Google Antigravity
Google · Coding
Google Antigravity is an AI agent coding platform from Google that lets agents plan, write, test and verify code on your behalf instead of only suggesting lines you type yourself. It started in November 2025 as a desktop coding environment and grew into a multi-agent workspace with a command-line tool and a Python SDK. Hand off whole tasks, not just snippets. That's what Google built it for.
About Google Antigravity
What Is Google Antigravity
Google Antigravity is a development platform where AI agents take the lead. You describe an outcome, and one or more agents break it into steps, edit files, run terminal commands, open a browser to check the result, and hand you structured artifacts you can review. Google calls the approach agent-first, and the name is honest about the shift: agents do the work, you approve it.
The project shipped on November 18, 2025 alongside Gemini 3 Pro, first as a standalone desktop app for Windows, macOS and Linux. At Google I/O 2026 it became Antigravity 2.0, a platform that no longer depends on an IDE at all. A separate Antigravity CLI replaced Gemini CLI, and an Antigravity SDK lets developers build and deploy their own agents on the same runtime.
The biggest limitation is cost and geography. Agentic runs burn tokens fast, so heavy users outgrow the free tier quickly, and access depends on your Google account region. There's no way to buy extra credits if you're on a plan that doesn't include them.
Getting Started
- Download the Antigravity app from the official site for Windows, macOS or Linux, then sign in with a Google account that's set to a supported region.
- Create a project and point it at one or more folders on your machine.
- Set permissions for file, terminal and browser access so agents only touch what you allow.
- Describe your task in the chat panel, then review the plan and artifacts the agent returns.
- Approve, comment on, or reject the changes before anything merges.
Product Information
A quick look at Google Antigravity's pricing, supported platforms, and performance.
Best for
The users, tasks, and scenarios where this tool fits best.
Users
- Software developers
- Product managers and technical writers
- Small teams without a dedicated DevOps hire
Tasks
- Building a feature end to end
- Legacy code migration
- Prototyping from an idea
Scenarios
- Weekend side projects
- Sprint cleanup
- Learning a new framework
Key features
Agent Manager and Parallel Agents
Google Antigravity runs several agents at once inside a project. You can have one rewriting an API, another adjusting React components and a third writing test cases, all working in parallel with their own context windows. The point is throughput: complex tasks finish faster when the work splits instead of queueing behind a single conversation.
Subagents That Spawn on Demand
When a task gets large, the main agent creates focused subagents to handle the parts. Each one runs in its own context. Subtasks don't crowd out the parent agent's memory, and they run at the same time. Google showed this at scale with a demo that spun up dozens of subagents to build a custom operating system.
Artifacts You Can Actually Review
Agents report back with structured artifacts: task lists, implementation plans, screenshots and browser recordings. You can comment on any of them, Google Docs style, and the agent folds your feedback into the next pass without you stopping its run. It's a direct answer to the black-box problem that plagues most AI coding tools.
Antigravity CLI
For developers who live in a terminal, the Antigravity CLI lets you launch and manage agents without leaving your editor. It's lighter and faster than the Gemini CLI it replaces, and Google has told existing Gemini CLI users to migrate, since the old tool stopped serving requests for consumer tiers on June 18, 2026.
Antigravity SDK and Managed Agents
The Antigravity SDK is a Python library that lets you build your own agents on the same runtime that powers the Antigravity app. Agents start with file, shell, search and image tools, and you can swap in your own. Google also offers managed agents through the Gemini API that run in an isolated Linux environment when you'd rather not host them yourself.
Model Choice and Reasoning Modes
Google Antigravity runs on Gemini 3.5 Flash and Gemini 3.1 Pro. It also offers Claude Sonnet and Opus models plus open-weight options like GPT-OSS-120B. Fast mode favors speed. Plan mode spends more reasoning on architecture-level work. Bring your own key and a custom model channel accepts any compatible endpoint.
Scheduled Tasks
The /schedule command lets you run agents on a timer, once or on a recurring basis. That turns Antigravity into a background worker for chores like checking issues, refreshing dependencies, generating reports or topping up test coverage, so nobody has to remember to kick them off.
Pros and cons
Pros
- Parallel agents and on-demand subagents cut wall-clock time on large tasks. Each subtask keeps its own context.
- Artifacts with inline comments make agent work reviewable instead of opaque, which matters when you're approving changes to a real codebase.
- Multi-model support means you can switch between Gemini, Claude and open-weight models per task without juggling separate tools.
- A free tier with quotas that refresh every few hours is enough for personal projects, and the CLI and SDK give you a path off the desktop app.
Cons
- Agentic runs consume tokens fast, so free and Pro users can hit the quota wall during a long session. There's no pay-as-you-go top-up on lower tiers.
- Access is tied to your Google account region, and an account set to an unsupported country can be refused outright.
- Antigravity CLI is closed source, unlike the Apache-licensed Gemini CLI it replaces, so you can't patch or fork it yourself.
Frequently asked questions
It's an agent-first development platform for building and managing software with AI agents. You give it a task, agents plan and execute it across your files, terminal and browser, and you review the results. It's aimed at developers, but non-engineers use it for prototyping and research too.
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