Neither OpenAI Codex nor Claude Code is a defensible all-purpose winner. The better fit depends on the work you hand it, how you want to supervise it, your repository’s permission boundaries, and what your plan allows. A 2026 study of pull requests found that task category affected acceptance rates substantially, while the products also offer different combinations of local, cloud, terminal, desktop, and IDE workflows.
What does the available benchmark actually show?
A 2026 study by Pinna, Gong, Williams, and Sarro analyzed 7,156 agent-attributed pull requests in the AIDev dataset. It found an 82.1% acceptance rate for documentation changes and 66.1% for new-feature changes. The 16-point gap between those task categories was larger than typical differences between agents for most tasks in the analysis. Read the study, “Comparing AI Coding Agents: A Task-Stratified Analysis of Pull Request Acceptance.”
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Within that dataset, Claude Code had the highest reported figures in two categories highlighted by the authors: 92.3% acceptance for documentation and 72.6% for features. Codex ranged from 59.6% to 88.6% across nine task categories. These are observations from that study, not current guarantees or a universal ranking.
The unit measured was pull-request acceptance, not speed, code quality, security, productivity, or cost per accepted change. The analysis was not a randomized head-to-head trial in which both agents received identical prompts on identical repositories with identical model versions and conditions. It is useful evidence that task type matters; it cannot predict which agent will do better on your codebase.
#1 Best Overall
How do the workflows differ?
Both products can work with code, but they offer distinct ways to start, supervise, and execute tasks. OpenAI describes Codex as an agent for writing, reviewing, and shipping code, available through desktop, CLI, IDE extension, web, and cloud workflows. Cloud tasks run on OpenAI-managed computers; local workflows run on the user’s device. The specific surfaces and availability can change, so check the current Codex plan and access details.
Anthropic describes Claude Code as an agentic coding tool that can read a codebase, edit files, run commands, and integrate with development tools. Its documented surfaces include terminal, IDE, desktop, and browser. Most require a Claude subscription or Anthropic Console account; see Anthropic’s Claude Code overview.
| Decision point | OpenAI Codex | Claude Code |
|---|---|---|
| Documented surfaces | Desktop, CLI, IDE extension, web, and cloud | Terminal, IDE, desktop, and browser |
| Execution location described by vendor | Local workflows run on the user’s device; cloud tasks run on OpenAI-managed computers | The overview describes its surfaces and agent capabilities; it does not establish one universal execution location |
| Typical fit to investigate | Teams that want to choose between local work and delegating tasks to a cloud environment, or coordinate multiple agent threads | Developers who want an agent within terminal- or IDE-centered work, with documented desktop and browser options |
The “fit” examples are workflow questions to evaluate, not claims that either product performs better. Codex’s announced app workflow supports multiple agent threads and isolated Git worktrees. Whether that helps depends on whether parallel work and branch isolation match your review practices. Compare the Codex app announcement with how your team actually manages concurrent changes.
What should you compare about permissions and execution?
Security controls are important, but vendor documentation about controls does not independently prove that one product is categorically safer. Compare the boundaries you need, what triggers an approval, where commands run, and what your team is responsible for reviewing.
Codex
OpenAI says the Codex app limits editing by default to files in the working folder or branch and requests permission for commands requiring elevated access, such as network access. Those are vendor-described defaults and can change. Consult the Codex app announcement and confirm the behavior in the particular surface and plan you intend to use.
Claude Code
Anthropic documents manual and auto permission modes, sandboxed Bash with filesystem and network isolation, and prompts for access to files outside the working directory in Manual mode. It also says users remain responsible for reviewing proposed code and commands. See the Claude Code security documentation for the controls and their scope.
Rank #4
For either agent, make the comparison against your actual threat model and repository setup. A permission prompt, sandbox, or working-directory boundary is a control to understand—not a substitute for reviewing changes, commands, and organizational data-handling requirements.
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Codex access is included across ChatGPT plans, but usage allowances and limits vary. There is no single flat Codex price established by the cited access information; check the current plan details for your market and intended usage on OpenAI’s Codex plan page.
Best Value
Anthropic’s pricing page, checked October 3, 2026, listed Claude Pro at $20 when billed monthly or $17 per month with annual billing, and Claude Max starting at $100 monthly. Anthropic notes that plans and prices can change. These are listed subscription prices, not a direct measure of how many coding tasks a particular team can complete; verify current terms on Anthropic’s pricing page.
Compare likely usage, limits, and any organization-specific requirements along with subscription cost. The available evidence does not establish time saved or cost per accepted change for either tool; those outcomes depend on task mix, correction effort, review burden, and usage in your environment.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How can you choose fairly for your team?
Run a small pilot on the repository and tasks your team actually handles. The study’s task-category differences and the products’ different workflows make a single generic coding prompt a weak basis for a purchase decision.
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Outbyte Driver Updater FREEScan for outdated or missing drivers - takes under a minuteDriver Scan →Outbyte PC Repair FREEClear out junk files and repair common Windows errorsFree Scan →- Choose representative work. Include tasks your team regularly assigns—such as documentation, bug fixes, and new features—rather than selecting only a task that favors one workflow.
- Keep the comparison fair. Start from equivalent repository states and use comparable task descriptions, permissions, and review expectations. Record product and plan details because models, features, and limits can change.
- Use your real supervision model. Evaluate each product through the surface and execution mode your team would adopt, including whether work is local or cloud-delegated and how changes are reviewed.
- Measure outcomes that matter to you. Track acceptance, correction effort, review burden, and usage cost. Do not treat pull-request acceptance alone as a measure of speed, security, or productivity.
- Check organizational fit. Verify permission behavior, data-handling terms for the specific plan, and any team controls before expanding use.
This pilot is a practical decision method, not a published comparative test of the two products. It gives your team evidence about its own repository and operating constraints rather than assuming a benchmark result will transfer.
Which one should you choose?
Start with the work and workflow, not the headline benchmark. Codex is worth evaluating first if its mix of local and cloud work, multiple surfaces, or agent threads fits how your team delegates and reviews code. Claude Code is worth evaluating first if its terminal- and IDE-centered options and documented permission modes better match how developers work in your environment. Neither point establishes superior coding performance; use the same representative pilot to decide.
Quick Recap
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