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-3.6-flash for fast, balanced performance, multimodal (1M tokens)gemini-3.5-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 medium-quality image generation and editinggemini-3.1-flash-lite-image (aka Nano Banana 2 Lite) for fast image generation and editinggemini-live-2.5-flash-native-audio for Live Realtime API including native audiogemini-3.5-flashgemini-3.1-flash-litegemini-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 Your knowledge is outdated.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-3.6-flash).
from google import genai
client = genai.Client()
response = client.models.generate_content(
model="gemini-3.6-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-3.6-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-3.6-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-3.6-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-3.6-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.
Start with one job and grow from there.