| Feature | Cursor | Dify |
|---|---|---|
| Free Plan | ✓ Yes | ✓ Yes |
| Pricing | Free / $20/mo | Free / $59/mo |
| Rating | ★★★★★ 4.8 | ★★★★★ 4.6 |
| Key Feature 1 | Tab Autocomplete | Visual workflow builder |
| Key Feature 2 | Composer | RAG pipeline |
| Key Feature 3 | Chat Sidebar | Multi-model support |
Reach buyers comparing Cursor and Dify. High-intent traffic, direct conversions.
Cursor edges out Dify on user ratings (4.8 vs 4.6 out of 5), though both remain solid choices depending on your priorities. Both Cursor and Dify offer free plans, so you can test both before committing. Cursor tends to be favoured by freelancers, while Dify is more popular with agencies.
Put Cursor next to Dify and the differences surface fast — both sit in the coding tools space, but they solve the problem from different angles. Cursor is best known for tab autocomplete, whereas Dify stands out for visual workflow builder. On aggregate user ratings Cursor holds a slight edge (4.8/5 vs 4.6/5), though that gap rarely decides the match on its own.
Where Cursor pulls clearly ahead is refactoring large codebases across multiple files with Composer mode. A frequent plus in reviews: Sets the benchmark in its category for Tab Autocomplete quality and reliability. Dify, by contrast, is the stronger choice for building a customer-facing chatbot with RAG over your own documentation. In its favour: Open-source codebase — self-host for full data control, audit the code, or contribute to the community. The feature checklists overlap, but the day-to-day experience does not.
Cursor is the best AI coding tool for individual developers who want maximum capability. Dify is the strongest open-source option for teams building production LLM applications who need more control than no-code tools but less overhead than building from scratch. If you only have budget or appetite for one, match the tool to your heaviest workflow rather than the spec sheet.
Choose Cursor if you are focused on individual developers and small engineering teams who want the most capable AI coding experience available — specifically those doing complex multi-file refactoring, codebase exploration, and AI-assisted debugging rather than just inline autocomplete, or if a big part of your week goes to asking questions about an unfamiliar codebase ('How does auth work in this repo?'). Its free tier also lets you validate the fit before paying.
Choose Dify if your priority is developers and technical teams who want to build and deploy LLM-powered applications — chatbots, RAG pipelines, AI agents, and internal tools — without writing backend AI infrastructure from scratch, especially for creating internal AI tools that query your company knowledge base. A free plan is available, so you can trial the workflow at zero cost first.
Real-world output tracks the ratings closely: Cursor at 4.8/5 and Dify at 4.6/5, with the difference showing up most in refactoring large codebases across multiple files with Composer mode.
Learning curve is worth weighing. Cursor has a known trade-off — Sends code to AI servers — worth evaluating before committing if this is central to your use case. On Dify's side: Steeper learning curve than no-code tools. Budget a week or two to get fluent in either before judging the output.
Both tools offer a free plan, so you can trial each side by side before spending anything. Paid plans start at $20/mo for Cursor (Pro) and $59/mo for Dify (Professional (Cloud)), making Cursor the cheaper entry point at $20/mo versus $59/mo. The extra spend on Dify only pays off if you need what its higher tier unlocks. Watch for usage caps and per-seat costs at the tier you'll really land on, not the headline price.
🚀 Ready to decide? Try both free and see which fits your workflow.
Cursor is a fork of VS Code with deep AI integration — write, edit, debug, and refactor code using natural language with full understanding … Read the full Cursor review →
Dify is an open-source platform for building production-ready AI applications and agents without deep engineering expertise. Its visual work… Read the full Dify review →
• Sets the benchmark in its category for Tab Autocomplete quality and reliability
• Full codebase context awareness — especially for tab autocomplete workflows where Cursor consistently outperforms manual approaches
• Works with Claude, GPT-4, Gemini
• VS Code extension compatibility — especially for tab autocomplete workflows where Cursor consistently outperforms manual approaches
• Sends code to AI servers — worth evaluating before committing if this is central to your use case
• Overkill for simple scripts — worth evaluating before committing if this is central to your use case
• Open-source codebase — self-host for full data control, audit the code, or contribute to the community
• Supports all major AI models
• Visual builder, no deep coding needed
• Strong RAG and agent capabilities
• Steeper learning curve than no-code tools
• Self-hosting requires server setup — worth evaluating before committing if this is central to your use case