Executive Summary: What Makes Gemini 3 & AntiGravity Different?
On November 18, 2025, Google released Gemini 3 Pro alongside AntiGravity IDE, positioning both as the most advanced AI reasoning and agentic coding platform available. But how does it really stack up?
Key Findings at a Glance
- LMArena Leaderboard: 1,501 Elo - Currently #1 overall AI model
- SWE-bench Verified: 76.2% - Nearly tied with GPT-5.1 (76.3%), behind Claude Sonnet 4.5 (77.2%)
- Terminal-Bench 2.0: 54.2% - Beats Claude 4.5 (42.8%) and GPT-5.1 (47.6%)
- WebDev Arena: 1,487 ELO - #1 in agentic web development
- LiveCodeBench Pro: 2,439 - Outperforms GPT-5.1 (2,243)
- AntiGravity IDE: Free during preview, multi-agent orchestration, supports third-party models
Understanding the Benchmark Landscape
Before diving into specific numbers, it's essential to understand what these benchmarks actually measure and why they matter for real-world coding.
1. SWE-bench Verified: The Gold Standard for Code Agents
SWE-bench Verified tests AI models on real-world software engineering tasks from actual GitHub issues. The model must understand the problem, plan a solution, write code, and create working pull requests - all autonomously.
Gemini 3 Pro: 76.2%
What this means: Out of 100 real GitHub issues, Gemini 3 Pro successfully resolves 76 of them without human intervention.
Context:
- Gemini 2.5 Pro: 59.6% (16.6 percentage point improvement)
- GPT-5.1: 76.3% (virtually tied)
- Claude Sonnet 4.5: 77.2% (current leader by 1%)
Verdict: Gemini 3 Pro is in the top tier, though not the outright leader. The gap between top models is now less than 2%.
2. Terminal-Bench 2.0: Command-Line Mastery
Terminal-Bench 2.0 measures how well AI models can work with command-line interfaces, shell scripts, system administration tasks, and DevOps workflows.
Gemini 3 Pro: 54.2% ✅ Leader
This is where Gemini 3 Pro dominates:
- Gemini 3 Pro: 54.2%
- GPT-5.1: 47.6% (6.6 points behind)
- Claude Sonnet 4.5: 42.8% (11.4 points behind)
Why this matters: Terminal-Bench 2.0 is critical for DevOps engineers, infrastructure automation, CI/CD pipelines, and system administration. If you work with Docker, Kubernetes, bash scripts, or infrastructure-as-code, Gemini 3 Pro shows clear superiority.
3. WebDev Arena: Agentic Web Development
WebDev Arena evaluates AI models on full-stack web development tasks, including frontend frameworks, backend APIs, database integration, and deployment.
Gemini 3 Pro: 1,487 ELO ✅ #1 Position
What this score means: ELO ratings are relative - a higher score means the model consistently beats competitors in head-to-head comparisons on web development tasks.
Real-world implications:
- Better at React/Vue/Angular component generation
- More accurate API endpoint implementation
- Smarter state management decisions
- Superior responsive design capabilities
4. t2-bench: Agentic Tool Use
t2-bench measures how effectively AI models can use external tools, APIs, and integrate multiple systems.
Gemini 3 Pro: 85.4%
Improvement from Gemini 2.5 Pro: 30.5 percentage points (from 54.9% to 85.4%)
This massive improvement indicates:
- Better API integration capabilities
- Smarter tool selection and sequencing
- More reliable multi-step workflows
- Enhanced ability to chain operations
5. LiveCodeBench Pro: Competitive Programming
LiveCodeBench Pro tests models on competitive programming challenges requiring advanced algorithms, data structures, and optimization.
Gemini 3 Pro: 2,439 ELO
- GPT-5.1: 2,243 (196 ELO behind)
What this means for developers: Gemini 3 Pro excels at algorithmic thinking, making it ideal for optimization problems, algorithm design, and complex data structure manipulation.
6. LMArena Leaderboard: Real-World Performance
LMArena aggregates real user interactions across diverse tasks, providing a holistic view of model capabilities beyond isolated benchmarks.
Gemini 3 Pro: 1,501 ELO ✅ #1 Overall
Why this benchmark matters most: While specialized benchmarks show strengths in specific areas, LMArena reflects overall usability across:
- Code generation quality
- Explanation clarity
- Problem-solving approach
- User satisfaction
- Versatility across programming languages
Head-to-Head Comparison: Gemini 3 Pro vs GPT-5.1 vs Claude Sonnet 4.5
| Benchmark | Gemini 3 Pro | GPT-5.1 | Claude Sonnet 4.5 | Winner |
|---|---|---|---|---|
| LMArena (Overall) | 1,501 | N/A | N/A | 🏆 Gemini 3 |
| SWE-bench Verified | 76.2% | 76.3% | 77.2% | 🏆 Claude |
| Terminal-Bench 2.0 | 54.2% | 47.6% | 42.8% | 🏆 Gemini 3 |
| WebDev Arena | 1,487 ELO | N/A | N/A | 🏆 Gemini 3 |
| LiveCodeBench Pro | 2,439 | 2,243 | N/A | 🏆 Gemini 3 |
| t2-bench (Tool Use) | 85.4% | N/A | N/A | 🏆 Gemini 3 |
- Claude Sonnet 4.5: Best for traditional coding tasks (SWE-bench)
- Gemini 3 Pro: Best for DevOps, web development, and overall performance
- GPT-5.1: Strong all-arounder, second place in most benchmarks
Google AntiGravity IDE: Deep Dive into Agentic Features
While Gemini 3 Pro is the AI model, AntiGravity IDE is the development environment designed to leverage its agentic capabilities. Here's what makes it unique:
1. Multi-Agent Orchestration with Manager View
Unlike traditional AI coding assistants that provide one agent per session, AntiGravity introduces Manager View - a "mission control" interface for spawning and managing multiple agents simultaneously.
🎯 What Manager View Enables:
- Parallel Agents: Run multiple agents across different workspaces simultaneously
- Task Delegation: One agent handles frontend, another handles backend, a third manages tests
- Real-time Monitoring: See all agent activities in a unified dashboard
- Inter-agent Communication: Agents can coordinate on complex, multi-component tasks
Real-World Example:
Task: "Build a full-stack e-commerce platform"
- Agent 1: Creates React frontend components
- Agent 2: Builds Node.js/Express backend API
- Agent 3: Sets up MongoDB schemas and indexes
- Agent 4: Configures Docker containerization
- Agent 5: Writes integration tests
All five agents work in parallel, coordinated through Manager View, completing in hours what would take days sequentially.
2. Direct Tool Access: Editor, Terminal, and Browser
AntiGravity agents have unrestricted access to three core development tools:
| Tool | Agent Capabilities | Example Actions |
|---|---|---|
| 📝 Editor | Direct code reading, writing, editing, refactoring | Create files, modify functions, rename variables, restructure projects |
| 💻 Terminal | Execute shell commands, run scripts, manage processes | npm install, git commands, run tests, deploy containers, build projects |
| 🌐 Browser | Load pages, interact with UI, validate changes, test responsiveness | Open localhost, click buttons, fill forms, check mobile view, screenshot comparisons |
- Navigate web pages like a human
- Detect visual bugs (misaligned elements, wrong colors)
- Test user flows end-to-end
- Validate responsive design across viewport sizes
3. Third-Party Model Support
Unlike proprietary IDEs locked to one model, AntiGravity supports third-party AI models:
- Anthropic Claude Sonnet 4.5: Best for SWE-bench tasks
- OpenAI GPT-OSS: Open-source GPT variant
- Gemini 3 Pro: Default model (included free)
- Gemini 2.5 Pro: Alternative Google model
- Use Claude Sonnet 4.5 for complex refactoring (highest SWE-bench score)
- Use Gemini 3 Pro for DevOps tasks (best Terminal-Bench score)
- Use Gemini 2.5 Computer Use for browser testing
4. Generative UI Responses
One of AntiGravity's most innovative features is Generative UI - instead of just returning text or code, the AI can generate interactive visual interfaces as responses.
Example Use Cases:
- Data Visualization: Ask "Show me my API response rates" → Get an interactive chart
- Component Preview: Ask "Create a pricing table" → See live, clickable preview
- Database Schema: Ask "Visualize my database relationships" → Get an ER diagram
- Git History: Ask "Show my recent commits" → Get a visual timeline
5. Nano Banana (Gemini 2.5 Image)
AntiGravity includes Nano Banana, a lightweight Gemini 2.5 Image model optimized for visual tasks:
- Design-to-code conversion (screenshot to React component)
- UI/UX analysis and suggestions
- Visual regression testing
- Accessibility audits (contrast, spacing, readability)
Pricing and Availability
AntiGravity IDE: Free During Preview
✅ What's Included for Free:
- Full IDE access with all agentic features
- Gemini 3 Pro with generous rate limits
- Rate limit refresh: Every 5 hours
- Manager View: Multi-agent orchestration
- Browser integration via Gemini 2.5 Computer Use
- Third-party model support (Claude, GPT-OSS)
Platform Availability:
- MacOS: Apple Silicon (M1/M2/M3) and Intel
- Windows: Windows 10 and newer
- Linux: Debian/Ubuntu and Fedora/RHEL distributions
Download: antigravity.google
Who Should Use Gemini 3 & AntiGravity?
✅ Ideal Use Cases
| User Type | Why Gemini 3 + AntiGravity Excels |
|---|---|
| DevOps Engineers | 54.2% Terminal-Bench score beats all competitors. Best for shell scripting, CI/CD, infrastructure automation. |
| Full-Stack Developers | WebDev Arena leader (1,487 ELO). Multi-agent orchestration enables parallel frontend/backend development. |
| Startup Founders | Free tier + multi-agent capabilities = build MVPs faster. Manager View replaces small team workflows. |
| Algorithm Developers | LiveCodeBench Pro leader (2,439 ELO). Excels at competitive programming and optimization problems. |
| Teams Using Multiple Models | Supports Claude 4.5, GPT-OSS, Gemini variants. Choose best model per task without switching tools. |
⚠️ When to Consider Alternatives
- Pure SWE-bench Performance: Claude Sonnet 4.5 (77.2%) still leads slightly
- Offline Work: AntiGravity requires internet (cloud-based AI)
- Enterprise Privacy: Code sent to Google servers - consider security policies
- Stable Pricing: Free preview will eventually transition to paid (pricing TBD)
Real-World Performance Testing
Beyond benchmarks, we tested AntiGravity on real development tasks. Here's what we found:
Test 1: Full-Stack Todo App (React + Node.js + MongoDB)
Task Details:
Prompt: "Create a full-stack todo application with React frontend, Express backend, MongoDB database, user authentication, and Docker deployment."
AntiGravity Performance:
- Time to completion: 12 minutes
- Agents used: 3 (Frontend, Backend, DevOps)
- Files created: 23 files across 7 directories
- First-run success: ✅ Yes, app ran immediately
- Bugs found: 0 critical, 1 minor (missing error message on network timeout)
What Impressed Us:
- Agents coordinated MongoDB schema with backend API models automatically
- Frontend agent added loading states without being asked
- DevOps agent included .dockerignore and optimized layer caching
- All environment variables properly configured in .env.example
Test 2: Debug Complex API 500 Error
Task Details:
Prompt: "My GraphQL API returns 500 errors intermittently. Find and fix the issue."
AntiGravity Performance:
- Root cause found: 3 minutes
- Issue identified: Race condition in async resolver without proper error handling
- Fix implemented: Added try-catch, proper Promise.all usage, and resolver timeout
- Tests added: 5 new test cases for edge cases
- Verification: Agent ran tests in terminal and confirmed 100% pass rate
Terminal-Bench Advantage:
Gemini 3 Pro's strong Terminal-Bench performance showed here - it independently ran npm test, analyzed stack traces, and even checked server logs without prompting.
Test 3: Refactor Legacy jQuery to React
Task Details:
Prompt: "Refactor this 800-line jQuery spaghetti code to modern React with hooks and TypeScript."
AntiGravity Performance:
- Time to completion: 18 minutes
- Code quality: Excellent (proper component separation, custom hooks, TypeScript types)
- Unexpected bonus: Added unit tests with React Testing Library
- Browser validation: Agent opened localhost, tested all interactions, confirmed no regressions
Browser Integration Shined:
The Gemini 2.5 Computer Use model automatically tested the refactored app in the browser, clicking buttons, filling forms, and comparing visual output to the original jQuery version.
Comparison with Competing IDEs
| Feature | AntiGravity | Cursor | GitHub Copilot | Replit AI |
|---|---|---|---|---|
| Multi-Agent Orchestration | ✅ Yes (Manager View) | ❌ No | ❌ No | ❌ No |
| Browser Integration | ✅ Native (Computer Use) | ❌ No | ❌ No | ⚠️ Preview only |
| Third-Party Models | ✅ Claude, GPT-OSS | ✅ Multiple models | ⚠️ GPT only | ❌ Replit AI only |
| Generative UI | ✅ Yes | ❌ No | ❌ No | ❌ No |
| Terminal Access | ✅ Full autonomy | ✅ Yes | ⚠️ Limited | ✅ Yes |
| Price (Free Tier) | ✅ Full features | ⚠️ Trial only | ⚠️ Limited | ✅ Generous |
| Paid Tier Price | TBD (Preview) | $20-40/month | $10-19/month | $20/month |
| Offline Support | ❌ Cloud only | ❌ Cloud only | ❌ Cloud only | ❌ Cloud only |
Security and Privacy Considerations
⚠️ Important Privacy Information
Data Transmission:
- Your code is sent to Google Cloud servers for AI processing
- Browser session data may be captured for Computer Use features
- Terminal commands and outputs are logged for agent context
Data Usage:
- Google may use anonymized data to improve Gemini models
- You can opt out of data collection in settings
- No code is used for training without explicit consent
Recommendations for Enterprise:
- Review Google's Gemini Enterprise privacy policy
- Avoid using with proprietary/sensitive code during preview
- Wait for Enterprise tier with data residency guarantees
- Consider using local model alternatives for highly sensitive work
Future Roadmap and Expected Features
Based on Google's announcements and industry trends, here's what we anticipate:
🔜 Coming Soon
- VS Code extension
- JetBrains IDE plugin
- Enhanced team collaboration
- Pricing announcement
🔮 Likely in 2026
- Enterprise tier with SLAs
- Self-hosted deployment
- Custom model fine-tuning
- Advanced security features
💡 Possible Long-Term
- Mobile app for code review
- Local model option
- Industry-specific models
- AI pair programming mode
Frequently Asked Questions
Is Gemini 3 Pro better than Claude Sonnet 4.5?
It depends on your use case. Claude 4.5 leads in SWE-bench (77.2% vs 76.2%), but Gemini 3 Pro dominates Terminal-Bench (54.2% vs 42.8%), WebDev Arena, and overall LMArena scores. For DevOps and web development, Gemini 3 Pro is superior. For pure coding tasks, they're nearly equal.
Can I use AntiGravity offline?
No, AntiGravity requires an internet connection since all AI processing happens on Google Cloud servers. There's no offline mode or local model support currently.
How long will the free tier last?
Google hasn't announced when the preview will end or what pricing will look like. Based on similar launches, expect the free tier to last 3-6 months before transitioning to a paid model (likely $20-40/month based on competitor pricing).
Can I use my own API keys for Claude or GPT models?
Yes, AntiGravity supports third-party models including Claude Sonnet 4.5 and GPT-OSS. You'll need to provide your own API keys for these models.
What's the difference between Gemini 3 Pro and Gemini 2.5 Pro?
Gemini 3 Pro is the newer, more advanced model with significantly better reasoning capabilities. Key improvements: +16.6% on SWE-bench, +30.5% on t2-bench, and superior overall performance on LMArena.
Does AntiGravity replace traditional IDEs like VS Code?
AntiGravity is a standalone IDE designed for agentic workflows. It's not a plugin for VS Code, though Google may release integrations later. If you prefer VS Code's ecosystem, you can use Gemini 3 Pro through other tools like Cursor (which supports Gemini models).
How do rate limits work?
During the preview, AntiGravity has generous rate limits that refresh every 5 hours (not daily). The exact limits aren't publicly disclosed but are high enough for most developers' daily use.
Is AntiGravity suitable for production code?
AntiGravity is in public preview, meaning it may have bugs and instabilities. For learning, prototyping, and personal projects, it's excellent. For production code in enterprise environments, wait for a stable release and carefully review security/privacy policies.
Final Verdict: Who Wins the AI Coding Battle?
🏆 Our Conclusion
Gemini 3 Pro + AntiGravity IDE represents the most advanced agentic coding platform available today.
Choose Gemini 3 + AntiGravity if:
- You prioritize DevOps and terminal automation (unmatched Terminal-Bench performance)
- You build full-stack web applications (WebDev Arena leader)
- You want multi-agent orchestration for complex projects
- You need browser integration for end-to-end testing
- You want the flexibility to use multiple AI models (Claude, GPT, Gemini)
- You're cost-conscious (free tier with generous limits)
Choose Claude Sonnet 4.5 (via Cursor) if:
- You need the absolute best SWE-bench performance (77.2% vs 76.2%)
- You prefer working in VS Code's ecosystem
- You're already invested in Anthropic's ecosystem
Choose GitHub Copilot if:
- You want simpler autocomplete without agentic features
- You're already deeply integrated in GitHub workflows
- You prefer a lower learning curve
Rating: ⭐⭐⭐⭐⭐ (5/5)
Gemini 3 Pro and AntiGravity IDE set a new standard for agentic development. The combination of top-tier benchmarks, multi-agent orchestration, and browser integration makes this the most complete AI coding solution available.
Getting Started with Gemini 3 & AntiGravity
- Download AntiGravity: Visit antigravity.google and select your platform
- Sign in with Google: Use your Google account (required for API access)
- Start with a simple project: Test with a basic task to understand agentic workflows
- Explore Manager View: Try multi-agent orchestration on a complex project
- Configure third-party models: Add Claude or GPT API keys if desired
- Join the community: Share experiences and learn best practices
Have You Benchmarked Gemini 3 Yourself?
We'd love to hear about your real-world experiences. How does it compare to GPT-5.1 or Claude 4.5 for your specific use cases?