When comparing Cursor and Windsurf as LLM (Large Language Model) wrappers, both offer unique features, but they are designed with slightly different use cases and functionalities in mind. Here's a detailed comparison between the two:

1. Purpose & Focus:​

• Cursor:
  • Primarily focuses on providing a smooth and powerful interface to interact with LLMs like GPT models.
  • Emphasizes productivity features for developers, such as easy integration into coding workflows, instant code generation, and debugging help.
  • Supports real-time collaboration for teams working on LLM-powered applications.
• Windsurf:
  • Focuses on building robust and extensible LLM-based applications with a more comprehensive suite of tools for creating custom models.
  • Offers enhanced features for model customization, including tools for fine-tuning, training, and handling complex data pipelines.
  • Geared more toward users who are building AI-driven systems or need deep model integration.

2. Features:​

• Cursor:
  • Code Editor Integration: Offers seamless integration with IDEs like VSCode, making it ideal for developers who need quick AI code suggestions, completions, and documentation.
  • Real-Time Collaboration: Allows multiple team members to work collaboratively on code, leveraging LLMs to assist in coding tasks.
  • Model Accessibility: Provides a simplified interface to access models like OpenAI’s GPT, with a focus on low-code setups.
  • Instant Feedback: Provides real-time feedback for code quality, improvements, and potential issues.
• Windsurf:
  • Custom Model Building: Enables deep customization of models by providing tools for training, fine-tuning, and integration with various data sources.
  • Data Handling: Great for managing and processing large datasets, essential for users looking to create tailored, high-performing models.
  • Extensibility: Offers a more developer-centric environment with APIs for managing data, running inference, and fine-tuning LLMs.
  • Application Deployment: Supports easy deployment of LLMs into production applications, including scaling and maintaining them over time.

3. Ease of Use:​

• Cursor:
  • User-friendly interface designed for developers of varying expertise levels, with an emphasis on productivity.
  • Aimed at those who want quick and efficient access to LLM capabilities without delving deep into model management or customization.
• Windsurf:
  • More complex, suitable for users who need to integrate custom models into sophisticated applications.
  • Requires more technical knowledge to set up, especially for fine-tuning models and managing datasets.

4. Target Audience:​

• Cursor:
  • Ideal for developers, programmers, or data scientists who need an easy-to-use wrapper for integrating LLMs into their coding environment.
  • Best suited for individuals or small teams looking to use LLMs for productivity, code generation, or writing assistance.
• Windsurf:
  • Best suited for teams or enterprises working on more complex AI applications that need to create custom AI models and deploy them.
  • Ideal for users involved in data-intensive tasks or model training, especially those needing deep control over their models.

5. Customization & Flexibility:​

• Cursor:
  • More focused on user experience and ease of use rather than deep customization.
  • Offers pre-configured setups for common use cases (e.g., coding assistance, documentation generation).
• Windsurf:
  • Provides advanced customization options, including fine-tuning, custom model architecture, and control over training parameters.
  • Great for users who need more granular control over the model's performance and behavior.

6. Pricing & Plans:​

• Cursor:
  • Typically follows a subscription-based pricing model with different tiers based on usage and collaboration features.
  • May offer a free tier with basic features and paid plans for advanced functionality and additional users.
• Windsurf:
  • Pricing may depend on model usage, customization, and infrastructure costs (especially if training or fine-tuning is involved).
  • Offers more flexibility in terms of enterprise-level pricing, with potential support for large-scale deployments.

Conclusion:​

• Choose Cursor if:
  • You need a quick, user-friendly interface for interacting with LLMs, especially for code generation, documentation, and productivity tools.
  • You prefer a simple solution without getting into the complexities of model training or custom data pipelines.
• Choose Windsurf if:
  • You are building custom AI applications, need to fine-tune models, or need deep integration with data workflows.
  • You require more control over training, customization, and deployment of LLMs for advanced use cases.

Windsurf does unlimited revisions on freeplan. It's like letting AI create files, edit files and execute. However, its not always right. have been experimenting on developing a MVP for an AI agent, just let the AI correct its own mistakes including creating and editing and testing the file on loop for 3 hours straight. If you are lazy to write 1000 lines of code, this may work. But Human intervention is needed