+    model_id="anthropic.claude-sonnet-4-20250514-v1:0",
     region_name="us-east-1",  # Specify a different region than the default
     temperature=0.3,
     top_p=0.8,
@@ -220,7 +220,7 @@ in order to use these models. Both modes provide the same event structure and fu
 ```python
 # Streaming model (default)
 streaming_model = BedrockModel(
-    model_id="us.anthropic.claude-3-7-sonnet-20250219-v1:0",
+    model_id="anthropic.claude-sonnet-4-20250514-v1:0",
     streaming=True,  # This is the default
 )
 
@@ -243,7 +243,7 @@ from strands.models import BedrockModel
 
 # Create a Bedrock model that supports multimodal inputs
 bedrock_model = BedrockModel(
-    model_id="us.anthropic.claude-3-7-sonnet-20250219-v1:0"
+    model_id="anthropic.claude-sonnet-4-20250514-v1:0"
 )
 agent = Agent(model=bedrock_model)
 
@@ -278,7 +278,7 @@ from strands.models import BedrockModel
 
 # Using guardrails with BedrockModel
 bedrock_model = BedrockModel(
-    model_id="us.anthropic.claude-3-7-sonnet-20250219-v1:0",
+    model_id="anthropic.claude-sonnet-4-20250514-v1:0",
     guardrail_id="your-guardrail-id",
     guardrail_version="DRAFT",
     guardrail_trace="enabled",  # Options: "enabled", "disabled", "enabled_full"
@@ -320,7 +320,7 @@ from strands.models import BedrockModel
 
 # Using system prompt caching with BedrockModel
 bedrock_model = BedrockModel(
-    model_id="us.anthropic.claude-3-7-sonnet-20250219-v1:0",
+    model_id="anthropic.claude-sonnet-4-20250514-v1:0",
     cache_prompt="default"
 )
 
@@ -350,7 +350,7 @@ from strands_tools import calculator, current_time
 
 # Using tool caching with BedrockModel
 bedrock_model = BedrockModel(
-    model_id="us.anthropic.claude-3-7-sonnet-20250219-v1:0",
+    model_id="anthropic.claude-sonnet-4-20250514-v1:0",
     cache_tools="default"
 )
 
@@ -426,7 +426,7 @@ You can update the model configuration during runtime:
 ```python
 # Create the model with initial configuration
 bedrock_model = BedrockModel(
-    model_id="us.anthropic.claude-3-7-sonnet-20250219-v1:0",
+    model_id="anthropic.claude-sonnet-4-20250514-v1:0",
     temperature=0.7
 )
 
@@ -478,7 +478,7 @@ from strands.models import BedrockModel
 
 # Create a Bedrock model with reasoning configuration
 bedrock_model = BedrockModel(
-    model_id="us.anthropic.claude-3-7-sonnet-20250219-v1:0",
+    model_id="anthropic.claude-sonnet-4-20250514-v1:0",
     additional_request_fields={
         "thinking": {
             "type": "enabled",
@@ -555,13 +555,13 @@ This typically indicates that the model requires Cross-Region Inference, as docu
 Instead of: 
 
 ```
-anthropic.claude-3-7-sonnet-20250219-v1:0
+anthropic.claude-sonnet-4-20250514-v1:0
 ```
 
 Use: 
 
 ```
-us.anthropic.claude-3-7-sonnet-20250219-v1:0
+us.anthropic.claude-sonnet-4-20250514-v1:0
 ```
 
 ## Related Resources

diff --git a/docs/user-guide/concepts/model-providers/anthropic.md b/docs/user-guide/concepts/model-providers/anthropic.md
@@ -25,7 +25,7 @@ model = AnthropicModel(
     },
     # **model_config
     max_tokens=1028,
-    model_id="claude-3-7-sonnet-20250219",
+    model_id="claude-sonnet-4-20250514",
     params={
         "temperature": 0.7,
     }
@@ -49,7 +49,7 @@ The `model_config` configures the underlying model selected for inference. The s
 |  Parameter | Description | Example | Options |
 |------------|-------------|---------|---------|
 | `max_tokens` | Maximum number of tokens to generate before stopping | `1028` | [reference](https://docs.anthropic.com/en/api/messages#body-max-tokens)
-| `model_id` | ID of a model to use | `claude-3-7-sonnet-20250219` | [reference](https://docs.anthropic.com/en/api/messages#body-model)
+| `model_id` | ID of a model to use | `claude-sonnet-4-20250514` | [reference](https://docs.anthropic.com/en/api/messages#body-model)
 | `params` | Model specific parameters | `{"max_tokens": 1000, "temperature": 0.7}` | [reference](https://docs.anthropic.com/en/api/messages)
 
 ## Troubleshooting
@@ -82,7 +82,7 @@ model = AnthropicModel(
         "api_key": "<KEY>",
     },
     max_tokens=1028,
-    model_id="claude-3-7-sonnet-20250219",
+    model_id="claude-sonnet-4-20250514",
     params={
         "temperature": 0.7,
     }

diff --git a/docs/user-guide/observability-evaluation/evaluation.md b/docs/user-guide/observability-evaluation/evaluation.md
@@ -68,7 +68,7 @@ from strands_tools import calculator
 
 # Create agent with specific configuration
 agent = Agent(
-    model="us.anthropic.claude-3-7-sonnet-20250219-v1:0",
+    model="us.anthropic.claude-sonnet-4-20250514-v1:0",
     system_prompt="You are a helpful assistant specialized in data analysis.",
     tools=[calculator]
 )
@@ -94,7 +94,7 @@ with open("test_cases.json", "r") as f:
     test_cases = json.load(f)
 
 # Create agent
-agent = Agent(model="us.anthropic.claude-3-7-sonnet-20250219-v1:0")
+agent = Agent(model="us.anthropic.claude-sonnet-4-20250514-v1:0")
 
 # Run tests and collect results
 results = []
@@ -138,7 +138,7 @@ agent = Agent(model="anthropic.claude-3-5-sonnet-20241022-v2:0")
 
 # Create an evaluator agent with a stronger model
 evaluator = Agent(
-    model="us.anthropic.claude-3-7-sonnet-20250219-v1:0",
+    model="us.anthropic.claude-sonnet-4-20250514-v1:0",
     system_prompt="""
     You are an expert AI evaluator. Your job is to assess the quality of AI responses based on:
     1. Accuracy - factual correctness of the response
@@ -199,7 +199,7 @@ from strands import Agent
 from strands_tools import calculator, file_read, current_time
 # Create agent with multiple tools
 agent = Agent(
-    model="us.anthropic.claude-3-7-sonnet-20250219-v1:0",
+    model="us.anthropic.claude-sonnet-4-20250514-v1:0",
     tools=[calculator, file_read, current_time],
     record_direct_tool_call = True
 )

diff --git a/docs/user-guide/observability-evaluation/logs.md b/docs/user-guide/observability-evaluation/logs.md
@@ -99,7 +99,7 @@ DEBUG | strands.event_loop.error_handler | message_index=<5> | found message wit
 Logs related to interactions with foundation models:
 
 ```
-DEBUG | strands.models.bedrock | config=<{'model_id': 'anthropic.claude-3-7-sonnet-20250219-v1:0'}> | initializing
+DEBUG | strands.models.bedrock | config=<{'model_id': 'us.anthropic.claude-4-sonnet-20250219-v1:0'}> | initializing
 WARNING | strands.models.bedrock | bedrock threw context window overflow error
 DEBUG | strands.models.bedrock | Found blocked output guardrail. Redacting output.
 ```

diff --git a/docs/user-guide/observability-evaluation/traces.md b/docs/user-guide/observability-evaluation/traces.md
@@ -106,7 +106,7 @@ from strands import Agent
 # Option 1: Skip StrandsTelemetry if global tracer provider and/or meter provider are already configured
 # (your existing OpenTelemetry setup will be used automatically)
 agent = Agent(
-    model="us.anthropic.claude-3-7-sonnet-20250219-v1:0",
+    model="us.anthropic.claude-sonnet-4-20250514-v1:0",
     system_prompt="You are a helpful AI assistant"
 )
 
@@ -131,7 +131,7 @@ strands_telemetry.setup_otlp_exporter().setup_console_exporter()  # Chaining sup
 
 # Create agent (tracing will be enabled automatically)
 agent = Agent(
-    model="us.anthropic.claude-3-7-sonnet-20250219-v1:0",
+    model="us.anthropic.claude-sonnet-4-20250514-v1:0",
     system_prompt="You are a helpful AI assistant"
 )
 
@@ -200,7 +200,7 @@ Strands traces include rich attributes that provide context for each operation:
 | `gen_ai.agent.name` | Name of the agent |
 | `gen_ai.user.message` | Formatted prompt sent to the model |
 | `gen_ai.assistant.message` | Formatted assistant prompt sent to the model |
-| `gen_ai.request.model` | Model ID (e.g., "us.anthropic.claude-3-7-sonnet-20250219-v1:0") |
+| `gen_ai.request.model` | Model ID (e.g., "us.anthropic.claude-sonnet-4-20250514-v1:0") |
 | `gen_ai.event.start_time` | When model invocation began |
 | `gen_ai.event.end_time` | When model invocation completed |
 | `gen_ai.choice` | Response from the model (may include tool calls) |
@@ -340,7 +340,7 @@ strands_telemetry.setup_console_exporter()   # Print traces to console
 
 # Create agent
 agent = Agent(
-    model="us.anthropic.claude-3-7-sonnet-20250219-v1:0",
+    model="us.anthropic.claude-sonnet-4-20250514-v1:0",
     system_prompt="You are a helpful AI assistant"
 )
 

diff --git a/docs/user-guide/quickstart.md b/docs/user-guide/quickstart.md
@@ -35,15 +35,15 @@ pip install strands-agents-tools strands-agents-builder
 
 ## Configuring Credentials
 
-Strands supports many different model providers. By default, agents use the Amazon Bedrock model provider with the Claude 3.7 model.
+Strands supports many different model providers. By default, agents use the Amazon Bedrock model provider with the Claude 4 model.
 
-To use the examples in this guide, you'll need to configure your environment with AWS credentials that have permissions to invoke the Claude 3.7 model. You can set up your credentials in several ways:
+To use the examples in this guide, you'll need to configure your environment with AWS credentials that have permissions to invoke the Claude 4 model. You can set up your credentials in several ways:
 
 1. **Environment variables**: Set `AWS_ACCESS_KEY_ID`, `AWS_SECRET_ACCESS_KEY`, and optionally `AWS_SESSION_TOKEN`
 2. **AWS credentials file**: Configure credentials using `aws configure` CLI command
 3. **IAM roles**: If running on AWS services like EC2, ECS, or Lambda, use IAM roles
 
-Make sure your AWS credentials have the necessary permissions to access Amazon Bedrock and invoke the Claude 3.7 model. You'll need to enable model access in the Amazon Bedrock console following the [AWS documentation](https://docs.aws.amazon.com/bedrock/latest/userguide/model-access-modify.html).
+Make sure your AWS credentials have the necessary permissions to access Amazon Bedrock and invoke the Claude 4 model. You'll need to enable model access in the Amazon Bedrock console following the [AWS documentation](https://docs.aws.amazon.com/bedrock/latest/userguide/model-access-modify.html).
 
 ## Project Setup
 
@@ -170,15 +170,15 @@ agent("Hello!")
 
 ### Identifying a configured model
 
-Strands defaults to the Bedrock model provider using Claude 3.7 Sonnet. The model your agent is using can be retrieved by accessing [`model.config`](../api-reference/models.md#strands.models.model.Model.get_config):
+Strands defaults to the Bedrock model provider using Claude 4 Sonnet. The model your agent is using can be retrieved by accessing [`model.config`](../api-reference/models.md#strands.models.model.Model.get_config):
 
 ```python
 from strands import Agent
 
 agent = Agent()
 
 print(agent.model.config)
-# {'model_id': 'us.anthropic.claude-3-7-sonnet-20250219-v1:0'}
+# {'model_id': 'us.anthropic.claude-sonnet-4-20250514-v1:0'}
 ```
 
 You can specify a different model in two ways:
@@ -194,7 +194,7 @@ The simplest way to specify a model is to pass the model ID string directly:
 from strands import Agent
 
 # Create an agent with a specific model by passing the model ID string
-agent = Agent(model="us.anthropic.claude-3-7-sonnet-20250219-v1:0")
+agent = Agent(model="anthropic.claude-sonnet-4-20250514-v1:0")
 ```
 
 ### Amazon Bedrock (Default)
@@ -208,7 +208,7 @@ from strands.models import BedrockModel
 
 # Create a BedrockModel
 bedrock_model = BedrockModel(
-    model_id="us.anthropic.claude-3-7-sonnet-20250219-v1:0",
+    model_id="anthropic.claude-sonnet-4-20250514-v1:0",
     region_name="us-west-2",
     temperature=0.3,
 )