Using Gemini 3 Pro Preview on GCP Vertex AI

Implementation guide · Gemini 3 · Google DeepMind

Serverless

GCP Vertex AI exposes Gemini 3 Pro Preview through model ID gemini-3-pro-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
Create an account at GCP Vertex AI and generate an API key.
2
Use the GCP Vertex AI SDK or REST API to call gemini-3-pro-preview — see the documentation for request format.
3
You'll be billed $2.00/1M input, $12.00/1M output tokens. See full pricing.

API Portal Documentation Pricing

Code Examples

Install

pip install google-cloud-aiplatform

API key

GOOGLE_CLOUD_PROJECT

Model ID

gemini-3-pro-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("gemini-3-pro-preview")
response = model.generate_content("Hello")
print(response.text)

Pricing on GCP Vertex AI

Type	Price (per 1M)
Input tokens	$2.00
Output tokens	$12.00

Capabilities

VisionMultimodalJSON / Tool useStructured Outputs

About Gemini 3 Pro Preview

Deprecated/shut down March 9, 2026. Vertex: $0.20/$12.00 (<=200K), $0.40/$18.00 (>200K). Migrate to Gemini 3.1 Pro.

Full model details →

Model Specs

Released2025-09-01

Context1m

ArchitectureDecoder Only

Google Cloud Platform (GCP)

Mountain View, California, United States