Using Veo 3.1 on GCP Vertex AI

Implementation guide · Veo · Google DeepMind

Serverless

GCP Vertex AI exposes Veo 3.1 through model ID veo-3.1-generate-preview. Use the setup steps, sourced pricing, capabilities, and official provider links below to validate this route before deployment.

Last refreshed 2026-06-15. Next refresh: weekly.

Quick Start

  1. 1
    Create an account at GCP Vertex AI and generate an API key.
  2. 2
    Use the GCP Vertex AI SDK or REST API to call veo-3.1-generate-preview — see the documentation for request format.

Code Examples

Install
pip install google-cloud-aiplatform
API key
GOOGLE_CLOUD_PROJECT
Model ID
veo-3.1-generate-preview

For Google-published models use the model name directly, e.g. "gemini-2.0-flash-001". For third-party publishers (Anthropic, Meta, etc.) use the full publisher path, e.g. "publishers/anthropic/models/claude-3-5-sonnet-v2@20241022".

import os
import vertexai
from vertexai.generative_models import GenerativeModel

# Reads GOOGLE_CLOUD_PROJECT from env; authenticates via Application Default Credentials
vertexai.init(project=os.environ["GOOGLE_CLOUD_PROJECT"], location="us-central1")
model = GenerativeModel("veo-3.1-generate-preview")
response = model.generate_content("Hello")
print(response.text)

Pricing on GCP Vertex AI

Capabilities

VisionMultimodal

About Veo 3.1

Veo 3.1 is Google DeepMind's Veo model focused on video understanding and generation. It was released 2025-01-01.

Model Specs

Released2025-01-01

Provider

GCP Vertex AI

Google Cloud Platform (GCP)

Mountain View, California, United States