Refact.ai is an open-source AI coding agent developed by Small Magellanic Cloud AI Ltd. It provides autonomous code editing, in-IDE chat, and real-time autocompletion via VS Code and JetBrains extensions, with optional self-hosted deployment on your own infrastructure. As a Cursor alternative, it targets developers and teams who need data privacy, self-hosting control, or local model support.
Refact.ai is an open-source AI coding agent developed by Small Magellanic Cloud AI Ltd. It provides autonomous code editing, in-IDE chat, and real-time autocompletion via VS Code and JetBrains extensions, with optional self-hosted deployment on your own infrastructure. As a Cursor alternative, it targets developers and teams who need data privacy, self-hosting control, or local model support — use cases Cursor does not address.
| Refact.ai | Cursor | |
|---|---|---|
| Type | VS Code + JetBrains extension + self-hosted CLI agent | Standalone IDE (VS Code fork) |
| Pricing | Free tier; Pro $10/month; Enterprise: custom self-hosted | Free / $20 / $40 per month |
| LLM choice | Multiple (OpenAI, Anthropic, local models via Ollama); fine-tune on your codebase | Built-in models + own key |
| Offline / local models | Yes — Ollama, Qwen2.5-Coder, custom fine-tunes | No |
| Open source | Yes — Apache 2.0 (client and server) | No |
| Codebase indexing | Yes — RAG-based vector database, per-project | Yes (automatic) |
| Multi-file edits | Yes — autonomous agent mode | Yes |
| Self-hosting | Yes — on-premise deployment available | No |
Refact.ai is the right Cursor alternative for developers and teams who need on-premise data control, local model execution, or open-source transparency. It fits regulated industries (finance, healthcare, defense) where cloud-based AI coding tools fail compliance requirements, solo developers running local Ollama-based setups, and engineering teams that want to fine-tune a model on their own codebase. If data privacy is a non-negotiable requirement and Cursor's cloud-only model is disqualifying, Refact.ai is the strongest open-source alternative.
Prices are subject to change. Check the official pricing page for current details.
Cursor is a polished IDE with deep AI integration, but it requires all code to pass through Cursor's cloud infrastructure — there is no on-premise option. Refact.ai fills the self-hosting gap: same autonomous agent capabilities (multi-file edits, codebase context, step-by-step execution), with the option to run everything locally. Cursor's Pro plan is $20/month with fixed request limits; Refact.ai's Pro is $10/month with a coin system, which is cheaper for moderate usage but less predictable at scale. Cursor has better UI polish and a larger ecosystem; Refact.ai has open-source transparency and local model support. Teams choosing between them are essentially choosing between convenience (Cursor) and data control (Refact.ai).
Refact.ai is the leading open-source Cursor alternative for developers who need data sovereignty, on-premise deployment, or local model execution. At $10/month Pro or free for light usage, it competes directly with Cursor on autonomous coding capabilities while offering what Cursor cannot: a self-hosted, fully open-source option that never sends code to a third-party cloud.
Yes. Refact.ai has a free tier that includes 2,000 coins per month for AI Agent and chat use, plus unlimited fast code autocompletions powered by Qwen2.5-Coder. The Pro plan costs $10/month and adds 10,000 coins and thinking model access.
Yes. Refact.ai has a native VS Code extension available in the VS Code Marketplace. It also supports JetBrains IDEs including IntelliJ IDEA, PyCharm, WebStorm, and GoLand.
Both offer multi-file AI editing and autonomous agents, but Cursor is a standalone IDE (VS Code fork) without self-hosting, while Refact.ai is a VS Code/JetBrains extension with an optional self-hosted server. Refact.ai is open-source and supports local models; Cursor routes all requests through its cloud infrastructure. Cursor is more polished; Refact.ai gives more data control.
Yes. Refact.ai supports Ollama-compatible local models and runs entirely on-premise when self-hosted. You can use Qwen2.5-Coder locally for autocompletions with zero network calls. The self-hosted server also supports custom fine-tuned models trained on your own codebase.
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