A developer installs the Continue extension in VS Code. In the configuration JSON, they connect their preferred LLM—for example, a locally running Llama 3 model via Ollama. Inside the IDE, the developer highlights a complex, undocumented function. They press a keyboard shortcut (e.g., Cmd+M) to open the Continue sidebar chat and type, "Explain this and add error handling." Because the tool reads the active file context, it generates the refactored code instantly. The developer then clicks a single button or uses a shortcut to apply the generated diff directly into their active editor window.
Continue
Continue (or Continue.dev) is a rapidly growing, open-source AI code assistant designed as a deeply integrated extension for large-scale IDEs, primarily VS Code and JetBrains. Built by developers for developers, it is a direct, privacy-focused, and highly customizable alternative to closed-ecosystem corporate tools like GitHub Copilot.
Its primary differentiator is its established flexibility and "Bring Your Own Model" (BYOM) architecture. Instead of forcing developers to use a proprietary, hidden LLM, Continue allows users to effortlessly plug in any API key (OpenAI GPT-4, Anthropic Claude 3, Google Gemini) or, crucially, connect to local, entirely offline models hosted on their own machine via tools like Ollama.
It is heavily favored by senior engineers, open-source contributors, and enterprise security teams who refuse to send proprietary codebase data to third-party cloud servers, offering them a top-tier generative AI experience while maintaining established data sovereignty.
Best For
- Security-conscious enterprise developers and fintech engineers
- Open-source advocates and senior software architects
- Engineers wanting to test multiple different LLMs (Claude vs GPT-4)
- Developers requiring entirely offline/local AI assistance
How It Works
Key Features
IDE Integration
- Native VS Code and JetBrains extensions
- Inline diff application and editing
- Automated context gathering (active files, terminal errors)
- Customizable keyboard shortcuts
Model Customization
- Bring Your Own Model (BYOM) via API
- Local/Offline model support (Ollama, LM Studio)
- Open-source, extensible architecture
- Complete data privacy control
Pros & Cons
Pros
- The ability to use local, offline models provides established, unbreakable data security for proprietary code
- Being open-source means it evolves highly fast, driven by actual developer pull-requests
- Provides the freedom to switch between the world's best LLMs instantly based on the specific coding language task
- The inline diff and "apply to editor" UI is exceptionally frictionless and fast
Cons
- Requires significantly more technical setup (configuring JSON files, managing API keys, installing Ollama) than the one-click install of Copilot
- Local execution requires a very powerful local machine (high RAM/GPU) to achieve generation speeds comparable to cloud models
- Lacks the large-scale corporate institutional backing and seamless enterprise billing integration of Microsoft/GitHub
- The quality of the autocomplete is entirely dependent on the quality of the specific API or local model you choose to connect
Pricing
Continue itself is an open-source tool and is completely free to install and use. The cost comes entirely from the underlying models the developer chooses to connect. If a user connects local models (Ollama), it is 100% free. If a user connects OpenAI or Anthropic, they pay standard usage-based API costs directly to those providers.
How It Compares
Continue competes directly with GitHub Copilot and Cursor. Cursor is effectively a fork of VS Code, requiring users to switch their entire IDE. GitHub Copilot is the locked-in, paid corporate standard. Continue differentiates itself entirely through flexibility and data sovereignty. It allows developers to keep their existing IDE (VS Code/JetBrains), and gives them established choice over which AI model reads their code, making it the established champion for privacy-obsessed developers who want to run AI locally.