Cursor vs Windsurf
Both are AI-first VS Code forks with capable agents. The choice comes down to whether you want to hand the AI context or have it infer context for you.
Last checked . Jump to the same task in both tools
Short answer
Cursor if you want explicit control over what the AI looks at; Windsurf if you want it to keep up with you without being told. That is close to the whole comparison. Both are VS Code forks, both have competent multi-file agents, both run commands and iterate on tests. Cursor makes scoping a deliberate act through @ mentions, which is more typing and more predictability. Windsurf's Cascade (now Devin Local, after Cognition renamed Windsurf to Devin Desktop in June 2026) tracks your working session and follows the thread across files, which feels smoother right up until it looks at the wrong thing and you have less visibility into why.
Choose Cursor if
- You want to control exactly which files the agent reads, every time
- You value a large ecosystem: more worked examples, more shared rules files, more people who have hit your problem
- You are working across unfamiliar parts of a codebase where wrong context is expensive
- You want the most conservative, most reviewable agent behaviour of the two
Choose Windsurf if
- You want lower prompt overhead when iterating in an area you are already working in
- You find constant @ mentioning tedious and would rather the tool keep up
- You prefer a calmer, less cluttered agent interface
- You are doing sustained work in one part of the codebase rather than jumping around
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Cursor vs Windsurf, side by side
| Dimension | Cursor | Windsurf |
|---|---|---|
| Base editor | VS Code fork | VS Code fork |
| Context model | Explicit: @ mentions attach files and folders | Inferred: Cascade follows your working session |
| Predictability | High — you know what it read | Lower — inference is harder to audit |
| Prompt overhead | Higher: scope every request | Lower: it keeps up on its own |
| Multi-file agent | Agent mode, plans and verifies | Cascade, plans and verifies |
| Inline completion | Tab, strong | Supercomplete, strong |
| Project conventions | .cursor/rules | Windsurf rules |
| Ecosystem and examples | Much larger community | Smaller, fewer public examples |
| Pricing shape | Free tier, subscription, usage-based above | Free tier, subscription, credit-based agent use |
A check marks the tool with the clearer advantage on that row. Rows with no check are close enough that the difference is preference, not capability.
This is the closest comparison on the site, and anyone claiming a decisive winner is selling something. Both tools forked VS Code, both put an agent at the centre, both do multi-file edits and run your tests. Feature lists will not separate them.
The philosophical difference is real though, and it shows up in every prompt you write. Cursor asks you to declare context. Windsurf tries to work it out. Explicit scoping costs keystrokes and buys predictability. Inference saves keystrokes and costs you visibility into what the model actually read.
Which is better depends on how you work. Sustained sessions in one area favour inference. Jumping between unfamiliar modules favours explicit scoping, because a wrong guess about context is far more expensive than the @ mention that would have prevented it.
The same task, prompted for each tool
Feature tables describe a difference. These show it. Each pair below is the identical task written for Cursor and for Windsurf, and the gap between them is the gap between the two tools.
Build a dashboard UI
Build a dashboard page in this codebase using the existing component library and styling approach; check for Tailwind, CSS modules, or styled-components before writing anything. Lay out a header with a date range picker, four stat cards showing {{resource}} metrics with a delta versus the previous period, one line chart, and a recent activity table with client-side sorting. Fetch data through a single typed hook per widget so each region renders independently with its own skeleton state, an error state with a retry button, and an empty state with real copy rather than a blank div. Collapse the grid to one column below 768px. Do not add a charting library if one is already installed. When done, start the dev server, verify there are no console errors, and list the components you added.Build a dashboard UI in this project using {{language}} and the existing component conventions. Layout: a fixed sidebar with nav links, a top bar with a date-range picker, and a main grid of four stat cards above two charts and a recent-activity table. Fetch data through a single useDashboardData hook so widgets stay decoupled from the API layer. Every widget needs three states: skeleton while loading, an inline retry on fetch failure, and a zero-data message that tells the user what action creates data. The table should sort by column header and paginate client-side up to 500 rows. Keep the grid responsive: cards collapse to one column below 768px and charts stay legible at 320px wide. When done, run the dev server, confirm no console errors, and list the components you added with their file paths.Add JWT authentication
Add JWT authentication to the existing API in this repo. Create POST /auth/register and POST /auth/login endpoints that hash passwords with bcrypt or argon2, never plaintext, then issue a short-lived access token (15 minutes) and a refresh token (7 days) stored as an httpOnly, Secure, SameSite=Strict cookie. Add middleware that verifies the access token signature and expiry, attaches the user to the request, and returns 401 with a WWW-Authenticate header on failure rather than 500. Include POST /auth/refresh with refresh token rotation and a revocation check against {{database}}. Read the signing secret from an environment variable and fail fast at startup if it is missing. Cover expired tokens, tampered signatures, and reuse of a rotated refresh token in tests, run them, and list changed files.Add JWT authentication to this API. Endpoints: POST /auth/register hashing passwords with argon2 or bcrypt, POST /auth/login returning a short-lived access token plus an httpOnly refresh cookie, POST /auth/refresh rotating the refresh token, POST /auth/logout revoking it. Store refresh token hashes in {{database}} with a revoked flag; never store raw tokens. Sign with a secret read from env and fail startup loudly when it is missing. Middleware attaches req.user, returns 401 for expired tokens and 403 for valid but forbidden ones. Handle replayed refresh tokens, clock skew tolerance, and login rate limiting. Write integration tests covering the full register, login, refresh, logout cycle, run them in the Windsurf terminal, and show me the combined diff with the test output.Every task we have written for both
| Task | Cursor | Windsurf |
|---|---|---|
| Build a REST API | Prompt | Prompt |
| Build a SaaS starter app | Prompt | Prompt |
| Write unit tests | Prompt | Prompt |
| Refactor a large component | Prompt | Prompt |
| Add a search feature | Prompt | Prompt |
| Build a GraphQL API | Prompt | Prompt |
| Build a landing page | Prompt | Prompt |
| Build a to-do app | Prompt | Prompt |
| Write end-to-end tests | Prompt | Prompt |
| Migrate JavaScript to TypeScript | Prompt | Prompt |
| Integrate an LLM chatbot | Prompt | Prompt |
| Build a pricing page | Prompt | Prompt |
| Build a blog with a CMS | Prompt | Prompt |
| Add email notifications | Prompt | Prompt |
| Set up a Postgres database schema | Prompt | Prompt |
How prompting differs between them
In Cursor, the scoping is the prompt. A well-formed request names the files with @ mentions, states constraints that are invisible in the code, and ends with a verification step. Sixty to a hundred and sixty words is the sweet spot. Skip the scoping and quality drops immediately, because it will semantic-search and often pick the wrong module.
In Windsurf, you can lead with the task. Cascade already knows what you have been editing, so the first sentence can be the change itself. The discipline that pays off instead is stating the boundary: what should not change. Since you are not choosing the context, the way to keep it from wandering is to say where the edges are.
Both support rules files, and both benefit from them equally. Move any repeated instruction there.
What actually decides it
Try both for a week on real work — both have free tiers, and the switching cost between two VS Code forks is close to zero since your settings and extensions import either way. Pay attention to one thing: how often you find yourself surprised by what the AI read. If Windsurf's inference lands consistently on your codebase, it is the more pleasant tool. If it keeps pulling in the wrong module, Cursor's explicitness stops being tedious and starts being the point.
The ecosystem gap is real
Cursor has substantially more users, which shows up in ways that do not appear in a feature comparison: more public rules files to copy, more written-up workflows, more answers when something breaks, and faster third-party support. Windsurf is a good product with a smaller orbit. If you are the kind of person who solves problems by finding someone who already had them, that gap matters more than any individual feature.
Common questions
Is Windsurf better than Cursor?
Not measurably, and not for everyone. Windsurf's automatic context handling is genuinely more pleasant when it is right, and harder to correct when it is wrong. Cursor's explicit scoping is more work and more predictable. Both have free tiers; a week on real code will tell you more than any comparison will.
Can I switch between them easily?
Yes. Both are VS Code forks that import your settings, keybindings, and most extensions, so the switching cost is close to zero. What does not transfer is your rules file, which uses a different path and format in each — budget a few minutes to port it.
Do they use the same models?
Both offer a selection of frontier models and let you pick per request, so the underlying model is rarely what separates them. The difference is in how much of your codebase each one feeds the model, which is exactly the context question this comparison is about.
Which is better for large codebases?
Cursor, marginally, because explicit scoping matters more as a repo grows and inference has more ways to go wrong. If your codebase is large enough that this is a real concern, also look at Claude Code, which is built for repo-wide work.