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Continue
Dev Tools Open Source Free
β˜…β˜…β˜…β˜…β˜† 4.1/5
Open-source AI coding assistant that connects any model to VS Code or JetBrains.

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TOOL INFO
Dev Tools
Open Source, Free
⭐ 4.1 / 5
www.continue.dev
MORE Dev Tools TOOLS
SAGE'S REVIEW

Continue is an open-source AI coding assistant VS Code extension that lets you bring your own LLM β€” whether that's Claude, GPT-4o, a local Llama model via Ollama, or a self-hosted model β€” to get inline code suggestions, chat-based coding assistance, and codebase-aware Q&A without being locked into any single provider's subscription. For developers who want AI coding assistance but don't want to commit to a single vendor's pricing or data policies, Continue is a flexible alternative.

The 'bring your own model' design is Continue's defining characteristic. You configure it once with your preferred LLM API endpoints, and then get Copilot-style inline suggestions, context-aware chat, and edit commands powered by whatever model you've chosen. Local model support via Ollama is a particularly important feature for teams with data privacy requirements who can't send code to cloud APIs.

Continue's open-source nature means it's highly customizable β€” you can define custom slash commands, add your own context providers, and integrate with your specific toolchain. The tradeoff is that setup requires more technical investment than plug-and-play tools like Copilot or Cline. For individual developers or small teams with strong opinions about their AI stack, Continue gives unprecedented control. For users who want zero-configuration simplicity, Copilot or Cursor are easier starting points.

βœ“ BEST FOR
  • β€’ Developers who want control over which LLM powers their coding assistant
  • β€’ Teams with data privacy requirements that preclude sending code to cloud APIs
  • β€’ Open-source advocates who want a transparent, customizable AI coding tool
  • β€’ Engineers exploring different models for different coding tasks (fast local model for autocomplete, powerful cloud model for complex reasoning)
⚠ WATCH OUT FOR
  • β€’ More setup required than plug-and-play tools β€” not for beginners
  • β€’ Quality of suggestions depends on the model you configure β€” cheaper models produce worse results
  • β€’ Local model inference requires sufficient GPU/CPU resources for good performance
  • β€’ Some advanced features require technical configuration that can be fiddly to set up
🐱 SAGE SAYS

If data privacy is your primary concern, Continue + Ollama + a local model is the best path to capable AI coding assistance that never sends your code outside your machine.
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