Vertex AI Gemini API

When developing generative AI solutions with Gemini, developers choose between Gemini Developer API and the Vertex AI Gemini API.

Gemini Developer API provides an easy path to build, productionize and scale Gemini applications. Vertex AI offers a comprehensive ecosystem of enterprise ready features and services for building and deploying generative AI applications backed by the Google Cloud Platform.

While the best choice depends on your needs, we’ve recently simplified switching between these services. Both Gemini Developer API and Vertex AI Gemini API are now accessible through the unified Google Gen AI SDK, offering you greater flexibility.

Code comparison

Below are some side-by-side code comparisons between Gemini Developer API and Vertex AI quickstarts for text generation.

Python

You can access both Gemini Developer API and Vertex AI services through google-genai library. See libraries page for instructions on how to install the library.

Gemini Developer APIVertex AI Gemini API 
from google import genai

client = genai.Client(api_key="YOUR_API_KEY")

response = client.models.generate_content(
    model="gemini-2.0-flash", contents="Explain how AI works in a few words"
)
print(response.text)

from google import genai

client = genai.Client(
    vertexai=True, project='your-project-id', location='us-central1'
)

response = client.models.generate_content(
    model="gemini-2.0-flash", contents="Explain how AI works in a few words"
)
print(response.text)

JavaScript and TypeScript

You can access both Gemini Developer API and Vertex AI services through @google/genai library. See libraries page for instructions on how to install the library.

Gemini Developer APIVertex AI Gemini API 
import { GoogleGenAI } from "@google/genai";

const ai = new GoogleGenAI({ apiKey: "YOUR_API_KEY" });

async function main() {
  const response = await ai.models.generateContent({
    model: "gemini-2.0-flash",
    contents: "Explain how AI works in a few words",
  });
  console.log(response.text);
}

main();

import { GoogleGenAI } from '@google/genai';
const ai = new GoogleGenAI({
  vertexai: true,
  project: 'your_project',
  location: 'your_location',
});

async function main() {
  const response = await ai.models.generateContent({
    model: "gemini-2.0-flash",
    contents: "Explain how AI works in a few words",
  });
  console.log(response.text);
}

main();

Go

You can access both Gemini Developer API and Vertex AI services through google.golang.org/genai library. See libraries page for instructions on how to install the library.

Gemini Developer APIVertex AI Gemini API 
import (
  "context"
  "encoding/json"
  "fmt"
  "log"
  "google.golang.org/genai"
)

// Your Google API key
const apiKey = "your-api-key"

func main() {
  ctx := context.Background()
  client, err := genai.NewClient(ctx, &genai.ClientConfig{
    APIKey:  apiKey,
    Backend: genai.BackendGeminiAPI,
  })

  // Call the GenerateContent method.
  result, err := client.Models.GenerateContent(ctx, "gemini-2.0-flash", genai.Text("Tell me about New York?"), nil)

}

import (
  "context"
  "encoding/json"
  "fmt"
  "log"
  "google.golang.org/genai"
)

// Your GCP project
const project = "your-project"

// A GCP location like "us-central1"
const location = "some-gcp-location"

func main() {
  ctx := context.Background()
  client, err := genai.NewClient(ctx, &genai.ClientConfig
  {
        Project:  project,
      Location: location,
      Backend:  genai.BackendVertexAI,
  })

  // Call the GenerateContent method.
  result, err := client.Models.GenerateContent(ctx, "gemini-2.0-flash", genai.Text("Tell me about New York?"), nil)

}

Other use cases and platforms

Please refer to use case specific guides on Gemini Developer API Documentation and Vertex AI documentation for other platforms and use cases.

Migration considerations

When you migrate:

If you no longer need to use your Gemini API key for the Gemini Developer API, then follow security best practices and delete it.

To delete an API key:

  1. Open the Google Cloud API Credentials page.

  2. Find the API key you want to delete and click the Actions icon.

  3. Select Delete API key.

  4. In the Delete credential modal, select Delete.

    Deleting an API key takes a few minutes to propagate. After propagation completes, any traffic using the deleted API key is rejected.

Next steps