[saberience]

This is kinda FUD. Claude really isn’t that good compared to Codex firstly and if you combine the latest DeepSeek model with any good coding harness the results are surprisingly comparable to Claude Code.

I would say DeepSeek is definitely behind compared to Codex but Claude doesn’t and hasn’t impressed me for some time now. It writes way too much code when it doesn’t need to in a fashion that gradually rots your codebase.

Codex is the only model I’ve used which will regularly remove more code than it adds or make a fix or feature by adding a single line of code or otherwise do minimal working changes.

Claude is the model which can get the feature working by adding two new classes, 20 new methods and 2000 lines of code, when it actually needed to remove 500 lines of code and add two new methods.

Claude will also often refactor by adding tons of new code and using it while not deleting any of the old code.

[IXCoach]

Fascinating, Claude outperforms codex in my coding setup by 5X to 10X, its not even close. Interesting that your claiming the opposite is a general fact here, if i take you literally at your word. Codex has been so bad, in fact, that while I was maintaining a $200/m sub I literally did not even "use it up" while paying for it, ( after cancelling ).

But that was 3 months ago, have not tried it since, they could have grown.

To be fair, I think what you are meaning, if I drop the literal frame here, is this, tell me if I am right:

Codex > Claude in my setup.

that right?

To be fair, my tests were not apples to apples. I have sophisticated agent alignment harnesses which prevent claude from hallucinating or going off the rails, ( not literally, not 100% = about 80% less hallucination, about 90% less drift, and about 98% more starting from crystal clear intent.

And in my personal tests, codex was not calibrated to use those systems, it had them but would have needed to find them.

Also I am in a massive project, next ai labs, ixcoach, with likely in the range of 20k files of code, 100x files of docs...

It could just be my agent alignment harness thats making claude outperform codex. Looking into testing it on the major benchmarks and publishing the results.

[ay]

Both you and parent could be right.

There is a fun term “jagged frontier”.

Meaning: one model can be much better than the other one in one thing, and much worse than the other in another thing.

[nsonha]

Codex 3 months ago was really different (I think they released 2 versions since?). It was also the same time that I started using Codex and I see no different in quality comparing to Claude. Still using Claude mainly because work mandates it, but doing all my personal stuff with Codex now.

[rapind]

Claude at times feels lobotomized compared to where it was a few months ago with 4.6. I think Anthropic was (is still?) struggling with their infrastructure and hasn't felt as good for me anecdotally for a few months. Significantly enough that I've cancelled (max 20x).

Codex 5.5 extra high currently feels a good amount smarter than either 4.6 or 4.7 Opus. I only just started using it about a week ago, so maybe that's a recent development and then OpenAI will eventually lobotomize their model or throttle etc.

What I dislike about frontier models is how opaque and incentivized the businesses are about tweaking their services. Anthropic definitely does some shady throttling. I have zero trust for Altman and he's BS AGI claims. And Google makes it non-obvious that you can't turn Gemini training off on even their highest tier personal plan. There's a lot of shady and dishonest behaviour, probably because they are all overhyped and heavily subsidized to win the race. I don't mind at all paying more than I currently am for these services, but I don't trust any of these frontier model companies, and so I'm cheering for open models.

Right now I'm using Codex for planning and DeepSeek V4 Flash [1m] for implementation. It's quite fast. Quite possible / likely that OpenAI will make significant changes that kill this workflow for w/e reason... at which point I will probably move to full open weight models.