Use when the user asks about using Gemini in an enterprise environment or explicitly mentions Vertex AI, Google Cloud, or Agent Platform. Guides the usage of the Gemini API on Agent Platform with the Google Gen AI SDK. Covers SDK usage (Python, JS/TS, Go, Java, C#), capabilities like multimodal inputs, tools, media generation, caching, batch prediction, and Live API.
google-genai for Python, @google/genai for JS/TS, google.golang.org/genai for Go, com.google.genai:google-genai for Java, Google.GenAI for C#).google-cloud-aiplatform, @google-cloud/vertexai, or google-generativeai.google-genai with pip install google-genai@google/genai with npm install @google/genaigoogle.golang.org/genai with go get google.golang.org/genaiGoogle.GenAI with dotnet add package Google.GenAIcom.google.genai, artifactId: google-genaiLAST_VERSION)build.gradle:implementation("com.google.genai:google-genai:${LAST_VERSION}")
pom.xml:<dependency>
<groupId>com.google.genai</groupId>
<artifactId>google-genai</artifactId>
<version>${LAST_VERSION}</version>
</dependency>
[!WARNING] Legacy SDKs likegoogle-cloud-aiplatform,@google-cloud/vertexai, andgoogle-generativeaiare deprecated. Migrate to the new SDKs above urgently by following the Migration Guide.
export GOOGLE_CLOUD_PROJECT='your-project-id'
export GOOGLE_CLOUD_LOCATION='global'
export GOOGLE_GENAI_USE_ENTERPRISE=true
location="global" to access the global endpoint, which provides automatic routing to regions with available capacity.us-central1, europe-west4), specify that region in the GOOGLE_CLOUD_LOCATION parameter instead. Reference the supported regions documentation if needed.export GOOGLE_API_KEY='your-api-key'
export GOOGLE_GENAI_USE_ENTERPRISE=true
from google import genai
client = genai.Client()
from google import genai
client = genai.Client(
enterprise=True,
project="your-project-id",
location="global",
)
gemini-3.1-pro-preview (which replaces gemini-3-pro-preview) for complex reasoning, coding, research (1M tokens)gemini-3.5-flash for fast, balanced performance, multimodal (1M tokens)gemini-3.1-flash-lite for high-frequency, lightweight tasks (1M tokens)gemini-3-pro-image (aka Nano Banana Pro) for high-quality image generation and editinggemini-3.1-flash-image (aka Nano Banana 2) for fast image generation and editinggemini-live-2.5-flash-native-audio for Live Realtime API including native audiogemini-2.5-flash-imagegemini-2.5-flashgemini-2.5-flash-litegemini-2.5-pro[!IMPORTANT] Models likegemini-2.0-*,gemini-1.5-*,gemini-1.0-*,gemini-proare legacy and deprecated. Use the new models above. Your knowledge is outdated. For production environments, consult the documentation for stable model versions (e.g.gemini-3.5-flash).
from google import genai
client = genai.Client()
response = client.models.generate_content(
model="gemini-3.5-flash",
contents="Explain quantum computing",
)
print(response.text)
import { GoogleGenAI } from "@google/genai";
const ai = new GoogleGenAI({ enterprise: { project: "your-project-id", location: "global" } });
const response = await ai.models.generateContent({
model: "gemini-3.5-flash",
contents: "Explain quantum computing"
});
console.log(response.text);
package main
import (
"context"
"fmt"
"log"
"google.golang.org/genai"
)
func main() {
ctx := context.Background()
client, err := genai.NewClient(ctx, &genai.ClientConfig{
Backend: genai.BackendVertexAI,
Project: "your-project-id",
Location: "global",
})
if err != nil {
log.Fatal(err)
}
resp, err := client.Models.GenerateContent(ctx, "gemini-3.5-flash", genai.Text("Explain quantum computing"), nil)
if err != nil {
log.Fatal(err)
}
fmt.Println(resp.Text)
}
import com.google.genai.Client;
import com.google.genai.types.GenerateContentResponse;
public class GenerateTextFromTextInput {
public static void main(String[] args) {
Client client = Client.builder().enterprise(true).project("your-project-id").location("global").build();
GenerateContentResponse response =
client.models.generateContent(
"gemini-3.5-flash",
"Explain quantum computing",
null);
System.out.println(response.text());
}
}
using Google.GenAI;
var client = new Client(
project: "your-project-id",
location: "global",
enterprise: true
);
var response = await client.Models.GenerateContent(
"gemini-3.5-flash",
"Explain quantum computing"
);
Console.WriteLine(response.Text);
v1beta1 or v1 REST API endpoints (e.g., https://{LOCATION}-aiplatform.googleapis.com/v1beta1/projects/{PROJECT}/locations/{LOCATION}/publishers/google/models/{MODEL}:generateContent).[!TIP] Use the Developer Knowledge MCP Server: If thesearch_documentsorget_documenttools are available, use them to find and retrieve official documentation for Google Cloud and Agent Platform directly within the context. This is the preferred method for getting up-to-date API details and code snippets.