Codex vs Cursor: Which AI Coding Tool to Pick for Your Team

Pick Codex if your team wants to hand whole tasks to an agent and review the pull request afterward. It comes bundled with ChatGPT plans, so a five-person team on ChatGPT Business pays $100 to $125 a month before any extra credits. Pick Cursor if your developers spend the day inside an editor and want completions, inline edits and a choice of Claude, GPT and Gemini models in one window, and accept that those outside models are billed on top of the seat.

For most small product teams I would start with Codex. The seat price is lower, code review in GitHub is included on paid plans, and the bill is easier to predict. Cursor is the better pick for a team of strong engineers who want their hands on every change as it happens.

Both products changed a lot this year. Cursor has been part of SpaceX since August 14, 2026, its plans were renamed, and its included usage now covers only its own models. Codex now runs on the GPT-6 family and is folded further into the ChatGPT apps. Everything below reflects the vendors' own pricing and docs pages as of November 11, 2026.

The two tools started from opposite ends and have been growing toward each other. Each is still strongest where it began.

Codex

Codex is OpenAI's coding agent. You give it a task in plain language, it reads the repository, edits files, runs commands and tests, and reports back. It shows up in four places: the Codex CLI in your terminal, the Codex IDE extension, Codex Cloud for tasks that run on OpenAI's machines, and the ChatGPT desktop, web and mobile apps. OpenAI's docs also list integrations for GitHub, Slack and Linear, with GitLab in beta.

You do not buy Codex on its own. It is included with ChatGPT plans, with limited access on Free and Go and fuller access from Plus upward. You can also run the CLI, the SDK and the IDE extension on an API key and pay per token, though that route leaves out the cloud features.

Cursor

Cursor is a code editor built on VS Code with AI in every part of it: tab completion, inline edits, an agent panel, and Cloud Agents that run in isolated virtual machines. Cloud Agents were called Background Agents until this year. You can start one from the editor, from cursor.com/agents, from the iOS app, from Slack or Linear, or by mentioning Cursor on a GitHub or Bitbucket pull request. Cursor also has a CLI, a code review bot called Bugbot, and since October 20 an Agent SDK.

The ownership change matters for how it is sold. Cursor's subscription is now a bundle with Grok, and the weekly usage pool on each plan is shared across Cursor and the Grok apps. Cursor's own models are Composer 2.5 and the Grok line, which the docs describe as jointly trained by Cursor and SpaceXAI. Grok 4.7 was introduced on September 21.

Cursor is an editor you drive. Codex is an agent you delegate to. You can do both jobs in either, but the defaults pull you one way.

In Cursor, the developer stays in the file. You type, the editor predicts the next edit, you accept or reject it. You highlight a function and ask for a change. When you hand something bigger to the agent, you watch the diff build up and step in when it drifts. The feedback loop is seconds long.

In Codex, the unit of work is a task. You write two or three sentences, such as "add rate limiting to the invite endpoint and cover it with tests", and go do something else. Locally, the CLI works inside a sandbox on your machine. In Codex Cloud, each task gets its own workspace and keeps running while your laptop is closed. You come back to a set of changed files and decide whether to commit or open a pull request. The loop is minutes long, and you can have several running at once.

A Cursor team writes code with help. A Codex team writes task descriptions and reviews pull requests. The second style pays off when your tasks are well specified and your tests are good. It goes badly when the spec lives in one person's head, because the agent will build exactly what you wrote down.

Seniority matters here too. Junior developers tend to do better in Cursor, since they see every change as it lands. Delegating to an agent takes the judgment to spot a plausible but wrong pull request. If you are weighing a third option, our comparison of Cursor, Windsurf and Claude Code covers the editor side in more depth.

These are list prices from each vendor's pricing page on November 11, 2026, before tax. Both change often.

Codex plans

• ChatGPT Plus: $20 a month for one person. Includes Codex on the web, in the CLI, in the IDE extension and on iOS, plus automatic code review and the Slack integration.
• ChatGPT Pro: tiers at $100, $200 or $500 a month, with no five-hour limit at the moment.
• ChatGPT Business: $20 per user a month billed annually, or $25 billed monthly, with a two-seat minimum. Adds a shared workspace, admin controls, SAML SSO and MFA.
• Enterprise and Edu: through sales.
• API key: pay per token at API rates, CLI, SDK and IDE extension only.

Usage on Plus and standard Business seats is metered in five-hour windows, and weekly limits can apply as well. OpenAI publishes estimates instead of fixed caps, and they vary by model. For GPT-6.1 Sol the range is 15 to 160 local messages per window, and for the small GPT-6 Luna model it is 350 to 3,000. Cloud tasks draw from the same allowance and use more of it. When you run out, Plus and Pro users can buy credits, and Business workspaces on flexible pricing can buy workspace credits.

Cursor plans

• Plus: $8 a month. Cursor's own models only. No Cloud Agents, no Bugbot, no third-party models.
• Premium: $30 a month, with four times the Plus usage, Cloud Agents and third-party models.
• Super: $100 a month, 15 times the Plus usage.
• Ultra: $200 a month, 50 times the Plus usage.
• Teams: per seat at the Premium, Super or Ultra price, and one team can mix tiers. Adds central billing, usage analytics and SAML or OIDC SSO.

The part to read twice is what the seat covers. Each paid plan includes a usage pool that refreshes weekly, and that pool only pays for Cursor's own models. Claude, GPT and Gemini are billed at the provider's API list price from the first request, out of prepaid credit. On Teams and Enterprise, Cursor adds its own rate of $0.25 per million tokens on eligible third-party requests. Admins can set a monthly cap on that extra spend. Teams that signed up before the new subscription can stay on their older plans, which work differently.

The math for five developers

On Codex, five ChatGPT Business seats cost $100 a month on annual billing or $125 month to month. If two of your five are heavy users who keep hitting limits, the simple fix is workspace credits. Some teams instead put those two on a personal Pro plan at $100 or $200 each, which lands the team between $275 and $475 a month, though a personal plan sits outside your workspace controls.

On Cursor, five Premium seats cost $150 a month. Two Super seats and three Premium seats cost $290. Five Super seats cost $500. If your developers stay on Grok and Composer, that is the whole bill. If they pick Claude or GPT for agent work, add third-party usage on top. My own estimate for that is $20 to $150 per developer a month depending on how much they delegate, so a realistic Cursor range for this team is $150 to about $1,000. Set the monthly limit on day one.

The old advice was that Cursor gave you every model and Codex locked you to one vendor. That is only half true now.

Codex runs OpenAI models. The current list in its docs is GPT-6 Astra for the hardest work, GPT-6.1 Sol as the cheaper near-equivalent for long runs, GPT-6.1 Terra for fast work that involves reading screens and using apps, and GPT-6 Luna for high-volume simple tasks. Terra arrived in Codex on October 26. If you do not choose, the client picks a recommended model for you. The CLI has built-in provider setups for Amazon Bedrock and Google Cloud Vertex AI and accepts a custom provider that speaks the Responses API, which helps with procurement. In practice you are still running OpenAI's models.

Cursor still lists a long catalog: Anthropic, OpenAI, Google, DeepSeek, Moonshot, Meta and others. Two details change the picture. First, only Cursor's own models are covered by your seat, so the price nudges every developer toward Grok and Composer. Second, the catalog does not always carry a rival's newest release. When I checked Cursor's model page for this post, the OpenAI entries stopped at the GPT-5.6 family and did not include the GPT-6 models that Codex runs.

So ask which lock-in you can live with. With Codex you are tied to OpenAI's models and can leave by changing tools, since your code and your Git history stay yours. With Cursor you keep a choice of models but pay extra to use it, and your editor, rules files and review bot all sit with one vendor. Neither traps your code. If your team already prefers Anthropic's models, read our Codex vs Claude Code comparison before deciding.

Codex reviews in four places. Type /review in the CLI, the IDE extension or the desktop app to check uncommitted changes or a branch against its base. In GitHub, comment @codex review on a pull request, or turn on automatic reviews so every new pull request gets one. GitHub review is generally available and GitLab merge request support is in preview. Automatic review is listed as part of Plus and above, so a Business team gets it without a separate bill. It is not available when you run Codex on an API key.

Cursor's reviewer is Bugbot. It runs on new pull requests in the background, comments on likely bugs, offers a fix you can open in the editor or hand to a Cloud Agent, and follows custom Bugbot Rules. There is no separate Bugbot subscription. Reviews are billed from usage, and the $8 Plus plan does not include it.

For background work the two are close. Codex Cloud gives each task its own workspace built from an environment you define once, and you start tasks from the web, the desktop app, mobile, the CLI or Slack. Cursor Cloud Agents each get a virtual machine with your repositories, dependencies and secrets, and can be started from more places, including an API. Cursor also lets you run cloud agents on machines you manage, which it announced on September 2.

Codex has the simpler review story for a small team, because it is already paid for. Cursor has the more flexible agent setup, and you pay for each piece you turn on.

Before either tool touches a client's code, confirm a few settings. They are easier to set before the team forms habits.

Codex

• Sandbox. Locally the agent runs in an operating system sandbox: Seatbelt on macOS, bwrap with seccomp on Linux. The modes are read-only, workspace-write and danger-full-access. The Auto preset is workspace-write with approvals on request.
• Network. Off by default for local runs. In Codex Cloud, internet access is a per-environment setting, and you can limit it to package manager domains.
• Training. OpenAI's pricing page lists "No training on your business data by default" for Business. Personal plans have their own data controls, so do not let the team work from personal Plus accounts on client code without checking them.
• Admin. Business has SAML SSO and MFA.

Cursor

• Privacy Mode. When it is on, Cursor says customer data will not be used for training and that it keeps zero data retention agreements with its model providers. When it is off, Cursor may store and use code, prompts and editor actions. Teams can enforce Privacy Mode for every member. Do that first.
• Models without zero retention. These are marked, or need admin approval for your workspace.
• Certifications. Cursor lists SOC 2 Type II and ISO 27001 among others, with reports through its trust portal.
• Cloud Agents. They hold your repositories and secrets in a remote machine. Decide which secrets they may see, or use self-hosted machines.

One more point for regulated teams. Cursor's data-use page does not spell out how code is handled across the wider Grok bundle beyond the Privacy Mode commitment, and it links out to SpaceXAI's enterprise terms. If a client contract names subprocessors, get the answer in writing from Cursor's sales team before you roll it out.

Codex fails when the task is vague. It will produce a clean pull request for the wrong thing. It is also the weaker tool for fast, exploratory editing, where you want to nudge a component twenty times in ten minutes. The five-hour windows can stall a developer in the middle of a push, and the published limits are estimates, so you learn your real ceiling by hitting it. And you are betting on one model vendor.

Cursor fails on cost control and on distance. A developer with an agent open all day on a third-party model can spend more than the seat price in a week, and the charge is easy to miss until the credit balance drops. The ownership change adds a question no one can answer yet, which is how long rival models stay first-class inside a product whose seat price only covers the house models.

Both share the failure that matters most. They write code faster than a small team can review it. Without tests, a staging environment and one person who owns the merge button, either tool will fill your repository with code nobody on the team has read.

Running both is a reasonable setup if you keep the roles separate. The pattern I would suggest for five people: everyone gets a ChatGPT Business seat for Codex tasks and GitHub review, and the two or three engineers who do the most hands-on front-end work also get a Cursor Premium seat. On monthly billing that is $125 plus $60 to $90, so $185 to $215 a month before extra usage.

OpenAI's docs list Cursor among the editors the Codex extension supports, so the two can sit in one window. Send the longer jobs, such as a dependency upgrade, a test backfill or a refactor across forty files, to Codex and review what comes back.

What does not work is paying for both and letting each developer choose per task with no convention. You end up with two review bots commenting on every pull request and a bill nobody can explain. Pick one reviewer.

Here is how I would map real situations to a pick. Adjust for the people you have.

• A solo founder shipping an MVP: Codex on ChatGPT Plus at $20 a month. You already use ChatGPT, and delegating tasks suits someone doing five jobs. If you are a strong engineer who wants to type, Cursor Premium at $30 is close behind.
• A non-technical founder: neither, on its own. Both assume someone can read a diff. Get a developer or a team first.
• A 5-person team on a React Native app: Codex on Business for everyone, plus Cursor seats for the engineers who live in screens and components. Mobile UI work is full of small visual adjustments that go faster in an editor.
• A regulated fintech codebase: Codex through Business or Enterprise, with the sandbox left on workspace-write and network access restricted. If the team insists on Cursor, enforce Privacy Mode and look at self-hosted machines for agents.
• A large legacy monorepo: Cursor for the engineers learning the code, since codebase search and inline questions help most there, and Codex Cloud for the mechanical migrations once someone has written the pattern down.
• A team that already standardized on Claude models: Cursor, with a firm monthly cap, or a different agent altogether.

The tool is a smaller decision than it feels like this week. Scope and a clear first version move a launch date far more than the editor does. Politik, a civic app we built with three founders who had never shipped software, reached the App Store in under three months and hit #2 there. That came from a tight first version and a two-week product sprint at the start. You can read the full story on the Politik case study.

If you are still at the stage of working out what to build and in what order, our founder's guide to creating an app is the next thing to read. Kanopy helps founders pick a stack and build the product on it, so if you want a second opinion on your tools and your first version, Book a free strategy call.