Kiro vs Cursor
Detailed comparison of features, performance, and use cases
85/100
Kiro
AWS's spec-driven agentic IDE that transforms natural language into structured requirements, designs, and tasks—enabling autonomous AI agents to work for hours or days with persistent context.
Quick Verdict
Kiro excels at agentic workflows and spec-driven development with a score of 85/100. Kiro represents AWS's strategic entry into agentic coding, differentiated by its unique spec-driven development approach.
94/100
Cursor
A polished AI-native code editor with sophisticated hybrid architecture, combining agentic reasoning with vector search for strong cross-file understanding.
Quick Verdict
Cursor excels at ai-native development and code refactoring with a score of 94/100. Cursor delivers the most polished AI-native IDE experience, with seamless integration of frontier models directly into the editing workflow.
📊 Visual Score Comparison
Side-by-side comparison of key performance metrics across six evaluation criteria
Technical Specifications
| Feature | Kiro | Cursor |
|---|---|---|
| Core AI Model(s) | Claude Sonnet 4.5 as primary model, with Auto mode that combines frontier models with prompt caching to optimize quality, latency, and cost. | 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'. |
| Context Window | Large context support through Claude Sonnet 4.5. Persistent context across sessions enables multi-day autonomous work without losing project understanding. | The Pro plan provides access to maximum context windows. |
| Deployment Options | Standalone IDE (Code OSS-based) for macOS, Windows, Linux. CLI available for macOS and Linux. No AWS account required—sign in with GitHub, Google, AWS Builder ID, or IAM Identity Center. | 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. |
| Offline Mode | Cloud-based, requires internet connection. Core agentic features depend on cloud AI inference. | 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. |
Core Features Comparison
Kiro Features
- Spec-driven development with auto-generated requirements.md, design.md, and tasks.md
- Autonomous agent that works for hours/days with persistent context
- Kiro Powers for dynamic context activation (Stripe, Figma, Datadog)
- Property-based testing (PBT) to verify code matches specifications
- Native MCP (Model Context Protocol) integration
- Agent hooks for automated documentation and testing on file events
- Multimodal chat supporting images and UI designs
- Agent steering files for project-specific customization
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
- Native Docker and deployment integration
- Multiple frontier model support (Claude, GPT-4, Gemini)
Pricing & Value Analysis
| Aspect | Kiro | Cursor |
|---|---|---|
| Pricing URL | View Kiro Pricing | View Cursor Pricing |
| Overall Score | 85/100 | 94/100 |
| Best For | Agentic Workflows, Spec-Driven Development, Enterprise Development, AWS Integration, Long-Running Tasks | AI-Native Development, Code Refactoring, Multi-file Projects, Rapid Prototyping |
Best Use Cases
Kiro Excels At
- Converting product requirements into structured specs and implementation plans before writing any code—ensuring alignment between stakeholders and developers
- Running autonomous agents on complex features overnight, returning to completed implementations with full audit trails of decisions made
- Enterprise development where compliance requires traceable specifications that map directly to generated code artifacts
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
Performance & Integration
| Category | Kiro | Cursor | Winner |
|---|---|---|---|
| IDE Support | Kiro is a standalone IDE based on Code OSS. Supports VS Code settings import, Open VSX extensions, and existing themes. CLI available for terminal workflows. | 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. | Tie |
| Community | Active community | Active community | Tie |
| Data Richness | Comprehensive | Comprehensive | Tie |
| Overall Score | 85/100 | 94/100 | Cursor |
The Bottom Line
Both Kiro and Cursor are capable AI coding tools, but they serve different needs. Cursor scores higher (94/100 vs 85/100) and excels in ai-native development and code refactoring. The choice depends on your specific workflow, team size, and technical requirements.
Choose Kiro if: you prioritize agentic workflows and spec-driven development and don't mind a slightly lower score for specialized features.
Choose Cursor if: you prioritize ai-native development and code refactoring and want the higher-rated option (94/100).