by Continue · Open-Source AI Code Assistant for VS Code & JetBrains
Continue.dev is the leading open-source AI coding assistant, letting you plug in any LLM — Claude, GPT-4, Gemini, local Ollama models, or your own API — directly into VS Code or JetBrains. No vendor lock-in, full customization, optional self-hosting.
Free & Open SourceVS Code + JetBrainsSelf-Host Option
4.5
★★★★½
TechVernia Score
Based on in-depth testing
Free
Core Extension
Any LLM
Model Flexibility
VS Code + JB
IDEs Supported
18k+
GitHub Stars
Apache 2.0
License
Continue.dev Overview
The open-source alternative: Continue.dev gives developers the power of AI coding assistance without locking them into a single model or vendor. You choose the model, you control the data, and you can self-host the entire stack. It is the preferred choice for privacy-conscious teams, enterprises with air-gapped environments, and developers who want to use local models via Ollama or LM Studio.
Continue was founded in 2023 and quickly became the de facto open-source alternative to GitHub Copilot. The VS Code extension surpassed 18,000 GitHub stars within its first year, driven by its flexible model support and powerful codebase context features.
Unlike closed tools, Continue.dev allows you to configure which LLM powers each feature: you might use Claude 3.5 Sonnet for complex reasoning tasks, GPT-4o Mini for quick autocomplete (lower latency), and a local Ollama model for sensitive code that shouldn't leave your machine.
2025–2026: Continue.dev introduced an "Agent Mode" for multi-step autonomous task execution, a "Hub" for sharing custom configurations across teams, and first-class support for Claude 3.7 Sonnet's extended thinking mode — allowing it to tackle complex architectural problems that shorter context windows couldn't handle.
Supported Models (2026)
One of Continue.dev's core strengths is model flexibility. You can mix and match models for different tasks:
Claude 3.7 Sonnet
Best for complex reasoning, architecture, and long-context codebase analysis
GPT-4o / Mini
Reliable general-purpose coding. Mini offers lower latency for autocomplete
Gemini 2.0 Flash
Excellent for large file context — 1M token window for massive codebases
Ollama (Local)
Llama, Mistral, CodeLlama — runs 100% locally. No data leaves your machine
DeepSeek Coder
Excellent coding-specific model with a generous free API tier
Custom API
Any OpenAI-compatible endpoint. Bring your own fine-tuned model or proxy
Key Features
Chat Sidebar
Ask questions about your codebase, debug errors, explain functions, and get implementation suggestions — all within your IDE sidebar.
Inline Autocomplete
Tab-to-accept code completion as you type. Configure which model powers autocomplete separately from chat for optimal latency.
Codebase Context (@codebase)
Use @codebase to give the AI full context of your project. Continue indexes your repo and retrieves relevant files automatically.
@ Mentions
Reference specific files (@file), functions, docs (@docs), GitHub issues, or web URLs directly in chat for precise context injection.
Agent Mode
Give Continue a multi-step task and watch it execute: edit files, run terminal commands, read test output, and iterate autonomously.
Local Model Support
Full Ollama and LM Studio integration. Run Llama 3, Mistral, or DeepSeek Coder locally — zero data sent to external servers.
Custom Prompts / Slash Commands
Define your own /commands with custom system prompts. Teams can standardize on company-specific coding styles and workflows.
JetBrains Support
Full plugin for all JetBrains IDEs: IntelliJ IDEA, PyCharm, WebStorm, GoLand, Rider — not just VS Code.
Pros & Cons
Pros
Completely free and open-source (Apache 2.0 license)
Use any LLM — no vendor lock-in to OpenAI or GitHub
Local model support for air-gapped or privacy-sensitive environments
Works in both VS Code and all major JetBrains IDEs
@codebase indexing for intelligent, relevant context retrieval
Note: You still pay for the LLM API you choose. Using Claude 3.7 Sonnet via Anthropic API costs ~$3/MTok input + $15/MTok output. Using Ollama locally is completely free. Most individual developers spend $5–30/month on API costs depending on usage.
Continue.dev vs Competitors
Feature
Continue.dev
GitHub Copilot
Cursor
Codeium
Open source
Apache 2.0
Any LLM support
Full flexibility
GPT-4 only
Multiple
Codeium model
Local model (Ollama)
JetBrains support
Full
VS Code only
Free plan
Fully featured
$10/mo min
Limited
Limited
Autocomplete quality
Depends on model
Excellent
Excellent
Good
Final Verdict — Is Continue.dev Worth It?
Continue.dev is the best choice for developers who want full control over their AI coding stack. It is free, open-source, works with any LLM, and supports both VS Code and JetBrains — a combination no paid tool matches. For teams with privacy requirements, the ability to use local models is invaluable.
The trade-off: you need to manage your own API keys and configuration. This is trivial for experienced developers but can be a barrier for beginners who prefer the plug-and-play simplicity of GitHub Copilot.
Recommended for: Developers who want LLM flexibility, teams with privacy/security requirements, open-source enthusiasts, JetBrains users, developers who want to use local models (Ollama), and anyone who wants a free alternative to GitHub Copilot.
Not recommended for: Developers who want zero configuration and instant setup. In that case, GitHub Copilot or Cursor is easier to get started with.
Frequently Asked Questions
Yes. The VS Code extension and JetBrains plugin are completely free and open-source (Apache 2.0). You do need to provide your own LLM API key (Claude, OpenAI, etc.) or use a local model via Ollama. The Teams Hub plan adds managed configuration features for $20/user/month but is optional.
Yes — this is one of Continue.dev's strongest features. You can connect to Ollama, LM Studio, or any OpenAI-compatible local server. Local models like Llama 3.1 or DeepSeek Coder run 100% on your machine with no data sent externally — ideal for sensitive codebases.
With a strong model (Claude 3.7 Sonnet or GPT-4o), Continue.dev's autocomplete quality is comparable to GitHub Copilot. With smaller/local models, quality decreases. GitHub Copilot has an edge in raw autocomplete speed due to its dedicated fine-tuned model, but Continue.dev's flexibility in choosing the model offsets this for most use cases.
Yes, when configured with a local model via Ollama or LM Studio. The extension itself doesn't require internet; only the LLM API calls do. Air-gapped enterprise environments can run Continue.dev entirely offline with locally-hosted models.
It depends on which model you use. If you use the OpenAI or Anthropic API, your code snippets are sent to their servers (subject to their privacy policies). With local Ollama models, no code ever leaves your machine. Enterprise plans can deploy Continue Hub on-premise for full data control.
