Google just released Google Antigravity, an agentic development platform that lets AI agents autonomously write, test, debug, and verify entire applications while you watch. Unlike traditional AI coding assistants that suggest lines of code, Antigravity gives agents direct control over your editor, terminal, and browser transforming them from helpful tools into autonomous software developers.
Available in free public preview since November 17, 2025, Antigravity runs on Gemini 3 Pro (scoring 1,501 Elo on LMArena and 76.2% on SWE-bench Verified) and supports Claude Sonnet 4.5 and GPT-OSS. It’s downloadable for Windows, macOS, and Linux, with no subscription required during preview.
Summary: Google Antigravity is a VS Code-based IDE where AI agents autonomously build applications from prompts, generate task plans, write code, run tests in Chrome, and produce verification artifacts all while you maintain oversight through Editor or Manager views. Free during public preview with generous rate limits.
Table of Contents
What Google Antigravity Actually Does
Beyond Traditional AI Code Assistants
Most AI coding tools like GitHub Copilot or Cursor’s Tab autocomplete work reactively; they suggest code as you type or respond to chat prompts. Google Antigravity flips this model by introducing agent-first architecture where AI operates proactively at a task level rather than a line-by-line level.
When you give Antigravity a high-level instruction like “build a flight tracking app with real-time updates,” agents autonomously break the request into subtasks (set up backend API, create frontend components, implement WebSocket connections), execute each step across your editor and terminal, then validate the final product by opening it in Chrome and recording the test session. This end-to-end workflow happens without you writing a single line of code manually.
The platform introduces Artifacts digestible documentation including task lists, implementation plans, screenshots, and browser recordings that replace overwhelming action logs with human-readable progress reports. Developers can annotate these artifacts with Google Docs-style comments to redirect agents mid-task without stopping their execution.
The Agent-First Architecture Explained
Antigravity’s architecture grants agents direct access to three surfaces: the code editor (reading and writing files), the terminal (running commands and scripts), and the browser (via a Chrome extension that observes UI behavior and interacts with web apps). This “elevated surface” design means agents don’t just suggest changes they implement, test, and verify autonomously while generating progress checkpoints.
Built on Microsoft’s VS Code, Antigravity inherits compatibility with thousands of existing extensions while adding agent-specific capabilities like synchronized multi-workspace control and self-improving workflows that learn from past projects. The platform uses Gemini 3’s 1 million-token context window to understand entire monorepos without truncation.
Getting Started With Google Antigravity
System Requirements and Download
Minimum requirements vary by platform:
macOS: macOS Monterey or later, Apple Silicon only (M1/M2/M3 chips)
Windows: 64-bit Windows 10 or later
Linux: glibc ≥ 2.28, glibcxx ≥ 3.4.25 (e.g., Ubuntu 20.04+, Fedora 29+)
Download installers from the official site at antigravity.google/download. The installer size ranges from 250-400 MB depending on your operating system.
Installation Walkthrough
Step 1: Navigate to antigravity.google and download the installer for your OS to verify you’re on the legitimate Google domain to avoid fake clones.
Step 2: Run the installer on your default system drive (Windows users should install to C: drive to avoid login issues reported in early testing).
Step 3: Set Chrome as your default browser before first launching Antigravity’s browser agent and authentication flow rely on Chrome integration.
Step 4: Launch Google Antigravity and click “Sign in with Google” using the account you want tied to cloud access and rate limit quotas.
Step 5: Wait for the OAuth callback to redirect into the app if the login screen spins for several minutes, restart the app with Chrome set as default and ensure installation was on the C: drive.
Upon successful login, you’ll reach the Agent Manager interface, confirming setup completion. The platform includes generous rate limits on Gemini 3 Pro usage that refresh every 5 hours.
First Project Setup
Create your first project by either opening an existing Git repository or starting fresh with a blank workspace. Antigravity supports all languages VS Code handles (JavaScript, Python, Java, Go, Rust, etc.) since it’s built on the same foundation.
To test agentic capabilities immediately, try a simple prompt in Manager View: “Create a responsive landing page with a navbar, hero section, and contact form using Tailwind CSS”. Antigravity will generate a task plan, scaffold files, write HTML/CSS, and open the result in your browser with a recorded walkthrough.
Two Ways to Work With Antigravity
Editor View for Daily Coding
Editor View resembles traditional AI-enhanced IDEs like Cursor, with the code editor occupying the main canvas and an AI agent panel on the side. This mode suits developers who want to write code themselves while using agents for specific tasks like refactoring functions, generating boilerplate, or explaining legacy code.
In Editor View, you maintain direct control agents that suggest changes you can accept, reject, or modify inline, similar to GitHub Copilot’s workflow but with more sophisticated multi-file understanding thanks to Gemini 3’s extended context. The interface feels familiar to anyone using VS Code extensions.
Manager View for Multi-Agent Workflows
Manager View transforms the experience into “mission control” for running multiple AI agents across separate workspaces simultaneously. This mode shines when tackling complex features that span frontend, backend, database migrations, and testing.
Google describes Manager View as supervising “several virtual interns working on different parts of a project”. One agent might handle API endpoint implementation while another builds corresponding UI components and a third writes integration tests all progressing in parallel with shared context.
Artifacts in Manager View provide high-level progress summaries rather than line-by-line diff logs, making it practical to oversee multiple concurrent tasks. Developers can jump into any agent’s workspace to inspect details or provide inline corrections via comment annotations.
When to Use Each Mode
Choose Editor View when: You’re writing code actively yourself, working on small-scope tasks (bug fixes, single-function implementations), or learning a new codebase where you want to maintain hands-on control.
Choose Manager View when: Building greenfield features from scratch, coordinating work across multiple services or layers (full-stack implementations), or handling architectural changes that require simultaneous updates in many files.
Many developers reported keeping both Cursor and Antigravity installed using Cursor as the polished daily driver for stability and Antigravity as the experimental lab for letting agents tackle ambitious multi-step workflows.
How Antigravity Compares to Cursor
Performance Benchmarks That Matter
Independent testing conducted within 48 hours of Antigravity’s launch revealed measurable performance gaps:
Codebase navigation: Antigravity resolved queries across 100,000+ line repositories 40% faster than Cursor 2.0.
Complex refactoring accuracy: Antigravity achieved 94% accuracy compared to Cursor’s 78% on multi-file refactoring tasks.
Bug introduction rates: Antigravity reduced bugs introduced during refactoring by approximately 50% due to Gemini 3’s superior reasoning about edge cases.
Code generation speed: Antigravity completed a typical Next.js + Supabase backend feature in 42 seconds versus Cursor’s 68 seconds, a 38% speed improvement that compounds significantly over a workday.
SWE-bench Verified: Gemini 3 Pro scores 76.2% on this benchmark measuring coding agent performance, placing it among the top models globally.
Pricing and Accessibility
Cursor charges $20-$40 per user monthly for meaningful usage beyond free tier limits. Google Antigravity launches completely free for individual developers during public preview with generous rate limits tied to Google Cloud accounts.
Teams using Antigravity pay only to compute beyond baseline quotas, often cheaper than Cursor Pro for heavy users. Enterprise contracts include dedicated Gemini 3 fine-tuning capabilities unavailable in third-party tools.
This pricing disruption drove mass migration within the first week of launch, particularly among startups and independent developers seeking cost-effective agentic capabilities.
Context Window and Codebase Understanding
Gemini 3 handles over 1 million tokens natively, enabling Antigravity to understand entire monorepos without truncation or manual context pruning. Cursor, even with its latest Composer model, caps effective context significantly lower in practice.
This advantage manifests in first-attempt accuracy Antigravity refactors massive codebases correctly on the initial try, whereas Cursor often requires multiple iterations or manual context selection. The platform additionally supports MCP (Model Context Protocol) and Knowledge Items, allowing agents to pull live schemas, logs, and external documentation on demand.
Unique Features Antigravity Brings
Browser agent integration: Antigravity’s Chrome extension enables agents to run code, observe visual behavior in real browsers, identify UI bugs, and make adjustments automatically. This workflow proves especially powerful for web application development requiring visual verification.
Artifact-based transparency: Instead of overwhelming developers with action logs showing every keystroke, Antigravity generates task lists, screenshots, and browser recordings that document what agents accomplished and plan to do next.
Multi-model support: While Gemini 3 Pro serves as the default, Antigravity supports Claude Sonnet 4.5 and OpenAI’s GPT-OSS, giving developers flexibility to choose models based on task requirements.
Self-improving workflows: Agents learn from past work by saving relevant code snippets, architectural patterns, and debugging strategies for reuse in future projects.
Real-World Use Cases We Tested
Building a Full-Stack App From a Single Prompt
In hands-on testing, we prompted Antigravity with: “Build a real-time flight tracker app that shows live flight positions on a map with filters for airline and destination”.
The agent autonomously broke this into subtasks: set up Express.js backend with WebSocket support, integrate aviation API for flight data, create React frontend with Mapbox GL for visualization, implement filter UI components, and add responsive design. Total execution time from prompt to working application: 4 minutes 37 seconds.
Antigravity then opened Chrome, navigated to localhost:3000, interacted with the map and filters, and recorded a walkthrough video demonstrating functionality. The artifact documentation included a task checklist with completion timestamps and screenshots of each implementation phase.
Browser-Based Testing and Verification
Traditional AI coding tools stop after generating code developers manually test in browsers. Antigravity’s browser agent validates its own work by loading applications in Chrome, clicking UI elements, filling forms, and observing behavior.
During testing of an e-commerce checkout flow, Antigravity autonomously identified a visual bug where the payment button overlapped form fields on mobile viewports. The agent captured a screenshot, annotated the issue in artifacts, adjusted CSS media queries, and re-tested to confirm the fix all without human intervention.
This closed-loop workflow (code → test → debug → verify) represents a significant leap beyond Cursor’s capabilities, which excel at code generation but require manual testing steps.
Debugging Complex Legacy Code
We fed Antigravity a 12,000-line Django project with undocumented business logic and intermittent database connection failures. Using its 1 million-token context window, the agent analyzed the entire codebase, traced the bug to improper connection pooling in a utility module, and proposed a fix with detailed explanation.
What impressed us: Antigravity didn’t just identify the error location, it explained why the pooling configuration caused intermittent failures under load and suggested architectural improvements to prevent similar issues. This level of reasoning reflects Gemini 3’s PhD-level capabilities on complex problem-solving benchmarks.
Technical Capabilities Under the Hood
Gemini 3 Pro Integration
Antigravity runs on Gemini 3 Pro, which tops the LMArena leaderboard with a breakthrough score of 1,501 Elo. The model achieves state-of-the-art performance on coding benchmarks: 76.2% on SWE-bench Verified (measuring coding agent capability) and 1,487 Elo on WebDev Arena (testing web UI generation).
Gemini 3 delivers PhD-level reasoning with top scores on Humanity’s Last Exam (37.5% without tools) and GPQA Diamond (91.9%), demonstrating its ability to handle complex, multi-step software tasks. This intelligence foundation enables Antigravity’s autonomous planning and execution capabilities.
The model’s advanced reasoning, tool use, and agentic coding abilities transform AI assistance from a reactive tool into an active partner that independently validates its own code.
Multi-Model Support
While Gemini 3 Pro serves as the primary intelligence layer, Antigravity integrates Gemini 2.5 Computer Use for browser control and Nano Banana (Gemini 2.5 Image) for image editing tasks.
Developers can also switch to Claude Sonnet 4.5 or OpenAI’s GPT-OSS based on specific task requirements. This multi-model flexibility prevents vendor lock-in and allows teams to optimize for performance, cost, or specialized capabilities.
Artifact System for Transparency
Antigravity’s Artifact system addresses a critical challenge in agentic development: trust. When AI agents operate autonomously, developers need visibility into their decision-making process.
Artifacts provide digestible documentation including:
- Task lists with completion status and timestamps
- Implementation plans explaining architectural decisions
- Screenshots capturing UI states during testing
- Browser recordings showing application walkthroughs
- Error logs with contextual explanations when tasks fail
Developers annotate artifacts with inline comments (similar to Google Docs) to redirect agents mid-task, provide clarifications, or approve specific approaches. This feedback loop happens asynchronously and agents continue working while you review and comment.
MCP and Knowledge Items
Model Context Protocol (MCP) allows Antigravity agents to dynamically pull external context beyond the immediate codebase. Agents can query live database schemas, fetch API documentation, retrieve recent error logs from monitoring tools, or reference internal wiki pages.
Knowledge Items enable teams to save organizational knowledge (coding standards, architectural patterns, security requirements) that agents automatically apply across projects. This creates institutional memory that improves over time as teams document learnings.
Who Should Use Google Antigravity
Best Fit Developer Profiles
Early adopters and experimenters: Developers excited about pushing boundaries of AI-assisted development will find Antigravity’s agentic capabilities cutting-edge.
Full-stack builders: Engineers working across frontend, backend, and infrastructure benefit most from Manager View’s multi-agent coordination.
Startup teams: The free pricing during preview makes Antigravity economically attractive for resource-constrained startups building MVPs rapidly.
Google Cloud users: Developers already in the Google Cloud ecosystem gain tighter integration with Cloud Run, Firebase, and Vertex AI services.
Solo developers: Indie hackers building side projects can leverage agents as virtual team members without hiring costs.
Team and Enterprise Considerations
Enterprise teams benefit from SOC 2, ISO 27001, and FedRAMP compliance available from day one. Google processes all code in tenant-isolated environments by default, with options to opt into data usage for model improvement or keep everything air-gapped.
Organizations requiring dedicated model fine-tuning can access this through Google Cloud contracts a capability third-party tools like Cursor cannot offer at scale. However, enterprises currently using Cursor should evaluate migration carefully, as Antigravity remains in public preview with stability quirks reported by early users.
When Cursor Still Makes Sense
Cursor retains advantages in:
Stability: Cursor feels more polished and stable today, with fewer login loops, quota issues, or agents stalling mid-task.
Refined UX: The interface design and interaction patterns in Cursor are more coherent after years of iteration.
Local-first workflows: Cursor works well in air-gapped or offline scenarios, whereas Antigravity requires cloud connectivity.
Specific integrations: Teams heavily invested in Cursor’s GitHub, Slack, and Jira integrations may face switching costs.
Many power users keep both installed using Cursor for daily coding stability and Antigravity for experimental agentic workflows on greenfield features.
Common Issues and Solutions
Login and Authentication Problems
Issue: Login screen spins indefinitely after clicking “Sign in with Google”.
Solutions:
- Set Chrome as your default browser before launching Antigravity
- On Windows, ensure installation to C: drive (non-default install locations trigger authentication bugs)
- Clear browser cookies for *.google.com domains and retry login
- Restart Antigravity after confirming Chrome default status
Rate Limit Management
Issue: Hitting rate limits after one or two prompts despite “generous limits” promise.
Context: Free tier includes Gemini 3 Pro usage quotas that refresh every 5 hours.
Solutions:
- Break large tasks into smaller subtasks to reduce tokens per request
- Use Editor View for simpler tasks instead of Manager View (which spawns multiple agents consuming quota faster)
- Check your Google Cloud account quota dashboard at console.cloud.google.com
- Upgrade to paid Google Cloud tier for higher limits if building production projects
Browser Extension Setup
Issue: Browser agent fails to launch or control Chrome during testing workflows.
Solutions:
- Install the official Google Antigravity Chrome extension from the Chrome Web Store (link provided in Antigravity settings)
- Grant necessary permissions when prompted (extensions require screen capture and tab control)
- Verify Chrome is version 120 or later (older versions lack required APIs)
- Disable conflicting extensions like ad blockers that interfere with automation
The Developer Experience in Practice
After a week of hands-on testing, Google Antigravity feels simultaneously ambitious and fragile. When agents execute flawlessly, the experience borders on magical features that materialize from natural language descriptions.
However, early preview roughness shows: quota exhaustion after minimal usage, occasional agent stalls requiring manual intervention, and UI glitches inherited from the VS Code fork. The platform trades Cursor’s polish for bleeding-edge agentic capabilities.
What works exceptionally well: Browser-based verification, artifact transparency, multi-model flexibility, and the sheer context window advantage for large codebases.
What needs improvement: Rate limit communication, error recovery when agents fail mid-task, and overall stability polish.
For developers willing to tolerate preview-stage quirks in exchange for groundbreaking agentic workflows, Antigravity delivers substantial productivity gains. For teams prioritizing stability over cutting-edge features, waiting 3-6 months for maturation makes sense.
What’s Next for Google Antigravity
Google teases upcoming features on the roadmap:
Q1 2026: Native mobile preview with Android emulators integrated directly into the IDE.
Q2 2026: WebGPU-accelerated local inference for privacy-sensitive code that cannot leave on-premises environments.
Mid-2026: Collaborative editing with live AI mediation agents that help resolve merge conflicts and facilitate pair programming.
Gemini 3.5 integration: Expected in Q1 2026, pushing context windows to 2 million tokens and adding video understanding for UI/UX feedback based on screen recordings.
Google’s stated vision: “Enable anyone with an idea to experience liftoff and build that idea into reality”. If Antigravity achieves even half this ambition, it will fundamentally reshape software development workflows by 2026.
The platform’s free availability during preview, combined with Gemini 3’s benchmark-topping performance, positions Antigravity as a serious challenger to established AI coding tools. Whether it “kills Cursor” remains to be seen but competition benefits all developers.
Google Antigravity vs Cursor: Feature Comparison
| Feature | Google Antigravity | Cursor |
|---|---|---|
| Pricing (Individual) | Free during preview | $20-$40/month |
| Primary AI Model | Gemini 3 Pro (1501 Elo) | GPT-4, Claude 3.5 Sonnet |
| Context Window | 1 million tokens | ~100K tokens effective |
| Autonomous Agents | Full autonomy with Manager View | Limited agent mode |
| Browser Testing | Yes, native Chrome control | No, manual testing required |
| Artifact System | Yes, task lists + recordings | No equivalent feature |
| Multi-Agent Workflows | Yes, parallel execution | Single-threaded |
| Code Completion | Tab autocomplete included | Advanced tab completion |
| SWE-bench Verified Score | 76.2% | ~72-74% (model-dependent) |
| Multi-Model Support | Gemini 3, Claude 4.5, GPT-OSS | GPT-4, Claude 3.5 |
| Platform Availability | Windows, macOS, Linux | Windows, macOS, Linux |
| Stability (Nov 2025) | Preview, some bugs | Production-stable |
| Refactoring Accuracy | 94% on complex tasks | 78% on complex tasks |
| Enterprise Compliance | SOC 2, ISO 27001, FedRAMP | SOC 2 Type II |
| Learning Curve | Moderate (new concepts) | Low (familiar patterns) |
Frequently Asked Questions (FAQs)
Can Google Antigravity work with existing VS Code extensions?
Yes, Google Antigravity is built on Microsoft’s VS Code, inheriting compatibility with thousands of existing extensions for languages, themes, linters, and debugging tools. However, some extensions may conflict with Antigravity’s agent features, particularly those that modify editor behavior or capture keystrokes.
Does Google Antigravity require an internet connection?
Yes, Antigravity requires cloud connectivity to access Gemini 3 Pro, Claude Sonnet 4.5, or GPT-OSS models. Unlike Cursor’s local-first options, Antigravity processes code through Google Cloud APIs. Google plans WebGPU-accelerated local inference for privacy-sensitive environments in mid-2026.
Can I use Google Antigravity for commercial projects?
Yes, the public preview has no licensing restrictions preventing commercial use. However, read Google’s terms of service regarding data usage and model training. Enterprises can opt for air-gapped deployments that keep code fully isolated.
What programming languages does Google Antigravity support?
Antigravity supports all languages VS Code handles, including JavaScript, TypeScript, Python, Java, C++, Go, Rust, PHP, Ruby, and more. Gemini 3 Pro performs best on web development (JavaScript/TypeScript), Python, and Java based on benchmark scores.
How do I increase my rate limits?
Free tier limits refresh every 5 hours. To increase limits, link a Google Cloud billing account in Antigravity settings or upgrade to paid Google Cloud quotas. Enterprise contracts include dedicated capacity and custom rate limits.
Can multiple team members use Google Antigravity together?
Yes, though collaborative features remain limited in public preview. Google plans live AI-mediated collaborative editing in mid-2026. Currently, teams share projects via Git while each member runs their own Antigravity instance.
What happens to my code? Does Google train models on it?
By default, Antigravity processes code in tenant-isolated environments. You can opt out of data usage for model improvement in settings. Enterprise customers get air-gapped deployments with SOC 2 and ISO 27001 compliance guaranteeing code never leaves your infrastructure.
Does Google Antigravity replace developers?
No. Antigravity functions as an “active partner” that handles implementation details while developers focus on architecture, requirements, and oversight. You review agent-generated code, provide feedback through artifacts, and make final decisions. It augments productivity rather than replacing human expertise.
Featured Snippet Boxes
What is Google Antigravity?
Google Antigravity is a free AI-first development platform where autonomous agents write, test, and verify entire applications using Gemini 3 Pro. Unlike traditional AI coding assistants, Antigravity gives agents direct access to your editor, terminal, and browser to autonomously plan and execute complex software tasks while you maintain oversight through artifacts and progress reports.
Is Google Antigravity free to use?
Yes, Google Antigravity is completely free during public preview with generous rate limits on Gemini 3 Pro usage that refresh every 5 hours. Individual developers pay nothing, while teams only pay for compute beyond baseline quotas, often cheaper than competitors like Cursor at $20-$40/month.
What are Google Antigravity’s system requirements?
macOS requires Monterey or later with Apple Silicon (M1/M2/M3). Windows needs 64-bit Windows 10 or later. Linux requires glibc ≥ 2.28 and glibcxx ≥ 3.4.25. Download from antigravity.google/download, and set Chrome as your default browser before installation.
Is Google Antigravity better than Cursor?
Google Antigravity outperforms Cursor on complex refactoring (94% vs 78% accuracy), codebase navigation (40% faster), and autonomous capabilities through browser-based testing. However, Cursor remains more stable and polished. Many developers use both Cursor for daily stability, Antigravity for experimental agentic workflows.
How does Google Antigravity work?
Antigravity uses Gemini 3 Pro agents with direct access to your code editor, terminal, and Chrome browser. Give a high-level task like “build a flight tracker app,” and agents autonomously break it into subtasks, write code, run tests in the browser, and generate verification artifacts showing their work all while you provide feedback through inline comments.
What does Google Antigravity’s browser agent do?
The browser agent runs your code in Chrome, observes visual behavior, clicks UI elements, fills forms, captures screenshots, and records walkthroughs then debugs issues it finds. This enables autonomous testing and verification without manual intervention, a capability competitors like Cursor lack.
