Google Vertex AI

Google Vertex AI is Google Cloud's enterprise machine learning platform. It provides access to Gemini models, custom model training, and MLOps tools with enterprise-grade security, compliance, and scalability. Use Vertex AI when you need production-ready AI with Google Cloud's infrastructure backing it.

Vertex AI vs Google AI Studio

Getting Started

1. Set Up Google Cloud

Create a Google Cloud project and enable the Vertex AI API in the Cloud Console.

2. Authenticate

gcloud auth application-default login

Or set a service account key:

GOOGLE_APPLICATION_CREDENTIALS=/path/to/service-account-key.json

3. Install and Use

npm install @ai-sdk/google-vertex

import { vertex } from '@ai-sdk/google-vertex';
import { generateText } from 'ai';

const { text } = await generateText({
  model: vertex('gemini-2.0-flash'),
  prompt: 'Summarize the key benefits of cloud computing.',
});

Image Generation with Imagen

Vertex AI provides access to Google's Imagen models:

import { vertex } from '@ai-sdk/google-vertex';
import { experimental_generateImage as generateImage } from 'ai';

const { image } = await generateImage({
  model: vertex.image('imagen-3.0-generate-001'),
  prompt: 'A professional product photo of a coffee mug',
});

When to Use Vertex AI

• Your organization requires data residency compliance (GDPR, HIPAA)
• You need enterprise SLAs for AI model availability
• You want to fine-tune or train custom models
• You are already using Google Cloud infrastructure
• You need advanced MLOps features like model monitoring and A/B testing

Resources

• Vertex AI Documentation
• AI SDK Google Vertex Provider
• Vertex AI Pricing