Every week someone asks me which of the two is better.
I have been running both on the same project for months, and the answer I would give is not about which writes better code.
(abertura sugerida: confira se bate com a sua memória e ajuste para a sua voz antes de postar)
Claude Code versus Codex is the most asked question about AI coding agents, and most answers end in a draw with a list of pros and cons. This one tries to be useful differently.
Where the difference actually shows
On everyday tasks, both deliver. The difference shows at the edges, and it is a difference of temperament more than capability: one tends to be conservative and explain before changing, the other tends to act and show you the result. Which is better depends entirely on whether you are exploring a problem or executing something already decided.
This changes with every release on both sides, which is why quality comparisons age in weeks. One criterion that does not age: which one is already paid for in your account.
Why using both beats choosing
Asking the model that wrote the code to review the code is asking it to find a mistake it did not see while writing. Two models from the same company give you two versions of one opinion. Two from different companies disagree, and where they disagree is a map of what deserves your attention.
In practice: one implements, the other reviews. The second finds things the first considered settled, and the cost of finding out is a question instead of a production bug.
What it costs to run both
Less than you would think, because both tools run on subscriptions you probably already have. No API key, no per-token usage: each CLI uses the authenticated session of its own subscription. If you already pay for Claude and ChatGPT, using both on the same project costs nothing extra.
I wrote the full version, with the parts that did not fit here:
https://canvascode.app/en/news/claude-code-vs-codex-which-one-to-use
Top comments (1)
The “both” answer makes sense when the tools have different strengths in the workflow. I would choose based less on brand and more on where the project needs help: exploration, patch discipline, repo context, review, or repeated automation.