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Credit goes to docs.anthropic.com

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Prerequisites

Before configuring Claude Code with Vertex AI, ensure you have:
  • A Google Cloud Platform (GCP) account with billing enabled
  • A GCP project with Vertex AI API enabled
  • Access to desired Claude models (e.g., Claude Sonnet 4)
  • Google Cloud SDK (gcloud) installed and configured
  • Quota allocated in desired GCP region

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Region Configuration

Claude Code can be used with both Vertex AI global and regional endpoints.
Vertex AI may not support the Claude Code default models on all regions. You may need to switch to a supported region or model.
Vertex AI may not support the Claude Code default models on global endpoints. You may need to switch to a regional endpoint or supported model.

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Setup

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1. Enable Vertex AI API

Enable the Vertex AI API in your GCP project: 
# Set your project ID
gcloud config set project YOUR-PROJECT-ID

# Enable Vertex AI API
gcloud services enable aiplatform.googleapis.com

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2. Request model access

Request access to Claude models in Vertex AI:
  1. Navigate to the Vertex AI Model Garden
  2. Search for “Claude” models
  3. Request access to desired Claude models (e.g., Claude Sonnet 4)
  4. Wait for approval (may take 24-48 hours)

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3. Configure GCP credentials

Claude Code uses standard Google Cloud authentication. For more information, see Google Cloud authentication documentation.
When authenticating, Claude Code will automatically use the project ID from the ANTHROPIC_VERTEX_PROJECT_ID environment variable. To override this, set one of these environment variables: GCLOUD_PROJECT, GOOGLE_CLOUD_PROJECT, or GOOGLE_APPLICATION_CREDENTIALS.

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4. Configure Claude Code

Set the following environment variables: 
# Enable Vertex AI integration
export CLAUDE_CODE_USE_VERTEX=1
export CLOUD_ML_REGION=global
export ANTHROPIC_VERTEX_PROJECT_ID=YOUR-PROJECT-ID

# Optional: Disable prompt caching if needed
export DISABLE_PROMPT_CACHING=1

# When CLOUD_ML_REGION=global, override region for unsupported models
export VERTEX_REGION_CLAUDE_3_5_HAIKU=us-east5

# Optional: Override regions for other specific models
export VERTEX_REGION_CLAUDE_3_5_SONNET=us-east5
export VERTEX_REGION_CLAUDE_3_7_SONNET=us-east5
export VERTEX_REGION_CLAUDE_4_0_OPUS=europe-west1
export VERTEX_REGION_CLAUDE_4_0_SONNET=us-east5
export VERTEX_REGION_CLAUDE_4_1_OPUS=europe-west1
Prompt caching is automatically supported when you specify the cache_control ephemeral flag. To disable it, set DISABLE_PROMPT_CACHING=1. For heightened rate limits, contact Google Cloud support.
When using Vertex AI, the /login and /logout commands are disabled since authentication is handled through Google Cloud credentials.

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5. Model configuration

Claude Code uses these default models for Vertex AI:
Model typeDefault value
Primary modelclaude-sonnet-4@20250514
Small/fast modelclaude-3-5-haiku@20241022
To customize models: 
export ANTHROPIC_MODEL='claude-opus-4-1@20250805'
export ANTHROPIC_SMALL_FAST_MODEL='claude-3-5-haiku@20241022'

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IAM configuration

Assign the required IAM permissions: The roles/aiplatform.user role includes the required permissions:
  • aiplatform.endpoints.predict - Required for model invocation
  • aiplatform.endpoints.computeTokens - Required for token counting
For more restrictive permissions, create a custom role with only the permissions above. For details, see Vertex IAM documentation.
We recommend creating a dedicated GCP project for Claude Code to simplify cost tracking and access control.

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1M token context window

Claude Sonnet 4 supports the 1M token context window on Vertex AI.
The 1M token context window is currently in beta. To use the extended context window, include the context-1m-2025-08-07 beta header in your Vertex AI requests.

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Troubleshooting

If you encounter quota issues:
  • Check current quotas or request quota increase through Cloud Console
If you encounter “model not found” 404 errors:
  • Confirm model is Enabled in Model Garden
  • Verify you have access to the specified region
  • If using CLOUD_ML_REGION=global, check that your models support global endpoints in Model Garden under “Supported features”. For models that don’t support global endpoints, either:
    • Specify a supported model via ANTHROPIC_MODEL or ANTHROPIC_SMALL_FAST_MODEL, or
    • Set a regional endpoint using VERTEX_REGION_<MODEL_NAME> environment variables
If you encounter 429 errors:
  • For regional endpoints, ensure the primary model and small/fast model are supported in your selected region
  • Consider switching to CLOUD_ML_REGION=global for better availability

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Additional resources