What is Google Antigravity?

A new “agent-first” AI coding platform from Google

Google Antigravity is a newly launched, agent-driven coding tool — introduced by Google on November 18, 2025, alongside the release of Gemini 3 Pro. What makes it distinctive is that it isn’t just an AI assistant for autocomplete or suggestions — it’s designed as an autonomous coding environment where multiple AI agents can plan, execute and verify complex development tasks on behalf of the user.

Depending on the chosen mode, Antigravity can operate as:

• An AI-powered IDE: In a conventional “Editor View,” akin to a traditional code editor (similar to Visual Studio Code), providing inline completions and synchronous workflow assistance.
  
• An agent-orchestration system: In “Manager View,” you can spawn, oversee, and orchestrate multiple agents across different workspaces — effectively letting AI handle tasks like writing code, running tests, launching builds, or even testing browser interactions.
  

In short: Antigravity reframes coding from “you write, AI helps” to “you give high-level instructions, AI (agents) do the work.”

Core Features of Google Antigravity

Here’s a breakdown of the prominent features that define Antigravity’s value proposition:

• Multi-agent orchestration — Through a dedicated Agent Manager interface, developers can deploy and supervise multiple AI agents simultaneously, each potentially handling different parts of the project.
  
• Artifacts and audit trail: Agents produce “Artifacts” — including task plans, code diffs, screenshots, browser recordings, and logs — so that users can review exactly what actions were taken before accepting changes.
  
• Integrated code editor & terminal: Antigravity builds on a VS Code-like environment, giving access to inline editing, terminal commands (through agents), project navigation etc.
  
• Browser and UI workflow support: With a browser extension and agent-driven browser integration, Antigravity agents can launch web apps, test UI flows, and even record browser interactions — enabling end-to-end workflows (code → build → test).
  
• Flexible autonomy modes: Users can choose their level of control. In “Agent-assisted development” mode, agents augment human coding; in “Manager Surface” mode, agents act more autonomously. 

This design — combining an IDE, autonomous agents, task orchestration, auditability, and full-stack workflow support — aims to redefine how developers interact with code and build software.

Google Antigravity: Pricing and Usage — Is It Free?

One of the most common questions is whether Antigravity is free, or what its cost looks like. According to its initial release notes and coverage:

• Antigravity is currently offered in a public preview. For early adopters, there are “generous usage limits” under which Antigravity (powered by Gemini 3 Pro) is accessible without charge.
  
• However, it is not described as “unlimited.” Users engaging in heavy, frequent use — especially large codebases or many agents — may hit rate limits or quota thresholds, at which point a paid plan or a shift to a different infrastructure (e.g., Google’s broader AI Studio) may be required.
  

So, to answer directly: Yes — Google Antigravity is currently free to use under preview, but it has usage quotas. Over time, especially for enterprise or high-volume users, there is likely to be a paid tier.

Because Google has not yet publicly priced a final commercial release (as of late November 2025), definitive “Google Antigravity price” is not yet available. Observers expect pricing to follow typical SaaS / AI-IDE subscription models, potentially based on usage (compute, agent count, concurrency) rather than a flat license fee.

Benefits and Use-Cases: Where Antigravity Shines

Rapid prototyping & feature development

For early-stage projects, startups or solo developers working on MVPs, Antigravity can drastically reduce time-to-first-feature. Instead of writing boilerplate code, wiring APIs, setting up scaffolding — you can instruct an agent: “Generate a Next.js + Supabase backend for user authentication with email + OAuth, scaffold the frontend pages, add UI tests.” The agent can spawn, code, build, and even test UI flows in one go.

Parallel task execution and multi-agent workflows

Large projects — especially full-stack or microservices architectures — often involve multiple sub-tasks: backend, frontend, tests, documentation, deployment scripts. Antigravity lets you assign different agents to different tasks, freeing human developers to focus on higher-level design or review.

Automated testing, validation, and audit trail

Thanks to its “Artifacts” system, Antigravity provides visibility into what agents did — code diffs, pre- and post-state, screenshots, browser recordings, test logs. This is crucial for real-world software engineering where blind trust in AI outputs can be risky. The audit trail helps teams review, accept or reject changes.

Full-stack & UI-driven workflows (including web)

Because agents can operate not only in the editor and terminal but also interact with a browser — launching web apps, clicking through UI, testing flows — Antigravity may enable fully automated development-and-test pipelines: code → build → deploy → test, with minimal human supervision.

Risks, Limitations, and Security Concerns

Despite its ambition, Antigravity is not without significant risks and limitations — especially given its early stage.

Security vulnerabilities: Real, serious issues reported

Just a day after Antigravity’s launch, security researchers flagged a severe vulnerability: when a user marks a workspace as “trusted,” a malicious project repository can embed code that installs a persistent backdoor. That backdoor would run every time Antigravity launches — even after project closure, or uninstall/reinstall — unless manually removed.

Because Antigravity gives agents deep access — file system, terminal commands, browser — a compromised workspace becomes a long-term security risk. As one researcher put it: AI coding agents “are very vulnerable … often based on older technologies and never patched.”

Moreover, Antigravity’s design treats “trusted workspace” as a gateway: once you grant that trust, agents operate with broad permissions, which attackers can exploit.

For organizations managing sensitive code (proprietary logic, credentials, API keys), this is a red flag — using Antigravity in production demands rigorous sandboxing, code audits, and security hygiene.

Stability, UX & early-stage bugs

Because Antigravity is brand new, users have reported frequent crashes, agents terminating unexpectedly, or integrations (like browser extension) failing.

It’s also early days for its editing and workflow features — some developers compare it to a “beta” or “alpha” product: promising in concept, but rough in execution.

Quotas & rate limits limit heavy use

For heavy users — e.g., large codebases, many agents, frequent builds/tests — the free preview’s “generous limits” may still be restrictive. Once limits are hit, users will need to pay or wait for quota refresh, which could disrupt productivity. 

Trust vs control tradeoff

Antigravity’s agent-first model shifts much of the control from the human developer to AI. While this can accelerate productivity, it also raises questions: Do you trust the agent’s decisions? Are you comfortable with AI generating and executing code on your behalf? The “agent-as-autonomous engineer” model might feel too hands-off for safety- or compliance-sensitive projects.

Google Antigravity vs Cursor 2.0 — Feature Comparison Table

To better position Antigravity within the current ecosystem of AI-powered IDEs, here’s a detailed comparison between Google Antigravity and Cursor 2.0.

Feature / Dimension	Google Antigravity	Cursor 2.0
Core AI model	Gemini 3 Pro (with support for others)	Proprietary “Composer” model optimized for coding velocity
Agent architecture	Agent-first, centralized Agent Manager enabling orchestration of multiple agents	Multi-agent, with up to 8 agents in parallel (via git worktrees)
Browser / UI integration	Browser extension — agents can drive browser, record sessions, test UI flows	Embedded browser & DOM inspection inside the editor, enabling UI automation and testing
Workflow style	Agent-oriented orchestration (“mission control”): ideal for complex, multi-step tasks	Developer-centric multi-agent environment — retains more manual control and is arguably more predictable
Artifacts / output review	Agents generate detailed artifacts: plans, diffs, screenshots, browser recordings, logs — high transparency	Agents’ changes can be reviewed via standard code diffs and logs — more traditional but less rich audit trail
Speed / performance (e.g. large codebases)	According to some internal benchmarks, resolves queries ~40% faster than Cursor on 100k+ line repos; accuracy on complex refactoring reportedly ~94% vs Cursor’s ~78%	Faster prototyping with 8 parallel agents; tasks typically complete in ~30 seconds depending on context and size
Stability & maturity	Early preview; bugs, crashes, integration issues reported — “beta/alpha” feel	More mature multi-agent experience (though not bug-free), gaining adoption for production-oriented workflows
Best suited for	Experimentation, agent-oriented workflows, end-to-end automation (code, UI, tests)	Teams wanting multi-agent assistance in a familiar IDE-like workflow, emphasizing speed, control, and stability

In essence: Antigravity emphasizes orchestration, end-to-end automation, and an “AI engineering team” feel. Cursor 2.0 emphasizes speed, parallelism, stability, and a more controlled, developer-centric workflow.

Real-World Implications: Who Should (or Should Not) Use Antigravity — Today

Given its strengths and weaknesses, here’s a practical guide for when Antigravity makes sense, and when to be cautious.

Antigravity is well-suited for:

• Startups, solo developers, or small teams building prototypes or MVPs — especially when you want to rapidly scaffold both backend and frontend, or iterate features fast. The multi-agent orchestration and browser integration can massively speed up work.
  
• Projects where end-to-end automation matters — e.g., full-stack apps with UI, backend, tests, deployment pipelines. Antigravity’s ability to code, test, and even verify in a single session can reduce friction and speed deployment cycles.
  
• Exploratory, experimental coding work — e.g., building demos, PoCs, prototypes, or exploration of new features or modules where you can afford some instability.
  
• Environments with good security hygiene — if you use isolated sandboxed environments or virtual machines, version control / backups, and treat “trusted workspaces” with caution, the benefits may outweigh the security risks.
  

Consider avoiding (or using with caution) when:

• You are working on sensitive or proprietary code (e.g., enterprise software, financial or security-critical systems). Given reported vulnerabilities, granting “trusted workspace” to arbitrary code — even temporarily — is risky.
  
• Your project demands high stability, predictability, and reliability, such as production systems, enterprise-grade codebases, or teams with strict compliance requirements. Antigravity’s early bugs, crashes, and immature tooling may slow you down or introduce risk.
  
• You require fine-grained human control over every change — for auditability, regression risk, or compliance. The “agent-first” model trades off manual control for autonomy, which may not align with strict development workflows or regulatory demands.
  
• Your team depends on large-scale, heavy operations with many agents — because quotas and rate limits might constrain usage under the free tier; without a stable paid model, long-term scalability is uncertain.
  

Broader Significance: Why Antigravity Matters — and What It Signals for the Future of AI-powered Development

The emergence of Google Antigravity signals a significant shift in how we think about software development tooling. A few broader observations:

From “AI assistant” to “AI collaborator / teammate”

Until recently, AI coding tools mostly functioned as assistants — offering autocomplete, suggestions, or helping debug small snippets. Antigravity moves the needle toward AI as an autonomous collaborator — capable of understanding high-level instructions, coordinating multiple tasks, executing code, running tests, and delivering results independently.

That changes the developer’s role: from writing every line of code to orchestrating, reviewing, and supervising. For many, this could mean dramatically improved productivity and faster iteration cycles.

Full-stack automation becomes realistic

Because Antigravity supports not only code editing but also terminal commands, browser integration, testing workflows, and artifact generation — entire full-stack development lifecycles (frontend + backend + tests + deployment + UI) can potentially be automated or semi-automated. This lowers friction for small teams, solo developers, startups — democratizing software development.

Risk and responsibility shift — especially around security and trust

With powerful autonomy comes serious responsibility. The security flaws discovered in less than 24 hours after launch underscore how quickly vulnerabilities can emerge when AI tools are given broad permissions. Tools like Antigravity force teams to reconsider traditional notions of “trusted code,” “workspace security,” and “access controls.”

Enterprises adopting these tools will need stronger sandboxing, auditing, and governance — and may need to enforce strict review policies before allowing agent-run code in critical environments.

Pressure on other AI-IDE tools — innovation accelerates

By pushing the envelope — integrating multi-agent orchestration, artifact tracking, browser automation — Antigravity raises the bar for other AI-powered IDEs and coding assistants. Competing tools like Cursor, and future entrants, will need to evolve quickly to remain relevant. We may see a new generation of coding platforms blending AI, automation, and orchestration.

Google Antigravity vs Cursor 2.0 — When to Use Which: Recommendations

Here’s a decision-guide to help you choose between Antigravity and Cursor 2.0 (or use both, depending on your needs):

Use Antigravity when:

• You want to experiment, prototype, or build a complete full-stack application quickly.
  
• You appreciate agent orchestration, automation, and want to minimize manual overhead.
  
• Your codebase is new or small, and you’re comfortable with occasional instability.
  
• You have proper version control / sandboxing and can manage security risks carefully.
  

Use Cursor 2.0 when:

• You need stable, reliable multi-agent support in a familiar IDE environment.
  
• You’re working on production-ready code, with high stability, control, and predictable behavior.
  
• You value developer control over every change, and auditability via code diffs and human review.
  
• You anticipate long-term, heavy usage where quotas or rate limits of preview tools may be a barrier.
  

In many cases, developers may even use both: Antigravity for rapid prototyping or early-phase development; Cursor 2.0 (or traditional workflows) for production readiness, maintenance, and stable release cycles.

Conclusion: A Powerful but Early-Stage “Gamechanger” with Tradeoffs

Google Antigravity represents one of the boldest moves yet toward fully autonomous, agent-driven software development. Its agent orchestration, artifact tracking, and integration of editor + terminal + browser mark a shift: from AI as assistant to AI as full-stack collaborator. For many developers — especially solo devs, small teams, or startups — Antigravity could drastically shorten development cycles, speed up prototyping, and automate complex tasks.

Yet, as with many breakthrough tools, it comes with tradeoffs. Security vulnerabilities, rate limits, early-stage instability, and reduced manual control mean that Antigravity is not a magic wand — not (yet) for large-scale production systems or sensitive codebases. Organizations that adopt it must do so with caution: sandboxing, strict version control, code review protocols, and governance.

Meanwhile, tools like Cursor 2.0 remain relevant — offering greater stability and control, even if they lack some of Antigravity’s bells and whistles. For developers, the optimal approach may be hybrid: prototyping with Antigravity, stabilizing with Cursor or traditional tools, and staying alert for updates.

In the broader view, Antigravity signals where the future of coding is heading: toward agentic development platforms, full-stack automation, and AI-driven “coding teams.” As these tools mature, embrace better security, and integrate more deeply, we may soon see entire software projects — from idea to deployed product — built by AI agents under human supervision.