Source: https://docs.claude.com/en/docs/build-with-claude/claude-on-vertex-ai

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Claude on Vertex AI

Home Developer Guide API Reference Model Context Protocol (MCP) Resources Release Notes

On this page

• Install an SDK for accessing Vertex AI

• Accessing Vertex AI

• Model Availability

• API model IDs

• Making requests

• Activity logging

• Feature support

• Global vs regional endpoints

• When to use each option

• Implementation

• Additional resources

The Vertex API for accessing Claude is nearly-identical to the Messages API and supports all of the same options, with two key differences:

• In Vertex, model is not passed in the request body. Instead, it is specified in the Google Cloud endpoint URL.
• In Vertex, anthropic_version is passed in the request body (rather than as a header), and must be set to the value vertex-2023-10-16.

Vertex is also supported by Anthropic’s official client SDKs . This guide will walk you through the process of making a request to Claude on Vertex AI in either Python or TypeScript. Note that this guide assumes you have already have a GCP project that is able to use Vertex AI. See using the Claude 3 models from Anthropic for more information on the setup required, as well as a full walkthrough.

​

Install an SDK for accessing Vertex AI

First, install Anthropic’s client SDK for your language of choice.

Python

TypeScript

Copy

pip install -U google-cloud-aiplatform "anthropic[vertex]"

​

Accessing Vertex AI

​

Model Availability

Note that Anthropic model availability varies by region. Search for “Claude” in the Vertex AI Model Garden or go to Use Claude 3 for the latest information.

​

API model IDs

| Model | Vertex AI API model ID | | --- | --- | | Claude Sonnet 4.5 | claude-sonnet-4-5@20250929Copied! | | Claude Sonnet 4 | claude-sonnet-4@20250514Copied! | | Claude Sonnet 3.7 ⚠️ | claude-3-7-sonnet@20250219Copied! | | Claude Opus 4.1 | claude-opus-4-1@20250805Copied! | | Claude Opus 4 | claude-opus-4@20250514Copied! | | Claude Opus 3 ⚠️ | claude-3-opus@20240229Copied! | | Claude Haiku 4.5 | claude-haiku-4-5@20251001Copied! | | Claude Haiku 3.5 | claude-3-5-haiku@20241022Copied! | | Claude Haiku 3 | claude-3-haiku@20240307Copied! |

​

Making requests

Before running requests you may need to run gcloud auth application-default login to authenticate with GCP. The following examples shows how to generate text from Claude on Vertex AI:

Python

TypeScript

Shell

Copy

from anthropic import AnthropicVertex

project_id = "MY_PROJECT_ID"
region = "global"

client = AnthropicVertex(project_id=project_id, region=region)

message = client.messages.create(
    model="claude-sonnet-4-5@20250929",
    max_tokens=100,
    messages=[\
        {\
            "role": "user",\
            "content": "Hey Claude!",\
        }\
    ],
)
print(message)

See our client SDKs and the official Vertex AI docs for more details.

​

Activity logging

Vertex provides a request-response logging service that allows customers to log the prompts and completions associated with your usage. Anthropic recommends that you log your activity on at least a 30-day rolling basis in order to understand your activity and investigate any potential misuse.

Turning on this service does not give Google or Anthropic any access to your content.

​

Feature support

You can find all the features currently supported on Vertex here .

​

Global vs regional endpoints

Starting with Claude Sonnet 4.5 and all future models, Google Vertex AI offers two endpoint types:

• Global endpoints: Dynamic routing for maximum availability
• Regional endpoints: Guaranteed data routing through specific geographic regions

Regional endpoints include a 10% pricing premium over global endpoints.

This applies to Claude Sonnet 4.5 and future models only. Older models (Claude Sonnet 4, Opus 4, and earlier) maintain their existing pricing structures.

​

When to use each option

Global endpoints (recommended):

• Provide maximum availability and uptime
• Dynamically route requests to regions with available capacity
• No pricing premium
• Best for applications where data residency is flexible
• Only supports pay-as-you-go traffic (provisioned throughput requires regional endpoints)

Regional endpoints:

• Route traffic through specific geographic regions
• Required for data residency and compliance requirements
• Support both pay-as-you-go and provisioned throughput
• 10% pricing premium reflects infrastructure costs for dedicated regional capacity

​

Implementation

Using global endpoints (recommended): Set the region parameter to "global" when initializing the client:

Python

TypeScript

Copy

from anthropic import AnthropicVertex

project_id = "MY_PROJECT_ID"
region = "global"

client = AnthropicVertex(project_id=project_id, region=region)

message = client.messages.create(
    model="claude-sonnet-4-5@20250929",
    max_tokens=100,
    messages=[\
        {\
            "role": "user",\
            "content": "Hey Claude!",\
        }\
    ],
)
print(message)

Using regional endpoints: Specify a specific region like "us-east1" or "europe-west1":

Python

TypeScript

Copy

from anthropic import AnthropicVertex

project_id = "MY_PROJECT_ID"
region = "us-east1"  # Specify a specific region

client = AnthropicVertex(project_id=project_id, region=region)

message = client.messages.create(
    model="claude-sonnet-4-5@20250929",
    max_tokens=100,
    messages=[\
        {\
            "role": "user",\
            "content": "Hey Claude!",\
        }\
    ],
)
print(message)

​

Additional resources

• Google Vertex AI pricing: cloud.google.com/vertex-ai/generative-ai/pricing

• Claude models documentation: Claude on Vertex AI

• Google blog post: Global endpoint for Claude models

• Anthropic pricing details: Pricing documentation

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