Windsurf vs Cursor in 2026: Devin Desktop or Cursor, Which AI Code Editor to Choose?

Last updated: 13 November 2026

What happened to Windsurf?

Windsurf began as the AI editor from Codeium. In 2025, after a planned acquisition by OpenAI fell through and Google licensed technology and hired key staff, Cognition announced on 14 July 2025 that it would acquire Windsurf. On 2 June 2026, Cognition renamed the product Devin Desktop through an automatic update. Plans, settings, extensions and MCP connections carried over, and the old Windsurf website now points to Devin’s site. The Cascade agent that made Windsurf popular reached end of life on 1 July 2026 and was replaced by Devin Local.

People still search for “Windsurf vs Cursor”, so this comparison uses both names. In practice, you are now comparing Devin Desktop with Cursor.

Side-by-side comparison

Pricing compared

Both products restructured plans in 2026, and published figures vary by source, so treat these as approximate and confirm on each site. Devin Desktop has been reported with a free tier, a Pro plan around $20 a month, a higher Max tier, and team plans with a base fee plus per-seat pricing. Cursor has been reported with a free tier and several paid tiers, with access to third-party models on higher plans and some model usage billed at provider rates on top of the subscription, plus team plans priced per seat without a base fee.

The practical lesson: estimate a month of your real usage, including which models you use most, before comparing. A cheaper subscription can become more expensive if your preferred models are billed separately.

Agents compared in practice

Cursor’s Composer

Composer works inside the editor. You describe a change, it plans and edits across files, and you approve diffs before they apply. Developers like how tightly it fits into normal editing: you can switch between writing code yourself, using inline suggestions and handing larger edits to Composer without leaving the file you are in. Cloud Agents extend this by running tasks in isolated machines and returning pull requests, which suits backlog items you do not need to watch.

Devin Desktop’s Devin Local and Devin Cloud

Devin Local plays a similar role to Composer for interactive work in the editor, inheriting the “flow” style that made Cascade popular. The bigger strategic difference is Devin Cloud: Cognition’s product direction centres on asynchronous agents that take whole tasks, work independently and report back. Devin Desktop is increasingly the entry point into that ecosystem. If your team wants to delegate entire tickets to agents, this integration is a meaningful advantage.

Model access

Model choice matters because different models excel at different tasks. Some developers prefer Claude models for careful reasoning on large codebases, others prefer GPT or Gemini models for speed or specific languages, and each editor’s own models are tuned for in-editor work.

• Devin Desktop has been positioned around access to models from several major labs within a plan’s usage allowance, plus Cognition’s own coding models.
• Cursor emphasises its own Composer models, with third-party models available on higher tiers and some usage billed at provider rates.

If you rely heavily on one specific frontier model, check exactly how each plan includes and bills it.

Which should you choose?

How to run a fair two-week pilot

1. Pick five to eight developers with different experience levels.
2. Split them across both tools, or have each person use both on different tasks.
3. Use real backlog work: bugs, small features, tests and refactors.
4. Track metrics: time from ticket start to merged pull request, review comments per pull request, bugs found later, and model usage costs.
5. Collect qualitative feedback: what felt faster, what was frustrating, what they trusted.
6. Check admin needs: single sign-on, user management, billing, privacy settings and data terms.
7. Decide with data, not demos.

Strengths and weaknesses

Other AI coding tools to consider

Devin Desktop and Cursor are not the only choices. Depending on your workflow, these may fit better:

• GitHub Copilot: AI help and agents inside VS Code, JetBrains and GitHub, ideal for teams that want to keep their current setup.
• OpenAI Codex: a coding agent in the ChatGPT desktop app, terminal, IDE and cloud; see how to use OpenAI Codex.
• Claude Code: Anthropic’s agent for terminal and IDE work, valued for careful reasoning.
• Google Antigravity: Google’s agent-first platform with parallel agents; see how to use Google Antigravity.
• Replit Agent and v0: for building new apps from prompts rather than working in an existing codebase.

Our roundup of the best AI coding assistants compares them in more depth, and the best AI code review tools covers automated review.

Getting the most from any AI editor

• Write a project rules file describing conventions, test commands and boundaries, so agents behave consistently.
• Keep tasks small and reviewable, especially early on.
• Insist on tests for agent changes and run them yourself.
• Review every diff as you would a colleague’s pull request.
• Protect secrets and use privacy settings appropriate to your code.
• Measure outcomes rather than relying on how fast it feels.
• Revisit your choice yearly. This market changes quickly; the best tool this year may not be the best next year.

Security and privacy considerations

Both tools send code context to AI models to generate suggestions and edits. Before rolling out to a team, review the data terms, retention settings and any training opt-outs, enable privacy features, and confirm the setup meets client contracts and regulations. For sensitive or regulated code, consider enterprise plans with stronger controls, private deployment where available, or limiting AI use to specific repositories. Our AI data privacy guide and AI usage policy template cover the basics.

A short history of both editors

The history matters because it shows direction. Devin Desktop is increasingly a doorway into Cognition’s autonomous agent platform, while Cursor continues to focus on being the best place to write code with AI at your side.

Day-to-day experience

Beyond agents, much of a developer’s day involves small interactions: tab completions, quick inline edits, asking questions about a function, renaming across files. Cursor’s fast, context-aware tab completion has long been one of its most praised features, and many developers say it is what keeps them on Cursor even more than the agent. Devin Desktop inherits Windsurf’s smooth “flow” experience, where the agent tracks what you are doing and offers relevant help, and its IDE plugins let developers keep familiar editors. The best way to judge these small but important differences is to use each for a few days on real work, because they are hard to capture in a feature table.

Migrating between them

Because both are based on, or integrate with, the VS Code ecosystem, moving between them is relatively easy. Settings, keybindings and many extensions transfer, and your code lives in Git regardless of editor. The main migration work is rewriting project rules files for the new tool’s format, learning its agent workflow, and adjusting team billing and privacy settings. Plan a short overlap period where developers can use both while they adjust.

Use cases: which editor fits which job

What both get wrong sometimes

No AI editor is perfect. Common issues reported across both include agents making more changes than requested, confidently using outdated library APIs, weakening tests to make them pass, and losing track of context in very large repositories. The fixes are the same in both: clear rules files, small tasks, careful review, strong tests and a habit of asking the agent to explain its changes. Teams that adopt these habits get far more value than teams that simply switch tools hoping for better results.

Our verdict

For most individual developers and small teams who want the smoothest in-editor experience, Cursor remains an excellent default. For developers who want broad access to frontier models in one plan, prefer JetBrains or want to grow into autonomous agents that take whole tasks, Devin Desktop, the product formerly known as Windsurf, is a strong alternative. Both are mature, capable tools in 2026. The deciding factors are your editor preferences, model needs, team size and budget, so run a short pilot, measure real outcomes and choose the one your developers actually enjoy using.

Team rollout tips

Whichever editor you choose, a structured rollout avoids frustration. Start with a small group of enthusiastic developers who can create shared rules files and prompt examples. Hold a short internal session showing real before-and-after examples from your own codebase. Agree on review standards for agent-generated pull requests, such as requiring tests and a clear description of what the agent changed. Set spending alerts for model usage. After a month, gather feedback and adjust settings, rules and plans. Teams that treat AI editors as a process change, not just a software purchase, see the biggest gains.

Questions to ask before buying

• Which models will our developers actually use most, and how are they billed on each plan?
• Do we need single sign-on, user provisioning, audit logs or invoice billing?
• What are the data retention and training terms, and do they satisfy our clients’ contracts?
• Do we need private or on-premises deployment?
• Which editors does the team use today, and how disruptive is switching?
• How will we measure whether the tool improves delivery, not just how it feels?
• What is our plan if pricing or ownership changes again?

Getting written answers to these questions from both vendors, especially on billing and data, avoids unpleasant surprises after rollout.

Costs beyond the subscription

When comparing, include costs that do not appear on pricing pages: time spent reviewing agent output, onboarding and training, extra continuous integration minutes from agents opening more pull requests, and separately billed model usage. A tool that is slightly more expensive per seat can still be cheaper overall if its output needs less correction. That is why measuring review effort during your pilot is just as important as measuring speed.

For non-developers and agencies

Marketing agencies and small businesses sometimes ask whether they should buy an AI code editor for website work. If you have a developer, either editor will speed up tasks like theme changes, schema implementation, performance fixes and landing page builds. If you do not, simpler tools such as v0 or Replit Agent, or a managed website platform, are usually a better starting point. See how to use v0 and the best AI website builders.

Frequently overlooked differences

Feature tables rarely capture the details that shape daily experience. A few differences worth testing during a pilot:

• Indexing large repositories. How quickly each editor indexes a big monorepo, and how well its agent finds relevant files without being told, can vary noticeably by project.
• Handling of rules files. Both support project-level instructions, but they differ in format and how strictly agents follow them. Port your conventions carefully and check whether agents respect them.
• Terminal and test integration. Watch how each agent runs tests, reads failures and iterates. An agent that runs the right tests automatically saves a lot of time.
• Diff review experience. Some developers prefer reviewing many small diffs, others one larger change. Notice which tool’s review flow fits your team.
• Offline and network restrictions. In companies with strict networks or proxies, check that each tool works reliably behind your firewall.
• Extension compatibility. Confirm the extensions your team relies on, such as language servers, linters and debuggers, work smoothly.
• Support and roadmap. Given how quickly this market changes, look at how often each product ships updates and how responsive support is for business customers.

Writing down observations on these points during the pilot gives you a far more reliable basis for the decision than first impressions or benchmark scores published by vendors.

Bottom line for busy readers

If you want the short version: try Cursor first if editor polish and team price matter most, and try Devin Desktop first if you want broad frontier model access, JetBrains support or a path to autonomous cloud agents. Give each a fair trial on real work, measure time to merge and review effort, check data terms, and let your developers’ experience decide. Both are strong tools in 2026, and the habits you build around them matter more than the logo on the window.

Frequently asked questions