Open-source AI coding agent that works with any model, featuring multi-mode operation (Architect, Coder, Debugger), Memory Bank for persistent project context, and transparent pay-as-you-go pricing.
Watch Kilo Code switch between Architect, Coder, and Debugger modes to complete the task.
💡 This is a simulated example demonstrating typical Kilo Code capabilities. No actual LLM call is made.
| Core Competency | Model Flexibility, Open Source Development, Multi-Mode Workflows, Cost-Conscious Teams, VS Code & JetBrains Users |
|---|---|
| AI Architecture | Model-agnostic: Supports 500+ models including Gemini 3 Pro, Claude 4.5 Sonnet & Opus, GPT-5, and local models via Ollama/LM Studio. |
| Context Window | Depends on selected model. Memory Bank provides persistent context across sessions. |
| Deployment | VS Code extension, JetBrains plugin, and CLI. Fully open-source for self-hosting. |
| Offline Support | Supports local models via Ollama for fully offline operation. |
| IDE Integration | VS Code, all VS Code-based IDEs, JetBrains IDEs, and CLI |
| Company Maturity | 1 years |
| Pricing Model | Freemium - Basic features |
Visual breakdown of this tool's performance across six key evaluation criteria
See how Kilo Code ranks against the top AI coding assistants in our directory
Kilo Code stands out with its model-vendor neutral approach—use any AI provider without lock-in. The Memory Bank feature addresses a key pain point: persistent project context that survives across sessions. Founded by GitLab co-founder Sid Sijbrandij and backed by $8M seed funding, Kilo positions itself as a cost-effective Cursor alternative with transparent pricing. With 750K+ users and 6.1 trillion tokens/month processed, it's gaining significant traction among developers who value flexibility and open-source ethos.
Kilo Code offers solid AI development capabilities with specific technical strengths. Its multi-model architecture leveraging both Anthropic and OpenAI technologies provides exceptional versatility. Unique offline capabilities make it suitable for security-conscious enterprise environments. Best suited for developers requiring advanced AI assistance in their primary development workflow.
**Experienced developers** working in specialized domains or with specific technical requirements.
Status: Private (Kilo-Org)
Founded: 2025
Backing: $8 million seed funding (late 2025)
Model-agnostic: Supports 500+ models including Gemini 3 Pro, Claude 4.5 Sonnet & Opus, GPT-5, and local models via Ollama/LM Studio.
Kilo Code supports VS Code, all VS Code-based IDEs, JetBrains IDEs, and CLI.
Yes, Kilo Code supports offline mode. Supports local models via Ollama for fully offline operation.
Kilo Code scores 81/100 versus Claude Code's 98/100. Kilo Code excels at Model Flexibility and Open Source Development, while Claude Code is known for Agentic Coding and Complex Refactoring.
Kilo Code is best suited for Model Flexibility, Open Source Development, Multi-Mode Workflows, Cost-Conscious Teams, VS Code & JetBrains Users. Multi-stage development workflows using Architect mode for planning, Coder mode for implementation,
Depends on selected model. Memory Bank provides persistent context across sessions.
Primary references: blog, docs, release notes, API, and status pages.
No reviews yet. Share your experience with this tool!
Have experience with Kilo Code? Share your review and help other developers make informed decisions!
See how Kilo Code stacks up against other popular AI coding assistants:
Similar tools based on category and feature overlap:
View full comparison: Top 7 Alternatives to Kilo Code in 2025 →