> Couldn’t tell.

Why would you expect them to be able to recognize the signature of a model from a pair of PRs? I don’t understand why you think this is a useful test for anything when we have numerous benchmarks that run 100s of tests on models and both GPT-5.5 and Opus-4.8 perform similarly.

I have subscriptions to both. I run both on max reasoning. It is interesting to see the relative strengths and weaknesses of each model. You won’t always see it if you’re just scanning code. Some times one will spin for a long time on certain problems where the other has no problem finding the appropriate parts of the codebase and getting an efficient solution.

antirez made a comment that he and others found GPT-5.5 to be better at the optimization tasks he was working on than Opus. There are other classes of tasks where GPT-5.5 consistently stumbles where Opus will get a solution quicker. Lately I’ve been working on some code where neither model comes up with a good solution. That’s just how LLMs go.

The only reason you have seen more activity about Claude is that they got there first. Codex has been a step behind and GPT couldn’t match Opus at first. You’re testing them after they’ve closed the gap.

Anecdotally I hear of folks with workplace Claude Code subscriptions all the time. I'm not sure I've ever heard someone talk about their workplace Codex subscription. Anthropic clearly did a far better job chasing corporate customers while OpenAI was busy chasing consumers with Sora etc.

For example in your "test" you're only looking at output and ignoring the entire process of creation.

In addition to that process, you're ignoring that Claude Code was first and better for a long time, why would people switch for something that produces the same output? Claude Code has been way ahead in the process of agentic software creation for a long time, I still prefer its features. Even though I think that Opus 4.7 was a big step backwards, and I've been getting worse results seemingly every day with the churn of features at Claude Code, some of that may also be me testing the bounds of how little I can specify and still get acceptable results, so it's hard to know.

Calling all these concrete realities "marketing" is itself you trying to market Codex as "good enough" instead of paying attention to how we got where we are and where we will go in the future.

Convinced you can distinguish A from B? Ok! No problem, let's try! Can be at the dinner table for fancy wine or with agents, it's all the same, you try an option, another option, maybe all options from the same, and if you reliably can't tell well kudos, you are just like the rest of us!

It's easy to "know" in retrospect but blind test is where genuine difference can be found. Or not.

I have a strong affinity for Claude Code because of the interaction experience and overall tone / vibe / process. I am 100% willing to believe the code it produces is identical or possibly less good than Codex.

I enjoy working with Claude in a way I just don’t get from OpenAI. YMMV, you may feel just the opposite. But it’s a mistake to look at the produced code as the only dimension of these products.

Codex I feel the need to be very specific and precise with. Claude… I feel like I can be lazy, which I enjoy.

Both still need to be reviewed stringently but I feel I can be more ambiguous with Claude and get better results than when Codex.

2. In my case codex seem to be writing a more solid code, but I still use claude most of the time because it's my witty rubber ducky and I can actually sometimes force some legit insights out of it. Codex is much worse at this. And whether that matters or not depends on the project.

I do think OpenAI is doomed due to bad leadership. What you said (that the marketing is relatively terrible) and what others are saying here (that the product is worse) is damning isn't it? Are they really failing on all fronts?

GPT 5.5 genuinely was back on top for a while there, but if you look at the past 2 years, being on Claude was better than being on OpenAI most of the time. If you're going to pick a tool and not switch constantly it was the right choice. Not to mention their tooling has always been ahead, and that gets ecosystem benefits.

Are they close and interchangeable today? Sure. But Sonnet was genuinely way better than anything OpenAI offered for a long time -- the valuation reflects that, not any given moment in time.

add deepseek v4 to it, and it will be close at 1/10 th the price. I use all three codex, claude, and deepseek, and they are close.

For general use, ChatGPT's answers have gotten worse over the last year. I abandoned it.

Claude commit messages - well structured test plan, readable.

Codex commit messages - wall of text, no structure.

The big difference though is sitting with the tools and using them for work. These are for sure vibes, but I’m sure you could pull out metrics for # steering re-prompts for example.

Codex just goes off and solves the problem, usually comes back with a solve; Claude more often gives up or needs input. Opus gives a broader design discussion, better at conversation. Codex finds deeper/better edge cases.

I think it’s like EMacs vs Vim - you can get your work done with both. There may be some tasks where one is way stronger. A strict “Better” is quite hard to justify.

Ultimately tool choice is a mix of science and art/taste; I want to feel joy using my tools, and fun little pixel explosions make me happy. If a different tool makes you happy, that is also fine.

This is complicated by the way that the coding agents inject prompts that preempt and potentially undermine user instructions. I suspect that one of the reasons Codex works way better for me than Claude Code in certain projects is that the latter adds some garbage like "go ahead and write repetitive copy/paste code, keep it simple, take shortcuts" to every session. A fair test would have to hide but more or less still use the harnesses, not just the models.

Same reason people buy the RTX 4090 and 5090 cards - overpriced but they must have the "best". Never mind the diminishing returns trying to max out PC settings (3-4x performance hit for an almost imperceptible increase in graphics, ignoring DLSS) - it's the psychological cost of having to move a slider down a notch.

I've been using Google and now DeepSeek v4 and I am having absolutely no problems and it's a fraction of the cost. I'd love for Claude to be 10x better but it just isn't, for my use case anyway.

I think you're missing one (or more) of the facets individuals decide "better" is, for the subjective individual.

Early on i hopped between all the providers. Code quality for SOTA at the time was pretty decent if you didn't ask it to solve challenging problems. However the thing i found most difficult is consistency in how it listened. Eg Gemini (i forget what version, not current) was super prone to focusing solely on the functionality/goal, but not any of the directions on how to write the code. It would throw in comments everywhere, document in a manner i didn't want, use abstractions i told it not to, etc.

How well a model would follow instructions to drop their horrible "isms" was the #1 criteria for me. If i have to constantly remind the model not to do X behavior then it's a terrible model.

With that said, that is why i chose Claude for the last N months. However i've stuck with Claude because dealing with these "isms" and their little behavioral nuances is a chore in itself. I've found you have to learn the model just as much as anything, and so the idea of hopping these days when i'm just trying to get shit done is not likely.

These days for me personally, Claude has to give me a reason to switch rather than me investing even more money (i'm on the 20x plan) in other providers. I'm definitely not committed to Claude Code, but i am tired of the LLM churn, tooling churn, subscription churn, and the general fear of which providers we can trust.

edit: In short, it's the interactive UX just as much as it is the final output.

b) therefore a preference for Claude is marketing - complete bollocks

Either the tasks you chose were well below the capabilities of top models, or meaningful differences for preference are elsewhere, or both.

Your comment is probably energy-efficient and sustainable, however, because you could use it again and again when another comparison comes up, like Vim vs Emacs, or tea vs coffee

They served caviar. It probably had good ROI.

This is a really important insight. Great comment.

So much faith and money in this idea, and seeing how fragile it is, does not look good.

Some of its timing: Claude Code was good before other harnesses and so behaviors (and contracts) were timed to lock in on that ecosystem.

Some of it was ethical/political: Anthropic fighting with the Trump admin about use of the model.

Some of it is social: Never overrate a CEO just being kind of perceived as a piece of shit by people who have power to influence decisions.

But switching costs are low! Because of the same models!

Let the race to the bottom commence. Hopefully before the monopoly/collusion starts.

The belief structures here are really interesting. Blind tests would likely illuminate a lot of why people think that

1) Brockman ($25M) and Altman ($1M) both personally donated to Trump/MAGA.

2) Anthropic pushed back against DOD's demand for unrestricted use of AI to kill people while OpenAI eagerly said "please use ours!".

It’s one of the things I don’t like about it. All humans are susceptible to herd behavior and influence but engineers should be at least a bit more hard nosed and reason more from first principles.

It's the same reason why most of the software out there keeps using bloated technologies that are most of the time the wrong fit for the product.

And the same applies to tooling. Nothing new.

That seems like a strawman.

I can tell. It's night and day.

Last year I used a bunch of models to try to generate Rust code. They all sucked.

This February I tried again and used Claude to generate Rust code. I have never been more stunned in my life. It's just as good as I am, and 30x faster. No fluff, the code is verbatim just as I would have written.

I then tried other models. Total disappointment.

I've continued to repeat this experiment. Opus is the only model that can write Rust reasonably.

Codex produces junk to this day. It passes variables that aren't needed, it abuses pointers, it creates overly verbose monstrosities...

I don't want any single company to win. I want OpenAI to be competitive. I want open source models to win. But right now, Claude Code and Opus are it.

Having a sleazy CEO like Sam Altman or Elon Musk is a business risk. Many potential customers don’t like these people and they say abrasive and alienating things publicly.

Rolling over to the DoD’s desire for fully automated weaponry is more bad marketing. How many people switched from OpenAI to Anthropic over that? I sure did. Anthropic’s willingness to burn that bridge over an ethical stance said a lot about the company to me.

I’m not going to use OpenAI products for these reasons among others.

I’m also not going to use Cursor as xAI plans to acquire Cursor.

Maybe it’s foolish of me to avoid those companies for such petty reasons, but that’s not my problem. That’s their problem.

It takes years to build trust and hours to burn that trust to the ground. Customers can hold grudges for a lifetime.

This is especially true in a market with almost zero product differentiation.

Maybe not your typical HN crowd but marketing absolutely works on developers.

I have no idea how this wasn't the end of Anthropic's positive public perception.

At the top level of anything there is almost no such thing as a non-asshole.

None of them care genuinely about you they just want your money.

That's why he chose the OpenAI logo

Just curious how you can afford to care about the guy 7 levels above the men that built and support the API that you buy.

What Anthropic has done exceedingly well is work their way into corporations.

I have personally seen massive uptake over the last 6 months of regular people in corporations using Claude cowork. They are all genuinely amazed by what it can do for them.

OpenAI wants to be more of a Google. It’s increasingly seeming like consumer may not be as good of a play here

When Anthropic had the dispute with the Department of War over very meek conditions (a truly moral AI company would not be engaged in war crimes in the first place), it was a test for Altman, all he had to do was to take the same position. But because he's a psychopath he failed that very basic test.

We've always been having these debates over whether my choice of tech is better than your choice of tech, same holy wars, different type of tech

The advice today is the same as it was 10/20/30+ years ago, pick what works for you and build something good with it

Nobody will actually care how you built it, regardless of whether its good or crap (although if it's crap you can blame your tools)

The official implementation of apply_patch is well thought out. It is a two-phase process that will not actually make any changes until all files in the change set are not ambiguous. The pre-commit error feedback usually fixes anchoring issues with one or two additional attempts. It generally goes something like:

  Reading file A L1:154
  Reading file B L1:123
  Attempting to apply patch... 
  [anchor errors for both A & B]
  Reading file A L43:67
  Reading file B L50:74
  Attempting to apply patch... 
  Patch succeeded! Running compilation & unit tests...

Techniques that replace the whole file or depend on find-replace are useful in more isolated contexts. However, when you need to refactor 20+ files, something like apply_patch is what you want. Anything that depends on specific line numbers for actual replacement targets is a total dead end for complex edit scenarios.

https://developers.openai.com/api/docs/guides/tools-apply-pa...

Codex is very "miss the forest for the trees", but is much better at successfully making large changes in large codebases. Claude Code makes more mistakes, but has more taste and a better grasp on idiomatic and elegant software development.

If you can afford to, I recommend juggling both.

I have specific skills for trying to avoid this, but nevertheless I spent half of the time fighting with its verbosity.

Currently, I'm trying to scaffold the functions/classes I know I need with NotImpelmented and ask it to implement only inside those specific places. It's a little bit better, but I still have to fight with function in functions definitions ...

Admittedly my recent experience tilts Opus now 4.8, but you and others have my interest piqued re: GPT-5.5 Codex so I'm trying that more now.

Even now, I would guess that if you ask a normie off the street, they are far, far more likely to have heard of ChatGPT than Claude. Of course, Anthropic has been targeting businesses quite a bit harder than the general public for a while, so maybe that's not a fair test.

Anthropic inarguably does make an attempt at marketing their product. But I'm not convinced that the closing of the gap between them and OpenAI (as others have pointed out: I'm not sure it's defensible to claim that either is significantly ahead of the other given the paucity of available data, but they are certainly much closer than they were a year or two ago, when OpenAI was clearly in the lead) is mostly down to that. I think that, for a decent chunk of time (this one I mean in the AI world sense of the term), they had a very non-trivial lead in coding abilities. The developer and business world figured this out and jumped on board. That gap is largely now erased, but that's not enough to retake the momentum.

You can theoretically do most things AWS does most of the time, yet people pay premium for it and keep paying for it, even though alternatives are cheaper, simpler and more performant.

I'd bet you that after 20 years OpenAI and Anthropic would still be around and kicking.

You might have a subpar product (for the price) but the reputation and history is what makes people open their wallets.

Now, I think that with these companies IPO'ing and Nasdaq and other bending themseleves and their rules to cater to them (as in case of SpaceX), these companies are very close to an IPO.

So for the employees, they are probably gonna get good evaluations, atleast in the short term and perhaps they are having a problem which is worth having.

But as you have suggested, I feel like the whole thing might be flaky especially given open source models. I believe that OSS models are at worst close to literal SOTA ~6 months ago.

So OpenAI & Anthropic have to somehow always be on the edge to get better models to not lose this (imo) very small time grip that they have, all while losing billions of dollars and having to worry about profitability & so many other concerns in it of itself.

I don't think that there is any other thing inside CS or any industry where two pieces of software being almost comparable enough with not much moat around except a diff of 6 months best, is something on which trillions of dollars float around on. We don't know how things will pan out but if I have to guess, It might not be looking good for OAI, Anthropic over especially the longer horizon.

What infrastructure? The hardware would be outdated in 3 - 5 years, after all. What other infrastructure is needed for AI?

So it's more like selling a derivative on a promise to steal open source for you in a useful way.

Nobody is investing in closed-source labs for safety reasons, being able to explore more in details what and how the model is thinking is nice but by no means a game changer. What matters to investors and most of the users is that the model gives the right answer at the end.

Anthropic has much narrower capabilities. No image generation, no video generation, no 3d world models, barely any voice stuff. But they know who their target customers are, and their API has a model selection anyone can understand and pricing that rarely changes. Focus and predictably

Everyone I know at Anthropic is miserable. It’s not a fun place to work. There’s a reason you never see Anthropic employees talking online.