🔍 What is Continue?

Continue is an open-source AI code assistant that integrates directly into VS Code and JetBrains IDEs, giving developers complete control over their AI coding experience. Unlike proprietary assistants, Continue uses local or cloud-based AI models of your choice—whether it's OpenAI's GPT-4, Anthropic's Claude, local models via Ollama, or custom fine-tuned models. This flexibility makes Continue a favorite among developers who want privacy, customization, or the ability to use the latest models without waiting for vendor updates.\n\nContinue provides two main interaction modes: the chat panel for conversational coding assistance and inline editing for code generation and refactoring. It supports features like code editing with natural language commands, multi-file editing, slash commands for common actions, and custom context providers. Because it's open-source, the community has built extensions for documentation search, issue tracking integration, and custom model backends.\n\nThe platform's architecture is modular and extensible. Developers can configure custom model providers, create custom slash commands, build context providers that pull information from external systems, and contribute to the codebase. Continue's MIT license ensures it stays free and community-driven. The tool is particularly popular among developers who work with sensitive codebases where sending code to third-party APIs is not permissible, as they can run models entirely locally.

✨ Key Features

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Model Agnosticism Use any AI model—OpenAI, Anthropic, local models via Ollama/LM Studio, or custom endpoints—giving you full control over cost and privacy.

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Open Source & Extensible MIT-licensed with a plugin architecture for custom context providers, slash commands, and model backends built by the community.

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Multi-File Editing Generate and edit code across multiple files simultaneously with awareness of project structure and dependencies.

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Inline Code Editing Select code blocks and instruct the AI to modify, refactor, or explain them directly in the editor without leaving your workflow.

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Custom Context Providers Pull context from documentation, issue trackers, databases, or internal tools to ground AI responses in your specific project data.

💰 Pricing

Open Source (Self-Hosted)

Free

Full access to all features with your own API keys or local models. No restrictions, no data collection.

Continue Cloud

TBD

Hosted version with managed model access, team collaboration features, and simplified setup (coming soon).

📊 Pros and Cons

Pros

Complete privacy control—use 100% local models with no data ever leaving your machine
Model flexibility means you're never locked into a single AI provider's ecosystem
Active open-source community with rapid feature development and extensive customization options

Cons

Requires technical setup and configuration compared to plug-and-play proprietary alternatives
No built-in hosting means you need your own API keys or local hardware for model inference

🎯 Best For

Privacy-conscious developers who need AI assistance but cannot send code to third-party APIs Developers who want to experiment with and switch between different AI models freely Teams building custom AI coding workflows that require deep integration with existing tools and data sources

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