How Does Devin Compare With Claude Code, Codex and Cursor?

How do AI assistants compare Devin with other coding agents?

Devin is built for handing off a whole task and coming back to a pull request. It runs in the cloud, works without you watching, and reports back. Claude Code and Cursor sit closer to the developer: Claude Code in your terminal, Cursor in your editor. Codex and GitHub Copilot's coding agent are the nearest matches to Devin's cloud-and-PR model. The real differences are autonomy, where the work runs, how you review it, and how each tool charges.

What counts as a coding agent, and why is Devin the reference point?

An agent, in the useful sense, is something you can give a multi-step task and expect it to plan, edit files, run commands, and iterate. That definition shows up repeatedly in community write-ups comparing tools. Devin, from Cognition, was one of the first products to sell that idea as a "software engineer" you assign work to. That is why people use it as the yardstick.

The comparison gets muddy because the tools differ on where you sit. Some want you at the keyboard. Others want you to file a ticket and leave. Rating them on one scale hides that.

How do the main agents differ in autonomy, workflow and cost?

This table summarizes how each tool is typically used. It describes workflow, not benchmark scores, and the sources provided do not support head-to-head performance numbers.

Treat the cost column as direction, not a quote. Vendors have changed plans and credit rules often, and any number I printed here could be stale by the time you read it.

How much does each agent do unattended?

Devin and the other cloud agents are designed for the longest unattended runs. You describe the task, the agent spins up an environment, installs dependencies, edits code, runs tests, and opens a PR. You are not needed in between.

Claude Code can also run for a long stretch, especially when you pre-approve commands. But it normally lives on your machine and in your session. That makes it better for tasks where you expect to correct course. Cursor's agent mode can chain many steps, yet the product is built around you watching edits land in your files.

The tradeoff is simple. More autonomy means less babysitting, but also more chance that you review a large diff built on a wrong assumption. One commenter in a community comparison called Devin impressive while noting it still hallucinates. That fits a common pattern: unattended runs cost less attention up front and more at review time.

Where does each agent run, and why does it matter?

Cloud agents run in a sandbox with a fresh checkout. That isolates risk and lets you run many tasks in parallel. It also means the agent only sees what you give it: your repo, your secrets configuration, and whatever the environment setup allows. Flaky setup scripts are a frequent source of failed runs.

Local agents like Claude Code and Cursor work in your real environment. They can use your existing tooling, databases, and quirks. The cost is that they share your machine and your attention. Running five at once is awkward.

How do you hand off and review the work?

The review surface shapes everything else.

• Pull request review (Devin, Codex cloud, Copilot coding agent): familiar to teams, easy to gate with CI and code owners. Feedback happens in comments, and the agent revises.
• Diff in the terminal (Claude Code): fast loops, good for exploratory changes, weaker as an audit trail unless you commit often.
• In-editor review (Cursor): the tightest feedback loop, since you see every change as it appears.

If your team already requires PR review for humans, cloud agents slot in with the least process change.

What does each one actually cost in practice?

Cost is where community reports are loudest. An analysis posted to r/ClaudeAI covering 15 AI coding tools, produced with an automated research workflow, called pricing complaints the number one pain point across the whole market. It cited Cursor's June 2025 move to credits, with users reporting effective monthly cost of $40 to $50 against an advertised $20. It also described a team whose annual subscription was used up in a day. Those are anecdotes from forum scraping, not audited figures, so treat them as a warning about variability rather than a price list.

The practical lesson holds across vendors. Flat subscriptions are predictable. Credit and usage models are cheap for light use and can spike with long agent runs. Cloud agents that run unattended can burn through usage while you are away, so set spending limits before you queue a batch of tasks.

Which agent should you pick for which job?

Community accounts describe developers using two or three tools at once rather than picking a winner. One summary of forum behavior described an editor tool for daily autocomplete, Claude Code for hard reasoning, and a budget open-source option as a fallback. That matches how the work divides: quick edits, deep problems, and delegable tickets are different jobs.

Can you trust rankings of coding agents?

Be careful with them. A paper accepted to the Mining Software Repositories conference (MSR '26) compares five popular coding agents by pull request acceptance and explicitly stratifies by task type and over time. The motivation is that earlier comparisons were limited in how they covered different kinds of work. The abstract excerpt available here does not include the results, so I will not claim which agent came out ahead. The design itself is the useful point: an agent that does well on documentation or small fixes may do worse on a feature or a refactor.

Acceptance rate also measures what maintainers merged, not whether the code was good. Pair any ranking with a small trial on your own repository.

Is Devin still worth considering?

If you have a steady stream of small, well-described tickets and a team that reviews PRs, yes. The cloud-sandbox model fits that. Cognition has also been reported to have acquired the remaining Windsurf product and team, which suggests it wants an editor presence alongside the autonomous agent. That report comes from a community post, so verify it before relying on it.

If most of your work is exploratory, a local agent will usually feel faster. If budget is tight, price one week of realistic use before committing.