As of November 18, 2025, Google Antigravity is brand-new, sitting at the intersection of AI IDEs, agentic coding, and Google’s latest flagship model, Gemini 3 Pro. This is NEWS CONTENT: Antigravity and Gemini 3 Pro were both announced on November 18, 2025, and are in free public preview. What follows is a concise, fact-focused guide to what Antigravity is, how it uses Gemini 3 Pro, and why it matters for developer productivity beyond “just another VS Code fork.”
What Google Antigravity and Gemini 3 Pro are
On November 18, 2025, Google announced Gemini 3, its new “most intelligent” model family, and simultaneously launched Google Antigravity, described as an “agentic development platform” and an “agent-first” coding environment. Antigravity is a desktop IDE, built as a fork on top of Microsoft’s open-source VS Code stack, but tightly coupled to Gemini 3 Pro and other frontier models.
Gemini 3 Pro (model ID gemini-3-pro-preview) is the first Gemini 3 model in public preview, with a 1M-token context window and a January 2025 knowledge cutoff. Google positions it as its best model yet for reasoning, multimodal understanding, and particularly “vibe coding” and agentic coding. In Antigravity, Gemini 3 Pro is the default engine for code generation, planning, and multi-step workflows. The IDE also supports Anthropic Claude Sonnet 4.5 and Google’s GPT-OSS open-weight models as additional backends, according to The New Stack’s launch coverage.
How Antigravity works: more than a VS Code fork
Although the editor layer looks and behaves like VS Code, Antigravity introduces a few structural changes aimed at “agent-first” workflows rather than traditional inline chat:
- Three “surfaces” instead of one panelized editor: an Agent Manager dashboard, a VS Code-style Editor view, and a browser integration via a Chrome extension for computer-use style testing and interaction.
- Artifacts instead of just chat logs: Gemini 3 Pro agents generate markdown “artifacts” such as task lists, implementation plans, verification reports, screenshots, and browser recordings. These are intended to make agent behavior auditable and easier to trust than raw tool calls.
- Agent Manager (“mission control”): a dedicated view for spawning, orchestrating, and monitoring multiple agents across workspaces, rather than burying agents in a single sidebar.
- Cross-surface agents: agents can act across editor, terminal, and browser simultaneously, leaning on Gemini 3’s strong tool-use and planning benchmarks (e.g., high scores on Terminal-Bench 2.0 and SWE-bench Verified, per Google’s official benchmarks).
Under the hood, Antigravity relies heavily on Gemini 3 Pro’s new capabilities: dynamic “thinking” levels, long-context reasoning over entire repos, and advanced tool use for terminal and browser control. Google also pairs Antigravity with a dedicated Gemini 2.5-based “Computer Use” model for browser automation and a Nano Banana (Gemini 2.5 Image) model for visual tasks such as UI validation and simple image editing.
How to get started with Google Antigravity
Antigravity is currently a free public preview for individual developers, with “generous rate limits” on Gemini 3 Pro usage. According to Google and The New Stack, here’s the current availability picture:
- Download the IDE
Visit antigravity.google and download the installer for macOS, Windows, or Linux. The current build is tied to the Gemini 3 Pro preview announcement from November 18, 2025. - Sign in with a Google account
On first launch, Antigravity prompts you to sign in with your Google account, similar to other Google developer tools. This links the IDE to your Gemini 3 Pro quotas and agentic tooling. - Choose your model
Within the Antigravity settings or Agent Manager, you can select which backend model powers your agents: Gemini 3 Pro by default, with options for Claude Sonnet 4.5 and GPT-OSS where capacity allows. - Open or create a workspace
You can clone an existing repo or create a new project exactly as you would in VS Code. The editor supports autocomplete, code navigation, terminals, and most common workflows out of the box. - Attach an agent mission
From the Agent Manager, create a new “mission” for Gemini 3 Pro: for example, “Implement a flight tracker app” or “Migrate this service from Node 14 to Node 22.” This is where Antigravity shifts from editor-with-chat into agentic coding territory.
Rate limits are enforced per-user and refreshed on a 5-hour cadence. Google states it will “provide access to models to the degree we have capacity,” so early adopters may see occasional “model provider overload” errors during peak usage.
Using Gemini 3 Pro for agentic coding inside Antigravity
The core innovation of Antigravity is agentic coding: letting Gemini 3 Pro and companion models plan, execute, and verify multi-step development tasks on your behalf while keeping you “in the loop” through artifacts. Practically, this looks less like “autocomplete on steroids” and more like pairing with a reliable, tool-using teammate.
- Task-oriented prompts: Instead of micromanaging code snippets, you assign high-level missions (“add OAuth-based login flow,” “refactor the checkout pipeline to support subscriptions”). Gemini 3 Pro uses its high “thinking” level to plan the work.
- Artifacts as checkpoints: For each mission, the agent writes artifacts such as:
- Task breakdowns and implementation plans
- Patch summaries for code changes
- Verification logs from tests or browser sessions
- Walkthroughs of the final feature behavior
- Cross-surface execution: Agents can edit code, run commands in the integrated terminal, and drive the browser via the Chrome extension. For front-end work, this means Gemini 3 can generate UI components, run them in a dev server, then visually validate behavior in the browser.
- Multi-agent workflows: From the Agent Manager mission control, you can run multiple agents in parallel on different parts of your repo: one building a new feature, another writing tests, and another updating docs.
Why it matters for developer productivity
Compared with a plain VS Code fork, Antigravity is tightly optimized around the emerging “agentic coding” workflow that Google is pushing as part of the Gemini 3 era. The model itself is tuned for this use case: Gemini 3 Pro scores highly on WebDev Arena, Terminal-Bench 2.0, and SWE-bench Verified, and is explicitly marketed as Google’s “best vibe coding and agentic coding model yet.”
For developers, that translates into several practical benefits:
- Higher-level work: You stay in an architectural and review role while Gemini 3 Pro handles boilerplate, multi-file refactors, and front-end scaffolding.
- Better observability of AI actions: Artifacts, browser recordings, and verification logs make it easier to audit and trust what the agent did, addressing a common criticism of opaque AI copilot tools.
- Reduced context juggling: By centralizing editor, terminal, and browser control under one agent interface, Antigravity aims to cut down context switching that plagues conventional AI-assisted workflows.
- Model flexibility: Built-in support for Gemini 3 Pro, Claude Sonnet 4.5, and GPT-OSS gives teams room to compare behavior or route different tasks to different models while staying in a single IDE.
Impact and early implications
Antigravity launches into a crowded field of AI-first IDEs and VS Code forks, but its tight integration with Gemini 3 Pro and Google’s broader agentic ecosystem makes it strategically important:
- For Google, Antigravity is a showcase for Gemini 3’s agentic capabilities, from long-context repo understanding to browser control. It complements Gemini CLI, AI Studio “vibe coding” mode, and other experiments like Jules, giving Google a full-stack story from API to IDE.
- For developers, it offers a no-cost way (during public preview) to experiment with deep agentic workflows on top of a familiar VS Code-like experience. The mission-control style Agent Manager and artifact system are early tests of what “agent-first” development might look like at scale.
- For the ecosystem, the support for multiple frontier models inside a Google IDE is notable: it acknowledges that serious teams will mix-and-match models rather than bet on a single provider.
As Antigravity and Gemini 3 Pro roll out more broadly, the key questions for teams will be less about raw model IQ and more about workflow fit: whether the Agent Manager, artifacts, and cross-surface control actually shorten time-to-production without introducing new failure modes or governance headaches.
