Refact.ai positions itself as an end-to-end engineering agent that goes far beyond code completion. The platform plans multi-step tasks, connects to GitHub, GitLab, Docker, PostgreSQL, and MySQL, searches and analyzes repositories, and iterates until tasks reach successful completion. Its number one ranking on SWE-bench Verified among open-source agents validates the effectiveness of this autonomous approach for real-world software engineering problems.
Continue takes a deliberately minimal approach as a VS Code and JetBrains extension that acts as a bridge between developers and their preferred LLM providers. It supports inline code completion via Tab autocomplete, chat-based assistance for explaining and refactoring code, and context injection from files, terminal output, documentation, and codebase search. The philosophy is to provide a clean interface layer rather than an autonomous agent.
Self-hosted deployment is where Refact.ai creates the strongest separation from competitors. Organizations can run the entire AI coding infrastructure on their own NVIDIA GPUs using Docker, ensuring source code never leaves company servers. This addresses the fundamental trust barrier that prevents many enterprises from adopting cloud-based AI coding tools, particularly in regulated industries like finance, healthcare, and defense.
Continue's model flexibility is its core strength. The extension works with virtually any LLM provider through a unified configuration, including OpenAI, Anthropic, Google, Mistral, Ollama for local models, and any OpenAI-compatible API endpoint. Users can configure different models for different functions, using a fast small model for completions and a larger model for complex chat interactions, optimizing both speed and cost.
The code completion experience differs in approach. Refact.ai uses a fine-tuned Qwen2.5-Coder model powered by RAG that indexes the entire codebase for context-aware suggestions reflecting project-specific patterns. Continue offers Tab autocomplete that works with any configured model, relying on the model's own capabilities supplemented by context from the current file, open tabs, and manually added documentation.
Agent capabilities represent the starkest contrast. Refact.ai's agent connects to development tools and databases, executes shell commands, browses the web, and maintains a growing knowledge base that improves with each interaction. Continue provides no autonomous agent functionality, instead offering manual code actions like explain, refactor, and generate tests that execute in a single turn without multi-step planning.
Enterprise features and pricing models diverge significantly. Refact.ai offers tiered pricing from a free tier with 5,000 coins through Pro and Enterprise plans that include on-premise deployment, custom model fine-tuning on organizational codebases, and dedicated engineering support. Continue is entirely free and open-source under Apache 2.0, with optional Continue for Teams offering centralized configuration management.