As a scientist (computational physicist, so plenty of math, but also plenty of code, from Python PoCs to explicit SIMD and GPU code, mostly various subsets of C/C++), I can confirm - Codex is qualitatively better for my usecases than Claude. I keep retesting them (not on benchmarks, I simply use both in parallel for my work and see what happens) after every version update and ever since 5.2 Codex seems further and further ahead. The token limits are also far more generous (and it matters, I found it fairly easy to hit the 5h limit on max tier Claude), but mostly it's about quality - the probability that the model will give me something useful I can iterate on as opposed to discard immediately is much higher with Codex.

For the few times I've used both models side by side on more typical tasks (not so much web stuff, which I don't do much of, but more conventional Python scripts, CLI utilities in C, some OpenGL), they seem much more evenly matched. I haven't found a case where Claude would be markedly superior since Codex 5.2 came out, but I'm sure there are plenty. In my view, benchmarks are completely irrelevant at this point, just use models side by side on representative bits of your real work and stick with what works best for you. My software engineer friends often react with disbelief when I say I much prefer Codex, but in my experience it is not a close comparison.

I'm in that camp -- I have the max-tier subscription to pretty much all the services, and for now Codex seems to win. Primarily because 1) long horizon development tasks are much more reliable with codex, and 2) OpenAI is far more generous with the token limits.

Gemini seems to be the worst of the three, and some open-weight models are not too bad (like Kimi k2.5). Cursor is still pretty good, and copilot just really really sucks.

Claude Code, Codex, and Cursor are old news. If you're having problems, it's because you're not using the latest hotness: Cludge. Everyone is using it now - don't get left behind.

As some other people mentioned, using both/multiple is the way to go if it's within your means.

I've been working on a wide range of relatively projects and I find that the latest GPT-5.2+ models seem to be generally better coders than Opus 4.6, however the latter tends to be better at big picture thinking, structuring, and communicating so I tend to iterate through Opus 4.6 max -> GPT-5.2 xhigh -> GPT-5.3-Codex xhigh -> GPT-5.4 xhigh. I've found GPT-5.3-Codex is the most detail oriented, but not necessarily the best coder. One interesting thing is for my high-stakes project, I have one coder lane but use all the models do independent review and they tend to catch different subsets of implementation bugs. I also notice huge behavioral changes based on changing AGENTS.md.

In terms of the apps, while Claude Code was ahead for a long while, I'd say Codex has largely caught up in terms of ergonomics, and in some things, like the way it let's you inline or append steering, I like it better now (or where it's far, far, ahead - the compaction is night and day better in Codex).

(These observations are based on about 10-20B/mo combined cached tokens, human-in-the-loop, so heavy usage and most code I no longer eyeball, but not dark factory/slop cannon levels. I haven't found (or built) a multi-agent control plane I really like yet.)

Us = me and say /r/codex or wherever Codex users are. I've tried both, liked both, but in my projects one clearly produces better results, more maintainable code and does a better job of debugging and refactoring.

I've found claude startlingly good at debugging race conditions and other multithreading issues though.

Not a scientist and use codex for anything complex.

I enjoy using CC more and use it for non coding tasks primarily, but for anything complex (honestly most of what I do is not that complex), I feel like I am trading future toil for a dopamine hit.