Kilo Code screenshot

What is Kilo Code?

Kilo Code is an open source AI coding assistant built directly into VS Code. It helps you plan, build, and fix code through an AI agent interface that works locally on your machine. The tool supports over 500 different models, giving you flexibility in choosing which AI backend to use. Because it runs locally first, your code stays on your computer rather than being sent to external servers. Kilo is designed for developers who want AI assistance without sacrificing privacy or control, and it's free to use since it's open source. You can start using it immediately by installing the VS Code extension.

Key Features

Local-first operation

code processing happens on your machine by default, keeping your work private

Multi-model support

compatible with 500+ AI models so you can choose your preferred provider or run open source models locally

Code planning

helps you think through architecture and approach before writing

Code generation and fixing

assists with writing new code and debugging existing issues

VS Code integration

runs as an extension within your editor for smooth workflow

Open source

free to use and modify, with source code available for inspection

Pros & Cons

Advantages

  • Privacy-focused approach means your code doesn't leave your machine unless you choose
  • No subscription required; being open source keeps it completely free
  • Flexibility to use different AI models based on your needs and preferences
  • Integrates directly into VS Code without requiring separate tools or tabs

Limitations

  • Requires some technical setup if you want to run local models; not as simple as cloud-based alternatives
  • Quality and speed depend heavily on which model you choose and your local hardware
  • Community-driven project, so support may be less formal than commercial tools

Use Cases

Writing new features while maintaining code privacy in regulated industries

Debugging and fixing existing code quickly without manual analysis

Planning complex features or refactoring before implementation

Learning coding patterns by having the AI explain its suggestions

Working offline or in environments with restricted internet access