Cursor vs Gemini
Detailed comparison of features, performance, and use cases
95/100
Cursor
An AI-powered code editor built from the ground up for AI programming, offering advanced AI features with a VS Code-like interface.
Quick Verdict
Cursor excels at ai-native development and code refactoring with a score of 95/100. Cursor represents the future of coding environments, built specifically for AI-powered development.
83/100
Gemini
Google's AI with multimodal capabilities and integration with Google services.
Quick Verdict
Gemini excels at google ecosystem and web development with a score of 83/100. Gemini shines within Google's ecosystem, especially for web development and cloud services.
Technical Specifications
| Feature | Cursor | Gemini |
|---|---|---|
| Core AI Model(s) | Supports frontier models including Claude Sonnet 4, OpenAI o3-pro, OpenAI GPT-4.1, Gemini 2.5 Pro, and Claude Opus 4. It also utilizes custom, purpose-built models for features like its native autocomplete, 'Tab'. | Gemini is a family of multimodal models developed by Google DeepMind, including Gemini 2.5 Pro, Gemini 2.5 Flash, Gemini 2.0, and Gemini Nano. |
| Context Window | The Pro plan provides access to maximum context windows. | The context window varies by model. For instance, Gemini 1.5 Pro supports a context window of up to 2 million tokens. |
| Deployment Options | Cursor is a downloadable desktop application for macOS, Windows, and Linux. For teams, it offers an Enterprise plan with SAML/OIDC SSO and SCIM seat management for centralized administration. | Gemini is primarily a cloud-based service available via its web interface and the Gemini API. An on-premises solution is becoming available through Google Distributed Cloud (GDC), which allows organizations to run Gemini models in their own data centers, including in air-gapped environments. |
| Offline Mode | Cursor has offline capabilities. A GitHub repository provides a guide for offline activation, enabling all features to work without a cloud or login requirement in airgapped systems. However, some users have reported difficulty using agent mode specifically in an offline setting. | No, Gemini is a cloud-based service and requires an internet connection. The on-premise GDC deployment still requires the managed hardware solution and is not a standalone offline application. |
Core Features Comparison
Cursor Features
- AI-powered code completion and generation
- Multi-file code editing with AI chat
- Advanced code understanding and refactoring
- Integrated terminal and debugging tools
Gemini Features
- Export to Google Docs and Colab
- Integration with Google Workspace and services
- Multimodal understanding for diagrams and code
- Real-time web access for latest documentation
Pricing & Value Analysis
| Aspect | Cursor | Gemini |
|---|---|---|
| Pricing URL | View Cursor Pricing | View Gemini Pricing |
| Overall Score | 95/100 | 83/100 |
| Best For | AI-Native Development, Code Refactoring, Multi-file Projects | Google Ecosystem, Web Development, Documentation |
Best Use Cases
Cursor Excels At
- Large-scale refactoring across multiple files with AI understanding the full codebase context
- Building complex features by describing functionality in natural language and letting AI generate the implementation
- Code reviews and debugging with AI analyzing relationships between files and suggesting improvements
Gemini Excels At
- Google Cloud development with integrated access to GCP documentation and best practices
- Web development projects with real-time access to the latest framework documentation and examples
- Educational content creation by exporting code explanations and tutorials to Google Docs and Colab
Performance & Integration
| Category | Cursor | Gemini | Winner |
|---|---|---|---|
| IDE Support | Cursor is a standalone code editor that is a fork of VS Code. This allows users to import their existing VS Code extensions, themes, and keybindings with a single click. | Google offers official Gemini extensions for VS Code and the JetBrains suite of IDEs. | Tie |
| Community | Active community | Active community | Tie |
| Data Richness | Comprehensive | Comprehensive | Tie |
| Overall Score | 95/100 | 83/100 | Cursor |
The Bottom Line
Both Cursor and Gemini are capable AI coding tools, but they serve different needs. Cursor scores higher (95/100 vs 83/100) and excels in ai-native development and code refactoring. The choice depends on your specific workflow, team size, and technical requirements.
Choose Cursor if: you prioritize ai-native development and code refactoring and want the higher-rated option (95/100).
Choose Gemini if: you prioritize google ecosystem and web development and don't mind a slightly lower score for specialized features.