Continue

Overview

Continue is a fully open-source AI coding plugin that supports both VS Code and the entire JetBrains suite (IntelliJ, PyCharm, WebStorm, etc.). Its core philosophy is "model freedom"—you can connect OpenAI, Anthropic, local Ollama models, or even self-hosted open-source models to build a fully private and controllable AI coding assistant. It supports a complete set of capabilities including code completion, chat, code editing, and @ context references, making it the top choice for enterprise intranets and data-sensitive scenarios.

Core features: fully open source, model freedom, dual VS Code + JetBrains support, locally deployable.

Installation

Continue is installed from the IDE extension marketplace. The installation steps differ slightly between VS Code and JetBrains; after installation you need to set up models in the config file.

# === VS Code install ===
1. Open VS Code → Extensions panel (Cmd/Ctrl+Shift+X)
2. Search for "Continue" → install
# Or via command line:
code --install-extension Continue.continue

# === JetBrains install ===
1. Open the IDE → Settings → Plugins → Marketplace
2. Search for "Continue" → Install → restart

# === Configure models ===
# Config file location: ~/.continue/config.json (the .continue folder in your home directory)

After installation a Continue icon appears in the sidebar; opening it for the first time guides you through configuring your first model.

Basic Usage

Continue is configured via config.json. Below is an example that connects Claude and a local Ollama model. Once configured, use Cmd/Ctrl+L to open Chat, Cmd/Ctrl+I for inline editing, and Tab to accept completions.

# ~/.continue/config.json example
{
  "models": [
    {
      "title": "Claude Sonnet",
      "provider": "anthropic",
      "model": "claude-sonnet-4-5",
      "apiKey": "your ANTHROPIC_API_KEY"
    },
    {
      "title": "Local Llama",
      "provider": "ollama",
      "model": "llama3"
    }
  ],
  "tabAutocompleteModel": {
    "title": "Local Llama",
    "provider": "ollama",
    "model": "deepseek-coder"
  }
}

# Common shortcuts
Cmd/Ctrl + L    # Open Chat
Cmd/Ctrl + I    # Inline-edit the selected code
Tab             # Accept completion

Local models require installing Ollama (ollama.com) first and pulling the model: ollama pull deepseek-coder

Tips

Continue's greatest value lies in data privacy and cost control: use a local Ollama model for completion (free, offline, no code leakage) and a cloud LLM for complex conversations. @codebase lets the AI search the entire codebase; @docs references official docs; custom slash commands can codify common workflows. Enterprises can self-host a model proxy for unified management.

# Context references
"@codebase Where is the entry point of this project?"
"@docs Latest usage of React useState"
"@terminal How do I fix the error just now?"

# Custom slash commands (~/.continue/config.json)
"customCommands": [{
  "name": "test",
  "description": "Write tests for the selected code",
  "prompt": "Write unit tests for the following code: {{{input}}}"
}]

# Use a local model for completion + a cloud model for chat
# tabAutocompleteModel uses ollama, models uses claude

Tip: For local completion models, deepseek-coder or starcoder2 are recommended—small, fast, and good quality.

Configuration

Continue is configured through ~/.continue/config.json. The models array defines chat models (provider, model, apiKey), and tabAutocompleteModel sets the completion model. Supported providers include OpenAI, Anthropic, Ollama, and self-hosted endpoints. Custom slash commands codify reusable workflows. Local Ollama models give free, offline completion while a cloud LLM handles complex chat.

# ~/.continue/config.json
{
  "models": [
    {
      "title": "Claude Sonnet",
      "provider": "anthropic",
      "model": "claude-sonnet-4-5",
      "apiKey": "your ANTHROPIC_API_KEY"
    },
    {
      "title": "Local Llama",
      "provider": "ollama",
      "model": "llama3"
    }
  ],
  "tabAutocompleteModel": {
    "title": "Local Coder",
    "provider": "ollama",
    "model": "deepseek-coder"
  },
  "customCommands": [{
    "name": "test",
    "description": "Write tests for the selected code",
    "prompt": "Write unit tests for: {{{input}}}"
  }]
}

# Local model (free, offline completion)
ollama pull deepseek-coder

Use a local Ollama model for completion (free, offline, no code leakage) and a cloud LLM for complex chat.

FAQ

Common questions cover data privacy, local models, provider support, cost, and @ context references. With a local Ollama model no code leaves your machine. Continue supports OpenAI, Anthropic, Google, Ollama, and self-hosted endpoints. @codebase searches the whole project and @docs references official docs.

Q: Is my code sent anywhere?
A: Only if you configure a cloud provider. With a local Ollama model,
   completion runs entirely on your machine—no code leaves.

Q: Which providers are supported?
A: OpenAI, Anthropic, Google, Ollama, LM Studio, and any OpenAI-compatible
   endpoint. Configure them in ~/.continue/config.json.

Q: How do I cut costs?
A: Use a local Ollama model for completion (free) and a cloud model only
   for complex chat tasks.

Q: What do @ references do?
A: @codebase searches the whole project, @docs references official docs,
   @file adds a specific file, @terminal references terminal output.

Q: Does it work in JetBrains IDEs?
A: Yes—Continue supports VS Code and the entire JetBrains suite
   (IntelliJ, PyCharm, WebStorm, etc.).

For local completion models, deepseek-coder or starcoder2 are recommended—small, fast, and good quality.