Continue.dev: The Open Source AI Coding Extension for VS Code and JetBrains
Continue.dev gives you Copilot-style autocomplete and chat for free, with any LLM. Here's what it does well, where it falls short, and how to set it up.
Continue.dev is a free, open source VS Code and JetBrains extension that gives you AI autocomplete, chat, and codebase search without paying a subscription. You connect it to any LLM (Anthropic, OpenAI, Ollama, or dozens of others) and pay only for the API usage you generate. For developers who want Copilot-style features without the $10/month fee, Continue.dev is the most capable option available today.
What Is Continue.dev?
Continue.dev is an IDE extension (VS Code and JetBrains) that adds three AI capabilities to your editor:
Autocomplete - inline code completions as you type, similar to Copilot's ghost text
Chat - a sidebar chat interface for asking questions, explaining code, and writing functions
Codebase context - index your codebase so the AI understands your specific code, not just general programming patterns
The key distinction from Copilot: Continue.dev has no proprietary model. It is a client that connects to any LLM you configure. The quality of autocomplete and chat depends entirely on which model you pick.
How Does Continue.dev Work?
Continue.dev operates as a local client that communicates with LLM providers via API. When you type in your editor, the extension sends context (surrounding code, file contents, and optionally your indexed codebase) to the configured model and receives completions or chat responses. The extension handles prompt construction, context window management, and response rendering.
The architecture is straightforward:
VS Code extension or JetBrains plugin as the UI layer
Configuration file (~/.continue/config.json) that defines models, providers, and behavior
Indexing engine that creates embeddings of your codebase for semantic search
Provider adapters for each LLM (OpenAI, Anthropic, Ollama, etc.)
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A practical setup uses a powerful model (Claude) for chat and a fast, cheap model (Codestral or a local Ollama model) for autocomplete. Autocomplete runs on every keystroke, so cost and latency matter more there than for chat.
Step 3: For local models (zero cost), use Ollama
# Install Ollama
brew install ollama
# Pull a code model
ollama pull codestral
With a local Ollama model for autocomplete and a Claude API key for chat, your total cost is API usage only (roughly $0 to $5/month for moderate use).
Step 4: Index your codebase
Open the Continue sidebar and click "Index codebase." Continue scans your project, creates embeddings, and makes your code searchable. After indexing, you can use @codebase in chat to ask questions that span your entire project.
Best Practices for Continue.dev
To get the most out of Continue.dev, follow these best practices:
Use separate models for chat and autocomplete. Chat benefits from a powerful, context-aware model like Claude Sonnet or GPT-4o. Autocomplete needs speed and low cost (Codestral or a local Ollama model like codestral or deepseek-coder) works best.
Index your codebase early. The @codebase feature is one of Continue's strongest capabilities, but it requires indexing. Run it once after setup and re-index when your project structure changes significantly.
Tune autocomplete triggers. In settings, you can adjust the debounce delay and max suggestions. Lower debounce (e.g., 100ms) gives faster completions but may increase API calls. Higher debounce (e.g., 300ms) reduces noise.
Use @file and @docs for precise context. Instead of asking vague questions, reference specific files or documentation URLs. This dramatically improves response relevance.
Experiment with different models. Continue makes it trivial to switch models. Try Mistral Codestral for autocomplete, DeepSeek Coder for chat, or Llama 3 for local-only setups. Each has different strengths.
How Autocomplete Quality Compares to Copilot
This is the honest part. Continue.dev's autocomplete with a strong model is competitive with Copilot on code you've been working on recently. When you have multiple related files open and a well-indexed codebase, Continue's suggestions are often highly relevant.
Where Copilot has a consistent edge: general programming patterns. Copilot is trained on a specific dataset and optimized for autocomplete in a way that Continue.dev is not. For boilerplate, common patterns, and code you haven't written before, Copilot's ghost text completions tend to be more accurate with fewer irrelevant suggestions.
Where Continue.dev can be equivalent or better: your own codebase. Once you've indexed your project and the AI has context about your specific architecture, naming conventions, and patterns, Continue can produce suggestions that feel very specific to your code rather than generic.
The gap is real but not dramatic. For a developer primarily working in their own codebase (not constantly writing code in unfamiliar territory), Continue's autocomplete with a good model is a workable Copilot replacement.
Codebase Context and Chat
The @codebase feature is where Continue.dev genuinely excels. In the chat sidebar, type @codebase how does authentication work in this project? and Continue searches the indexed codebase, finds the relevant files, and answers with actual references to your code.
You can also reference specific files directly:
@file src/auth/middleware.ts explain what this does
Or reference documentation:
@docs https://nextjs.org/docs explain the app router
The chat experience with Claude claude-3-5-sonnet is comparable to Copilot Chat with GPT-4. The quality of answers depends on the model, not on Continue itself.
Privacy Considerations
For teams with sensitive codebases, Continue with local Ollama models means your code never leaves your machine. No cloud API calls, no training data concerns, no vendor access to your code. This is a meaningful advantage for regulated industries or proprietary codebases.
Copilot, even with content exclusions, still sends code to GitHub's servers. Continue with Ollama does not.
Pricing
Continue.dev itself is free and open source (Apache 2.0). What you pay:
Using Ollama (local models): $0
Using Anthropic Claude API: roughly $0 to $5/month at moderate development usage
Using OpenAI API: similar cost range
Using Mistral Codestral for autocomplete: Mistral has a free tier for Codestral specifically
Total realistic cost for a developer using Continue with a mix of local Ollama (autocomplete) and Claude API (chat): $1 to $3/month.
Who Should Use Continue.dev
Developers who want Copilot features without the subscription. If $10/month is a meaningful constraint (especially for hobbyist or open source projects), Continue.dev is the best free alternative.
Privacy-conscious teams and individuals. Local model support with Ollama provides genuine privacy guarantees that subscription tools cannot.
Developers who want to experiment with models. Continue makes it easy to try different LLMs and find the combination that works best for your specific workflow.
JetBrains users who don't want Copilot. The JetBrains plugin is a real option alongside Copilot for developers on IntelliJ, WebStorm, or PyCharm.
Who Should Stay on Copilot
Enterprise teams needing compliance. Continue.dev has no enterprise compliance story: no SOC 2, no audit logs, no IP indemnification. If those matter, Copilot Business or Enterprise is the right choice.
Developers who want the best possible autocomplete with no configuration. Copilot works out of the box with a well-tuned model. Continue requires setup and model selection. For developers who want zero configuration, the setup overhead is a real cost.
Pristren builds AI-powered software for teams. Zlyqor is our all-in-one workspace (chat, projects, time tracking, AI meeting summaries, and invoicing) in one tool. Try it free.
Frequently Asked Questions
What is Continue.dev?
Continue.dev is a free, open source IDE extension for VS Code and JetBrains that provides AI-powered autocomplete, chat, and codebase search. It connects to any LLM provider (Anthropic, OpenAI, Ollama, etc.) and has no proprietary model. You pay only for API usage.
How does Continue.dev work?
Continue.dev runs as a local client that sends code context to a configured LLM via API. It handles prompt construction, context window management, and response rendering. It also indexes your codebase for semantic search using embeddings.
What are the best practices for Continue.dev?
Use separate models for chat (powerful like Claude) and autocomplete (fast like Codestral). Index your codebase early for @codebase feature. Tune autocomplete debounce (100-300ms). Use @file and @docs for precise context. Experiment with different models to find what works best.
How much does Continue.dev cost?
Continue.dev itself is free. With local Ollama models, cost is $0. With cloud APIs, expect $0 to $5/month for moderate use. A typical setup using Ollama for autocomplete and Claude API for chat costs $1 to $3/month.
Is Continue.dev worth it in 2026?
Yes, if you want Copilot-like features without the $10/month subscription or need privacy with local models. It's not as polished as Copilot for general autocomplete but excels with your own codebase context. Setup requires some effort, but the flexibility and cost savings are significant.
How does Continue.dev compare to GitHub Copilot?
Continue.dev's autocomplete is competitive on your own codebase after indexing, but Copilot is better for general patterns and boilerplate. Continue's chat and @codebase features are excellent. Copilot has enterprise compliance (SOC 2, IP indemnification) that Continue lacks.
Can I use Continue.dev with local models?
Yes, Continue.dev supports Ollama for local models. You can run models like Codestral, DeepSeek Coder, or Llama 3 locally. This ensures your code never leaves your machine, providing full privacy.
