Using ShieldGemma 2 on GCP Vertex AI

Implementation guide · Gemma 3 · Google DeepMind

Serverless

GCP Vertex AI exposes ShieldGemma 2 through model ID shieldgemma-2. 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 shieldgemma-2 — see the documentation for request format.
  3. 3
    You'll be billed Free/1M input, Free/1M output tokens. See full pricing.
API PortalDocumentationPricing

Code Examples

Install
pip install google-cloud-aiplatform
API key
GOOGLE_CLOUD_PROJECT
Model ID
shieldgemma-2

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("shieldgemma-2")
response = model.generate_content("Hello")
print(response.text)

Pricing on GCP Vertex AI

TypePrice (per 1M)
Input tokensFree
Output tokensFree

Capabilities

VisionMultimodalJSON / Tool useStructured Outputs

About ShieldGemma 2

ShieldGemma 2 is Google DeepMind's Gemma 3 model focused on content moderation and safety classification. It was released 2024-09-01.

Full model details →

Model Specs

Released2024-09-01
Parameters4B
ArchitectureDecoder Only

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Provider

GCP Vertex AI

Google Cloud Platform (GCP)

Mountain View, California, United States