Continue
0 comparisons available
About Continue
Continue is an open-source AI coding assistant for VS Code and JetBrains IDEs, founded in 2023 by Nate Sesti and Ty Dunn, designed to give developers full control over their AI coding workflow by connecting to any LLM — local models via Ollama, cloud models (Claude, GPT-4o, Gemini), or self-hosted endpoints. Continue's open-source nature (Apache 2.0) is its primary differentiator: developers can inspect, modify, and extend the assistant, configure any model, and run entirely locally without sending code to external services. Continue's context providers are its most powerful feature — @file, @codebase (semantic search), @terminal (last command output), @diff (git changes), @web (search results), @docs (indexed documentation) allow assembling rich, precise context for each AI request. Continue's config.json defines models, context providers, slash commands, and prompt templates in a single file, enabling full customization. Continue Autocomplete uses local models (via Ollama) for zero-latency, zero-cost tab completions. Continue supports multi-model configurations — use Claude 3.7 Sonnet for complex tasks and a local Llama 3 for quick completions in the same session. Continue's growing integration with LlamaIndex and custom RAG pipelines enables enterprise teams to build custom context retrieval over internal documentation and codebases. Continue reached 800,000+ VS Code installs and 20,000+ GitHub stars by 2025. It is the preferred AI coding tool for privacy-conscious developers, teams running air-gapped environments, and engineers who want full visibility into their AI toolchain.
Frequently Asked Questions
Can Continue run entirely locally without internet?
Yes — Configure Continue with Ollama as the model provider and local models (Llama 3, DeepSeek Coder, Qwen2.5-Coder), and both chat and autocomplete run entirely on your machine. The @codebase context provider uses local embeddings. No code, prompts, or completions leave your environment. This makes Continue the leading choice for air-gapped development environments and organizations with strict data policies.
Is Continue as good as GitHub Copilot?
Continue with frontier cloud models (Claude 3.7 Sonnet, GPT-4o) matches or exceeds Copilot's raw suggestion quality. Continue's @codebase semantic search and rich context providers often produce more relevant responses than Copilot Chat for complex questions. Continue's autocomplete quality with local models (Ollama) is below Copilot with cloud models. The tradeoff: Continue's flexibility and open-source nature vs Copilot's polished managed experience and GitHub integration.
How do I add custom documentation to Continue?
Continue's @docs context provider indexes third-party documentation sites (crawled and embedded locally) so you can ask questions about frameworks like LangChain, React, or your internal APIs. Add a docs entry to config.json with the documentation URL and Continue crawls, chunks, and embeds it using a local or cloud embedding model. Combined with @codebase, this enables Claude/GPT-4o to answer questions grounded in both your code and relevant documentation.
Top Alternatives to Continue
Cursor
AI-first IDE with deeper built-in context — Cursor for productivity; Continue for open-source control
GitHub Copilot
Managed AI assistant — stronger GitHub integration; Continue for self-hosted privacy and model choice
Codeium
Free managed AI extension — Codeium for easy setup; Continue for any-LLM flexibility and open source
Tabnine
Enterprise privacy-first AI — Tabnine has local model; Continue offers broader LLM choice and open source
Ollama
Local LLM runner — Continue uses Ollama as its backend for local model inference
Aider
Terminal-based AI coding assistant — Aider for git-integrated CLI workflow; Continue for IDE integration
No comparisons found for Continue yet.
Search for a comparison