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Gemini API

Go from a quick prompt to production apps and agents with the Gemini API. Tackle complex coding and multimodal reasoning with Gemini, or hand multi-step work to a managed agent. Stream voice and video with the Live API, or generate images with Nano Banana, video with Gemini Omni, and music with Lyria.

Python

from google import genai

client = genai.Client()

interaction = client.interactions.create(
    model="gemini-4-argon",
    input="Explain how AI works in a few words"
)

print(interaction.output_text)

JavaScript

import { GoogleGenAI } from "@google/genai";

const ai = new GoogleGenAI({});

const interaction = await ai.interactions.create({
  model: "gemini-4-argon",
  input: "Explain how AI works in a few words",
});

console.log(interaction.output_text);

Java

import com.google.genai.Client;
import com.google.genai.gaos.models.interactions.CreateModelInteraction;
import com.google.genai.gaos.models.interactions.Interaction;
import com.google.genai.gaos.models.interactions.InteractionsInput;
import com.google.genai.gaos.models.interactions.Model;
import com.google.genai.gaos.models.operations.CreateInteractionRequestBody;

Client client = new Client();

CreateModelInteraction params =
    CreateModelInteraction.builder()
        .model(Model.of("gemini-4-argon"))
        .input(InteractionsInput.of("Explain how AI works in a few words"))
        .build();

Interaction interaction =
    client.interactions.create(CreateInteractionRequestBody.of(params)).interaction().get();

System.out.println(interaction.outputText().orElse(""));

Go

package main

import (
    "context"
    "fmt"
    "log"

    "google.golang.org/genai"
    "google.golang.org/genai/interactions/models/interactions"
    "google.golang.org/genai/interactions/models/operations"
)

func main() {
    ctx := context.Background()
    client, err := genai.NewClient(ctx, nil)
    if err != nil {
        log.Fatal(err)
    }

    res, err := client.Interactions.Create(ctx, operations.CreateInteractionRequest{
        Body: operations.NewCreateInteractionRequestBody(interactions.CreateModelInteraction{
            Model: interactions.Model("gemini-4-argon"),
            Input: interactions.NewInteractionsInput("Explain how AI works in a few words"),
        }),
    })
    if err != nil {
        log.Fatal(err)
    }
    if res.Interaction.OutputText != nil {
        fmt.Println(*res.Interaction.OutputText)
    }
}

REST

curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \
  -H "x-goog-api-key: $GEMINI_API_KEY" \
  -H 'Content-Type: application/json' \
  -d '{
    "model": "gemini-4-argon",
    "input": "Explain how AI works in a few words"
  }'
Get Started Create API Key

Meet the models

View all

Gemini 4 Argon New

Our flagship reasoning model with a shared 1M context window and long decodes up to 1M tokens.

Gemini 3.8 Flash New

Our most intelligent Flash model, engineered for long-horizon software engineering, autonomous agents, and complex enterprise workflows.

Gemini 3.8 Flash TTS New

Studio-grade text-to-speech model with expressive acting, custom Voice design, and Voice replication.

Gemini 3.5 Flash-Lite

High-volume, cost-sensitive model optimized for low-latency high throughput subagent tasks.

Nano Banana

State-of-the-art image generation and editing models.

Gemini Omni Flash

Our state-of-the-art video generation and editing model.

Gemini 3.5 Transcribe New

Low-latency speech-to-text model with utterance-based language detection, speaker diarization, and word timestamps.

Gemini Robotics

A vision-language model (VLM) that brings Gemini's agentic capabilities to robotics and enables advanced reasoning in the physical world.

Explore Capabilities

Image Generation

Generate and edit highly contextual images natively with Nano Banana.

Long Context

Input millions of tokens to Gemini models and derive understanding from unstructured images, videos, and documents.

Structured Outputs

Constrain Gemini to respond with JSON, a structured data format suitable for automated processing.

Function Calling

Build agentic workflows by connecting Gemini to external APIs and tools.

Video Generation with Gemini Omni Flash

Create high-quality video content from text or image prompts with our state-of-the-art model.

Voice Agents with Live API

Build real-time voice applications and agents with the Live API.

Tools

Connect Gemini to the world through built-in tools like Google Search, URL Context, Google Maps, Code Execution and Computer Use.

Document Understanding

Process up to 1000 pages of PDF files with full multimodal understanding or other text-based file types.

Thinking

Explore how thinking capabilities improve reasoning for complex tasks and agents.

Create agents

Managed Agents give Gemini a workspace to plan and complete tasks on its own. In a single request, Gemini can write and run code, search the web, and create files in a hosted sandbox environment. Start with our prebuilt Antigravity agent, or customize it with your own instructions and tools.

Python

from google import genai

client = genai.Client()

interaction = client.interactions.create(
    agent="antigravity-preview-09-2026",
    input=(
        "Research the top 5 sustainable fashion brands, "
        "compare their materials and pricing tiers, and "
        "build an interactive dashboard in analysis.html."
    ),
    environment="remote"
)

print(interaction.output_text)

JavaScript

import { GoogleGenAI } from "@google/genai";

const ai = new GoogleGenAI({});

const interaction = await ai.interactions.create({
  agent: "antigravity-preview-09-2026",
  input:
    "Research the top 5 sustainable fashion brands, " +
    "compare their materials and pricing tiers, and " +
    "build an interactive dashboard in analysis.html.",
  environment: "remote",
});

console.log(interaction.output_text);

Java

import com.google.genai.Client;
import com.google.genai.gaos.models.interactions.AgentOption;
import com.google.genai.gaos.models.interactions.CreateAgentInteraction;
import com.google.genai.gaos.models.interactions.CreateAgentInteractionEnvironment;
import com.google.genai.gaos.models.interactions.Interaction;
import com.google.genai.gaos.models.interactions.InteractionsInput;
import com.google.genai.gaos.models.operations.CreateInteractionRequestBody;

Client client = new Client();

CreateAgentInteraction params =
    CreateAgentInteraction.builder()
        .agent(AgentOption.of("antigravity-preview-09-2026"))
        .input(
            InteractionsInput.of(
                "Research the top 5 sustainable fashion brands, "
                    + "compare their materials and pricing tiers, and "
                    + "build an interactive dashboard in analysis.html."))
        .environment(CreateAgentInteractionEnvironment.of("remote"))
        .build();

Interaction interaction =
    client.interactions.create(CreateInteractionRequestBody.of(params))
        .interaction()
        .get();

System.out.println(interaction.outputText().orElse(""));

Go

package main

import (
    "context"
    "fmt"
    "log"

    "google.golang.org/genai"
    "google.golang.org/genai/interactions/models/interactions"
    "google.golang.org/genai/interactions/models/operations"
)

func main() {
    ctx := context.Background()
    client, err := genai.NewClient(ctx, nil)
    if err != nil {
        log.Fatal(err)
    }

    res, err := client.Interactions.Create(ctx, operations.CreateInteractionRequest{
        Body: operations.NewCreateInteractionRequestBody(interactions.CreateAgentInteraction{
            Agent: interactions.AgentOption("antigravity-preview-09-2026"),
            Input: interactions.NewInteractionsInput(
                "Research the top 5 sustainable fashion brands, " +
                    "compare their materials and pricing tiers, and " +
                    "build an interactive dashboard in analysis.html.",
            ),
            Environment: genai.Ptr(interactions.NewCreateAgentInteractionEnvironment("remote")),
        }),
    })
    if err != nil {
        log.Fatal(err)
    }
    if res.Interaction.OutputText != nil {
        fmt.Println(*res.Interaction.OutputText)
    }
}

REST

curl -X POST \
  "https://generativelanguage.googleapis.com/v1beta/interactions" \
  -H "x-goog-api-key: $GEMINI_API_KEY" \
  -H 'Content-Type: application/json' \
  -d '{
    "agent": "antigravity-preview-09-2026",
    "input": "Research the top 5 sustainable fashion brands, compare their materials and pricing tiers, and build an interactive dashboard in analysis.html.",
    "environment": "remote"
  }'
Agents quickstart Try in AI Studio

Interactions API

The Interactions API has become our default interface as of June 2026 and is the best way to build with Gemini models and agents going forward. If you're starting a new project, you should use the Interactions API. While it remains supported, the generateContent API is now considered legacy.

Interactions Overview

Learn how the Interactions API manages conversation state, messages, and output formats.

Migration Guide

Step-by-step guide to transition your code from generateContent to the Interactions API.

Streaming

Stream real-time tokens, incremental thoughts, and tool call events.

Google AI Studio

Test prompts, manage your API keys, monitor usage, and build prototypes.

Developer Community

Ask questions and find solutions from other developers and Google engineers.

API Reference

Find detailed information about the Gemini API in the official reference documentation.

Status

Check the status of Gemini API, Google AI Studio, and our model services.