OpenAI Codex vs Google Antigravity
Detailed comparison of features, performance, and use cases
96/100
OpenAI Codex
OpenAI's flagship agentic coding platform combining Codex Web (autonomous cloud agent powered by o3) and Codex CLI (open-source local tool using GPT-5), delivering end-to-end software development with PR automation and multimodal input support.
Quick Verdict
OpenAI Codex excels at autonomous development and pr automation with a score of 96/100. OpenAI Codex has emerged as a legitimate Claude Code challenger, with GPT-5.
91/100
Google Antigravity
Google's revolutionary AI-powered IDE that enables autonomous AI agents to handle complex coding tasks through an agent-first approach with dual interface views.
Quick Verdict
Google Antigravity excels at agentic workflows and ai-native development with a score of 91/100. Google Antigravity represents a paradigm shift in AI-assisted development, moving beyond code completion to full agentic automation.
📊 Visual Score Comparison
Side-by-side comparison of key performance metrics across six evaluation criteria
Technical Specifications
| Feature | OpenAI Codex | Google Antigravity |
|---|---|---|
| Core AI Model(s) | Codex Web uses specialized o3 optimized for coding. Codex CLI uses GPT-5 by default with support for GPT-5.1-Codex-Mini for extended local usage. | Powered by Google's Gemini 3 Pro model as default, with support for Anthropic's Claude Sonnet 4.5 and OpenAI's GPT-OSS for flexible model selection. |
| Context Window | Large context via o3/GPT-5. Repository preloading enables full codebase understanding without manual file selection. | Supports large context windows through Gemini 3 Pro's advanced architecture, with multimodal processing of code, images, and design mocks. |
| Deployment Options | Codex Web runs in OpenAI's cloud sandboxes. Codex CLI is open-source and runs locally. Enterprise deployment options available. | Available as a downloadable desktop application for Windows, macOS, and Linux. Currently in public preview with enterprise features planned. |
| Offline Mode | Codex CLI supports local execution. Codex Web requires internet for cloud sandbox operation. | Limited offline capabilities; core agentic features require cloud connectivity for AI model inference and agent orchestration. |
Core Features Comparison
OpenAI Codex Features
- Dual-mode operation: Codex Web (cloud sandbox) and Codex CLI (local execution)
- Autonomous task execution running 1-30 minutes independently in cloud sandboxes
- Auto-review PRs with semantic understanding beyond static analysis
- Multimodal inputs: screenshots, diagrams, and images for context
- MCP (Model Context Protocol) integration for external tools
- Open-source CLI under permissive license
- Repository preloading for full codebase understanding
Google Antigravity Features
- Agentic development with autonomous AI agents
- Dual interface: Editor View and Manager View
- Artifact transparency system for trust verification
- Multimodal capabilities (code, images, design mocks)
- Multi-model support (Gemini 3 Pro, Claude Sonnet 4.5, GPT-OSS)
- Self-improvement mechanism learning from user feedback
Pricing & Value Analysis
| Aspect | OpenAI Codex | Google Antigravity |
|---|---|---|
| Pricing URL | View OpenAI Codex Pricing | View Google Antigravity Pricing |
| Overall Score | 96/100 | 91/100 |
| Best For | Autonomous Development, PR Automation, ChatGPT Ecosystem, Multimodal Coding, Enterprise Teams | Agentic Workflows, AI-Native Development, Multi-Agent Orchestration |
Best Use Cases
OpenAI Codex Excels At
- Autonomous feature implementation: describe the task, Codex works independently in a cloud sandbox for up to 30 minutes, then returns completed code with PR
- Automated PR review: tag Codex on any PR for semantic review that understands intent, runs tests, and catches bugs beyond static analysis
- Multimodal debugging: share screenshots of UI bugs or architecture diagrams—Codex interprets visual context to understand and fix issues
- Codebase exploration: ask questions about unfamiliar repositories, Codex navigates and explains code structure with full context
Google Antigravity Excels At
- Orchestrating multiple AI agents to work on different parts of a large codebase simultaneously
- End-to-end feature development from design mocks to implementation using multimodal AI
- Complex refactoring tasks with autonomous planning, execution, and validation by AI agents
Performance & Integration
| Category | OpenAI Codex | Google Antigravity | Winner |
|---|---|---|---|
| IDE Support | IDE-agnostic via CLI. Integrates with GitHub for PR workflows. ChatGPT desktop and web interfaces. | Google Antigravity is a standalone AI-native IDE. Integrates with Google Cloud services and supports extensions. | Tie |
| Community | Active community | Active community | Tie |
| Data Richness | Comprehensive | Comprehensive | Tie |
| Overall Score | 96/100 | 91/100 | OpenAI Codex |
The Bottom Line
Both OpenAI Codex and Google Antigravity are capable AI coding tools, but they serve different needs. OpenAI Codex scores higher (96/100 vs 91/100) and excels in autonomous development and pr automation. The choice depends on your specific workflow, team size, and technical requirements.
Choose OpenAI Codex if: you prioritize autonomous development and pr automation and want the higher-rated option (96/100).
Choose Google Antigravity if: you prioritize agentic workflows and ai-native development and don't mind a slightly lower score for specialized features.