What is Google Antigravity IDE: A Comprehensive Review and Comparison

About 8 min

What is Google Antigravity IDE: A Comprehensive Review and Comparison

Google Antigravity IDE represents a significant leap forward in AI-powered development tools. Launched on November 18, 2025, this "agent-first" integrated development environment is not just another code editor with AI features—it's a fundamentally new approach to software development that delegates complex coding tasks to autonomous AI agents. What makes Antigravity particularly compelling is its mature foundation: it's built by the same team that created Windsurf, one of the most advanced AI coding tools, and backed by Google's $2.4 billion investment in the technology.

The Windsurf Connection: A Proven Team

The $2.4 Billion Deal

In July 2025, Google made a strategic move that would reshape the AI coding landscape. The company entered into a $2.4 billion licensing agreement with Windsurf, a cutting-edge AI code generation startup. More importantly, Google hired Windsurf's CEO Varun Mohan, co-founder Douglas Chen, and key members of the research and development team to join its DeepMind division, specifically to work on agent-based coding projects related to Gemini.

This acquisition wasn't just about acquiring technology—it was about acquiring expertise. The Windsurf team had already proven their ability to build sophisticated AI coding tools, and Google recognized the value of bringing this experienced team in-house to accelerate the development of what would become Antigravity.

Why This Matters

The Windsurf team's background is crucial to understanding Antigravity's maturity:

Proven Track Record: Windsurf was already a respected name in AI-assisted development before the acquisition
Deep Expertise: The team had years of experience building and refining AI coding tools
Google Resources: Combined with Google's infrastructure and Gemini models, this expertise is now backed by massive resources
Rapid Development: The team could leverage existing Windsurf technology and Google's infrastructure to build Antigravity quickly

This isn't a startup's first attempt at an AI IDE—it's a mature product built by experienced developers with the backing of one of the world's largest tech companies.

What Makes Antigravity Special?

Agent-First Architecture

Unlike traditional AI coding assistants that provide suggestions or complete code snippets, Antigravity introduces an "agent-first" development paradigm. This means:

Autonomous AI Agents:

AI agents can work independently on complex tasks
Agents have direct access to the editor, terminal, and integrated browser
They can learn from previous interactions and improve over time
Agents generate verifiable "artifacts" like task lists, implementation plans, screenshots, and browser recordings

Parallel Processing:

Agents can work across multiple workspaces simultaneously
Each agent can handle different aspects of a project independently
This enables true parallel development workflows

Transparency and Verification:

Every agent action generates verifiable artifacts
Developers can review what agents did, not just the final code
This builds trust and makes debugging agent behavior possible

Built on Visual Studio Code Foundation

Antigravity is built as a fork of Visual Studio Code, which means:

Familiar Interface: Developers already comfortable with VS Code will feel at home
Plugin Compatibility: Most VS Code extensions work out of the box
Proven Stability: Built on a mature, battle-tested codebase
Rich Ecosystem: Access to VS Code's extensive plugin marketplace
Cross-Platform: Available for Windows, macOS, and Linux

This foundation ensures Antigravity isn't starting from scratch—it's building on years of IDE development and refinement.

Multi-Model AI Support

While Gemini 3 Pro is the primary model, Antigravity supports multiple AI providers:

Google Gemini 3 Pro: Primary model with 1 million token context window
Anthropic Claude Sonnet 4.5: Alternative for different use cases
OpenAI Models: Including open-source variants
Model Switching: Easy switching between models based on task requirements

This flexibility allows developers to choose the best model for each specific task, rather than being locked into a single provider.

Antigravity vs. Cursor: Detailed Comparison

Both Antigravity and Cursor are AI-powered IDEs, but they take fundamentally different approaches. Here's a comprehensive comparison:

Architecture and Philosophy

Aspect	Google Antigravity	Cursor
Core Philosophy	Agent-first: AI agents work autonomously	AI-assisted: AI provides suggestions and completions
Base Platform	VS Code fork	VS Code fork
AI Integration	Deep integration with autonomous agents	Integrated AI chat and code completion
Task Delegation	Full task delegation to agents	User-driven with AI assistance

Antigravity's Advantage:

True autonomous agents can handle entire features or modules
Less manual intervention required
Better for complex, multi-step tasks
Agents can work while you focus on other things

Cursor's Advantage:

More control over the development process
Better for learning and understanding code
Simpler mental model for developers

AI Model Support

Feature	Google Antigravity	Cursor
Primary Model	Gemini 3 Pro	GPT-4 / GPT-4 Turbo
Alternative Models	Claude Sonnet 4.5, OpenAI variants	Limited model switching
Context Window	Up to 1 million tokens	Varies by model
Model Flexibility	Easy switching between models	Primarily OpenAI ecosystem

Antigravity's Advantage:

Access to Google's latest Gemini models
Multi-provider support reduces vendor lock-in
Massive context window enables working with entire codebases
Can leverage different models for different tasks

Cursor's Advantage:

Deep integration with OpenAI's ecosystem
Proven performance with GPT-4
Consistent model behavior

Code Generation and Assistance

Capability	Google Antigravity	Cursor
Code Completion	✅ Advanced	✅ Excellent
Multi-file Editing	✅ Agent-driven across files	✅ User-guided
Code Review	✅ Agent-generated reviews	✅ AI-assisted review
Refactoring	✅ Autonomous refactoring	✅ AI-suggested refactoring
Debugging	✅ Agent-assisted debugging	✅ AI debugging help
Terminal Integration	✅ Agents can use terminal	✅ AI terminal commands

Antigravity's Advantage:

Agents can make changes across multiple files autonomously
Less context switching between files
Agents can run terminal commands and verify results
More comprehensive code changes in single operations

Cursor's Advantage:

More predictable code generation
Better for incremental development
Easier to review changes before applying

Developer Experience

Aspect	Google Antigravity	Cursor
Learning Curve	Moderate (agent concepts)	Low (familiar VS Code)
Setup Complexity	Simple (free preview)	Simple
Documentation	Growing	Extensive
Community	New, growing	Established
Plugin Ecosystem	VS Code compatible	VS Code compatible
Performance	Fast (optimized agents)	Fast

Antigravity's Advantage:

Free during preview period
Generous rate limits for Gemini 3 Pro
Backed by Google's resources
Innovative agent-first approach

Cursor's Advantage:

Mature community and documentation
More tutorials and resources available
Established best practices
Proven track record

Pricing and Availability

Feature	Google Antigravity	Cursor
Free Tier	✅ Free preview with generous limits	✅ Free tier available
Paid Plans	TBD (preview period)	$20/month Pro
Student Discount	Not yet announced	Available
Enterprise	Coming soon	Available

Current Status:

Antigravity is completely free during the public preview period
Generous rate limits for Gemini 3 Pro usage
No credit card required
Future pricing not yet announced

Key Features Deep Dive

1. Autonomous Agent System

Antigravity's agent system is its most distinctive feature. Here's how it works:

Agent Capabilities:

Can read and understand entire codebases
Makes changes across multiple files
Runs tests and verifies functionality
Generates documentation
Creates implementation plans
Takes screenshots for verification
Records browser interactions

Example Workflow:

Developer: "Add user authentication to this app"
Agent: Creates task list, implementation plan
Agent: Modifies multiple files (routes, models, views)
Agent: Runs tests to verify changes
Agent: Generates summary of changes
Developer: Reviews artifacts and approves

2. Verifiable Artifacts

Every agent action produces verifiable artifacts:

Task Lists: What the agent plans to do
Implementation Plans: How it will do it
Screenshots: Visual proof of changes
Browser Recordings: For web development tasks
Code Diffs: Clear before/after comparisons

This transparency is crucial for trust and debugging.

3. Multi-Workspace Support

Agents can work across multiple workspaces simultaneously:

Work on different features in parallel
Each workspace can have its own agent
Agents can coordinate between workspaces
Enables true parallel development

4. Integrated Browser

Antigravity includes an integrated browser for web development:

Agents can interact with web applications
Visual verification of changes
Testing in real browser environment
Screenshot capture for documentation

5. Terminal Integration

Agents have full terminal access:

Run build commands
Execute tests
Install dependencies
Run migrations
Verify changes work correctly

Use Cases and Best Practices

Ideal Use Cases for Antigravity

1. Complex Feature Development:

Multi-file refactoring
Adding new features across the stack
Implementing design patterns
Setting up project infrastructure

2. Code Migration:

Upgrading frameworks
Converting between languages
Modernizing legacy code
Porting between platforms

3. Documentation Generation:

API documentation
Code comments
README files
Architecture diagrams

4. Testing and QA:

Writing test suites
Generating test data
Creating test scenarios
Verifying functionality

5. Learning and Exploration:

Understanding new frameworks
Exploring codebases
Learning best practices
Prototyping ideas

Best Practices

1. Start with Clear Instructions:

Be specific about what you want
Provide context about your codebase
Set clear success criteria

2. Review Agent Artifacts:

Always review task lists and plans
Check screenshots and recordings
Verify code changes before committing

3. Use Incremental Development:

Break large tasks into smaller ones
Test after each agent operation
Build trust gradually

4. Leverage Multi-Agent Workflows:

Use different agents for different tasks
Parallelize independent work
Coordinate agents for complex projects

5. Monitor Agent Behavior:

Review artifacts regularly
Adjust instructions based on results
Learn agent capabilities and limitations

Current Limitations and Considerations

As a New Product

1. Ecosystem Maturity:

Smaller community compared to Cursor
Fewer tutorials and resources
Best practices still emerging
Plugin compatibility testing ongoing

2. Agent Reliability:

Agents may make mistakes on complex tasks
Requires human oversight
May need multiple iterations
Learning curve for effective prompting

3. Documentation:

Documentation is growing but not comprehensive
Some features may be undocumented
Community knowledge base developing
Official support channels still establishing

4. Future Pricing:

Currently free, but pricing unknown
May become paid after preview
Rate limits may change
Enterprise features coming

Technical Considerations

1. Internet Dependency:

Requires connection to Google's servers
May have latency for some operations
Offline mode not available
Data privacy considerations

2. Resource Usage:

Can be resource-intensive
Multiple agents increase load
Large context windows use memory
May slow down on older machines

3. Model Limitations:

Dependent on Gemini 3 Pro availability
Rate limits during preview
Model behavior may vary
Context window limits still apply

Subjective Assessment: Is Antigravity Worth It?

The Verdict: Yes, Especially Now

Why Antigravity Stands Out:

Mature Foundation: Built by the Windsurf team with proven expertise, not a first attempt
Google Backing: $2.4 billion investment shows serious commitment
Innovative Approach: Agent-first architecture is genuinely novel and powerful
Free Preview: No risk to try it during the preview period
VS Code Base: Familiar interface reduces learning curve
Multi-Model Support: Flexibility to choose the best model for each task

When to Choose Antigravity:

✅ You want to delegate complex, multi-file tasks
✅ You're comfortable with AI agents making autonomous decisions
✅ You need to work with large codebases (1M token context)
✅ You want to try cutting-edge AI development tools
✅ You're building new features or refactoring existing code
✅ You want free access to Gemini 3 Pro

When to Stick with Cursor:

✅ You prefer more control over code generation
✅ You want a mature, well-documented tool
✅ You need extensive community support
✅ You're learning to code (Cursor's suggestions are more educational)
✅ You prefer incremental, step-by-step development
✅ You're already invested in Cursor's workflow

The Future Outlook

Antigravity represents a significant shift in how we think about AI-assisted development. While Cursor improves the traditional development workflow, Antigravity reimagines it entirely. The agent-first approach may become the standard for AI coding tools in the future.

Potential Developments:

More sophisticated agent capabilities
Better agent coordination
Improved reliability and accuracy
Expanded model support
Enterprise features and pricing
Enhanced community and documentation

Getting Started with Antigravity

Quick Start Guide

Download Antigravity:
- Visit antigravity.codes
- Download for Windows, macOS, or Linux
- Install following the setup wizard
Sign Up:
- Create account with Google
- Join the public preview
- Verify your email
First Project:
- Open a project folder
- Try a simple agent task: "Add error handling to this function"
- Review the agent's artifacts
- Observe how it works
Explore Features:
- Try multi-file refactoring
- Test terminal integration
- Use the integrated browser
- Experiment with different models

Learning Resources

Official Documentation: Check antigravity.codes/docs
Community Forums: Join discussions and ask questions
Example Projects: Explore sample agent workflows
Video Tutorials: Watch setup and usage guides

Conclusion

Google Antigravity IDE is not just another AI coding tool—it's a glimpse into the future of software development. Built by the experienced Windsurf team and backed by Google's massive investment, Antigravity brings a mature, innovative approach to AI-assisted coding through its agent-first architecture.

Key Takeaways:

Proven Team: Built by Windsurf experts with Google's backing
Agent-First: Autonomous AI agents handle complex tasks
Mature Foundation: Based on VS Code with full plugin support
Multi-Model: Supports Gemini 3 Pro, Claude, and OpenAI models
Currently Free: Generous preview period with no credit card required
Innovative: Represents a new paradigm in AI-assisted development

Comparison with Cursor:

Antigravity excels at autonomous, multi-file tasks
Cursor is better for incremental, controlled development
Both have their place depending on workflow preferences
Antigravity is more innovative; Cursor is more mature

Recommendation:
Given that Antigravity is currently free during the preview period, there's no reason not to try it. The agent-first approach may revolutionize how you develop software, and even if you prefer Cursor's workflow, understanding Antigravity's capabilities will help you stay current with AI development trends.

The future of coding is here, and it's autonomous. Antigravity gives you a front-row seat to experience it.

Ready to try Antigravity?
Download it from antigravity.codes and start exploring the agent-first development paradigm. And if you need powerful infrastructure to support your AI development projects, check out LightNode's high-performance VPS solutions for deploying and testing your applications.