Using Antigravity Agent on Google AI Studio

Implementation guide · Antigravity · Google DeepMind

Serverless

Google AI Studio exposes Antigravity Agent through model ID antigravity-preview-05-2026. Use the setup steps, sourced pricing, capabilities, and official provider links below to validate this route before deployment.

Last refreshed 2026-06-15. Next refresh: weekly.

Quick Start

  1. 1
    Create an account at Google AI Studio and generate an API key.
  2. 2
    Use the Google AI Studio SDK or REST API to call antigravity-preview-05-2026 — see the documentation for request format.
API PortalDocumentationPricingModel Card

Code Examples

Install
pip install google-genai
API key
GOOGLE_API_KEY
Model ID
antigravity-preview-05-2026

Use the model name directly, e.g. "gemini-2.0-flash", "gemini-1.5-pro", or "gemini-2.5-pro-preview-05-06".

import os
from google import genai

client = genai.Client(api_key=os.environ["GOOGLE_API_KEY"])
response = client.models.generate_content(
    model="antigravity-preview-05-2026",
    contents="Hello"
)
print(response.text)

Pricing on Google AI Studio

Capabilities

VisionMultimodalReasoningJSON / Tool useCode Execution

About Antigravity Agent

Antigravity Agent is Google DeepMind's preview managed agent for autonomous coding and browsing workflows. Powered by Gemini 3.5 Flash, it plans, reasons, runs code, manages files, and browses the web inside a secure Google-hosted Linux sandbox through the Interactions API. It accepts text and image input, has a 1,048,576-token input context window that compacts at about 135K tokens, and supports a 65,536-token output limit. Environment compute is not billed during preview; Google describes pricing as pay-as-you-go based on underlying Gemini model tokens and tool use.

Full model details →

Model Specs

Released2026-05-19
Context1.05m
Knowledge cutoff2025-01

Provider

Google AI Studio