Whats interesting to me is that these gpt-5.3 and opus-4.6 are diverging philosophically and really in the same way that actual engineers and orgs have diverged philosophically
With Codex (5.3), the framing is an interactive collaborator: you steer it mid-execution, stay in the loop, course-correct as it works.
With Opus 4.6, the emphasis is the opposite: a more autonomous, agentic, thoughtful system that plans deeply, runs longer, and asks less of the human.
that feels like a reflection of a real split in how people think llm-based coding should work...
some want tight human-in-the-loop control and others want to delegate whole chunks of work and review the result
Interested to see if we eventually see models optimize for those two philosophies and 3rd, 4th, 5th philosophies that will emerge in the coming years.
Maybe it will be less about benchmarks and more about different ideas of what working-with-ai means
> With Codex (5.3), the framing is an interactive collaborator: you steer it mid-execution, stay in the loop, course-correct as it works.
> With Opus 4.6, the emphasis is the opposite: a more autonomous, agentic, thoughtful system that plans deeply, runs longer, and asks less of the human.
Ain't the UX is the exact opposite? Codex thinks much longer before gives you back the answer.
I've also had the exact opposite experience with tone. Claude Code wants to build with me, and Codex wants to go off on its own for a while before returning with opinions.
I'm personally 100% convinced (assuming prices stay reasonable) that the Codex approach is here to stay.
Having a human in the loop eliminates all the problems that LLMs have and continously reviewing small'ish chunks of code works really well from my experience.
It saves so much time having Codex do all the plumbing so you can focus on the actual "core" part of a feature.
LLMs still (and I doubt that changes) can't think and generalize. If I tell Codex to implement 3 features he won't stop and find a general solution that unifies them unless explicitly told to. This makes it kinda pointless for the "full autonomy" approach since effecitly code quality and abstractions completely go down the drain over time. That's fine if it's just prototyping or "throwaway" scripts but for bigger codebases where longevity matters it's a dealbreaker.
I'm personally 100% convinced of the opposite, that it's a waste of time to steer them. we know now that agentic loops can converge given the proper framing and self-reflectiveness tools.
I think it's the opposite. Especially considering Codex started out as a web app that offers very little interactivity: you are supposed to drop a request and let it run automatously in a containerized environment; you can then follow up on it via chat --- no interactive code editing.
Fair I agree that was true of early codex and my perception too.. but today there are two announcements that came out and thats what im referring to.
specifically, the GPT-5.3 post explicitly leans into "interactive collaborator" langauge and steering mid execution
OpenAI post: "Much like a colleague, you can steer and interact with GPT-5.3-Codex while it’s working, without losing context."
OpenAI post: "Instead of waiting for a final output, you can interact in real time—ask questions, discuss approaches, and steer toward the solution"
Claude post: "Claude Opus 4.6 is designed for longer-running, agentic work — planning complex tasks more carefully and executing them with less back-and-forth from the user."
This kind of sounds like both of them stepping into the other’s turf, to simplify a bit.
I haven’t used Codex but use Claude Code, and the way people (before today) described Codex to me was like how you’re describing Opus 4.6
So it sounds like they’re converging toward “both these approaches are useful at different times” potentially? And neither want people who prefer one way of working to be locked to the other’s model.
> With Opus 4.6, the emphasis is the opposite: a more autonomous, agentic, thoughtful system that plans deeply, runs longer, and asks less of the human.
This feels wrong, I can't comment on Codex, but Claude will prompt you and ask you before changing files, even when I run it in dangerous mode on Zed, I can still review all the diffs and undo them, or you know, tell it what to change. If you're worried about it making too many decisions, you can pre-prompt Claude Code (via .claude/instructions.md) and instruct it to always ask follow up questions regarding architectural decisions.
Sometimes I go out of my way to tell Claude DO NOT ASK ME FOR FOLLOW UPS JUST DO THE THING.
yeah I'm mostly just talking about how they're framing it:
"Claude Opus 4.6 is designed for longer-running, agentic work — planning complex tasks more carefully and executing them with less back-and-forth from the user"
I guess its also quite interesting that how they are framing these projects are opposite from how people currently perceive them and I guess that may be a conscious choice...
I am definitely using Opus as an interactive collaborator that I steer mid-execution, stay in the loop and course correct as it works.
I mean Opus asks a lot if he should run things, and each time you can tell it to change. And if that's not enough you can always press esc to interrupt.
I would love to see a nutritional facts label on how many prompts / % of code / ratio of human involvement needed to use the models to develop their latest models for the various parts of their systems.
Just some anecdata++ here but I found 5.2 to be really good at code review. So I can have something crunched by cheaper models, reviewed async by codex and then re-prompt with the findings from the review. It finds good things, doesn't flag nits (if prompted not to) and the overall flow is worth it for me. Speed loss doesn't impact this flow that much.
5.2 Codex became my default coding model. It “feels” smarter than Opus 4.5.
I use 5.2 Codex for the entire task, then ask Opus 4.5 at the end to double check the work. It's nice to have another frontier model's opinion and ask it to spot any potential issues.
Opus 4.5 still worked better for most of my work, which is generally "weird stuff". A lot of my programming involves concepts that are a bit brain-melting for LLMs, because multiple "99% of the time, assumption X is correct" are reversed for my project. I think Opus does better at not falling into those traps. Excited to try out 5.3
Another day, another hn thread of "this model changes everything" followed immediately by a reply stating "actually I have the literal opposite experience and find competitor's model is the best" repeated until it's time to start the next day's thread.
In my personal experience the GPT models have always been significantly better than the Claude models for agentic coding, I’m baffled why people think Claude has the edge on programming.
I think for many/most programmers = 'speed + output' and webdev == "great coding".
Not throwing shade anyone's way. I actually do prefer Claude for webdev (even if it does cringe things like generate custom CSS on every page) -- because I hate webdev and Claude designs are always better looking.
But the meat of my code is backend and "hard" and for that Codex is always better, not even a competition. In that domain, I want accuracy and not speed.
GPT 5.2 codex plans well but fucks off a lot, goes in circles (more than opus 4.5) and really just lacks the breadth of integrated knowledge that makes opus feel so powerful.
Opus is the first model I can trust to just do things, and do them right, at least small things. For larger/more complex things I have to keep either model on extremely short leashes. But the difference is enough that I canceled my GPT Pro sub so I could switch to Claude. Maybe 5.3 will change things, but I also cannot continue to ethically support Sam Altman's business.
ARC AGI 2 has a training set that model providers can choose to train on, so really wouldn't recommend using it as a general measure of coding ability.
Opus was quite useless today. Created lots of globals, statics, forward declarations, hidden implementations in cpp files with no testable interface, erasing types, casting void pointers, I had to fix quite a lot and decouple the entangled mess.
Hopefully performance will pick up after the rollout.
There's still no evidence we'll have any take off. At least in the "Foom!" sense of LLMs independently improving themselves iteratively to substantial new levels being reliably sustained over many generations.
To be clear, I think LLMs are valuable and will continue to significantly improve. But self-sustaining runaway positive feedback loops delivering exponential improvements resulting in leaps of tangible, real-world utility is a substantially different hypothesis. All the impressive and rapid achievements in LLMs to date can still be true while major elements required for Foom-ish exponential take-off are still missing.
making the specifications is still hard, and checking how well results match against specifications is still hard.
i dont think the model will figure that out on its own, because the human in the loop is the verification method for saying if its doing better or not, and more importantly, defining better
This has already been going on for years. It's just that they were using GPT 4.5 to work on GPT 5. All this announcement mean is that they're confident enough in early GPT 5.3 model output to further refine GPT 5.3 based on initial 5.3. But yes, takeoff will still happen because of this recursive self improvement works, it's just that we're already past the inception point.
,,GPT‑5.3-Codex is the first model we classify as High capability for cybersecurity-related tasks under our Preparedness Framework , and the first we’ve directly trained to identify software vulnerabilities. While we don’t have definitive evidence it can automate cyber attacks end-to-end, we’re taking a precautionary approach and deploying our most comprehensive cybersecurity safety stack to date. Our mitigations include safety training, automated monitoring, trusted access for advanced capabilities, and enforcement pipelines including threat intelligence.''
While I love Codex and believe it's amazing tool, I believe their preparedness framework is out of date. As it is more and more capable of vibe coding complex apps, it's getting clear that the main security issues will come up by having more and more security critical software vibe coded.
It's great to look at systems written by humans and how well Codex can be used against software written by humans, but it's getting more important to measure the opposite: how well humans (or their own software) are able to infiltrate complex systems written mostly by Codex, and get better on that scale.
In simpler terms: Codex should write secure software by default.
That’s just classical OpenAI trying to make us believe they’re closing on AGI…
Like all « so called » research from them and Anthropic about safety alignment and that their tech is so incredibly powerful that guardrails should be put on them.
>Our mitigations include safety training, automated monitoring, trusted access for advanced capabilities, and enforcement pipelines including threat intelligence.
I remember when AI labs coordinated so they didn't push major announcements on the same day to avoid cannibalizing each other. Now we have AI labs pushing major announcements within 30 minutes.
The labs have fully embraced the cutthroat competition, the arms race has fully shed the civilized facade of beneficient mutual cooperation.
Dirty tricks and underhanded tactics will happen - I think Demis isn't savvy in this domain, but might end up stomping out the competition on pure performance.
Elon, Sam, and Dario know how to fight ugly and do the nasty political boardroom crap. 26 is gonna be a very dramatic year, lots of cinematic potential for the eventual AI biopics.
As long the tactics are legal ( i.e. not corporate espionage, bribes etc), the no holds barred full free market competition is the best thing for the market and the consumers.
This goes way back. When OpenAI launched GPT-4 in 2023, both Anthropic and Google lined up counter launches (Claude and Magic Wand) right before OpenAI's standard 10am launch time.
I wish they’d just stop pretending to care about safety, other than a few researchers at the top they care about safety only as long as they aren’t losing ground to the competition. Game theory guarantees the AI labs will do what it takes to ensure survival. Only regulation can enforce the limits, self policing won’t work when money is involved.
The last thing I would want is for excessively neurotic bureaucrats to interfere with all the mind-blowing progress we've had in the last couple of years with LLM technology.
> Using the develop web game skill and preselected, generic follow-up prompts like "fix the bug" or "improve the game", GPT‑5.3-Codex iterated on the games autonomously over millions of tokens.
I wish they would share the full conversation, token counts and more. I'd like to have a better sense of how they normalize these comparisons across version. Is this a 3-prompt 10m token game? a 30-prompt 100m token game? Are both models using similar prompts/token counts?
I vibe coded a small factorio web clone [1] that got pretty far using the models from last summer. I'd love to compare against this.
Thank you. There's a demo save to get the full feel of it quickly. There's also a 2D-ASCII and 3D render you can hotswap between. The 3D models are generated with Meshy. The entire game is 'AI slop'. I intentionally did no code reviews to see where that would get me. Some prompts were very specific but other prompts were just 'add a research of your choice'.
This was built using old versions of Codex, Gemini and Claude. I'll probably work on it more soon to try the latest models.
I've been listening to the insane 100x productivity gains you all are getting with AI and "this new crazy model is a real game changer" for a few years now, I think it's about time I asked:
Can you guys point me ton a single useful, majority LLM-written, preferably reliable, program that solves a non-trivial problem that hasn't been solved before a bunch of times in publicly available code?
Heh, I agree. There is a vast ocean of dev work that is just "upgrade criticalLib to v2.0" or adding support for a new field from the FE through to the BE.
I can name a few times where I worked on something that you could consider groundbreaking (for some values of groundbreaking), and even that was usually more the combination of small pieces of work or existing ideas.
As maybe a more poignant example- I used to do a lot of on-campus recruiting when I worked in HFT, and I think I disappointed a lot of people when I told them my day to day was pretty mundane and consisted of banging out Jiras, usually to support new exchanges, and/or securities we hadn't traded previously. 3% excitement, 97% unit tests and covering corner cases.
In the 1930s, when electronic calculators were first introduced, there was a widespread belief that accounting as a career was finished. Instead, the opposite became true. Accounting as a profession grew, becoming far more analytical/strategic than it had been previously.
You are correct that these models primarily address problems that have already been solved. However, that has always been the case for the majority of technical challenges. Before LLMs, we would often spend days searching Stack Overflow to find and adapt the right solution.
Another way to look at this is through the lens of problem decomposition as well. If a complex problem is a collection of sub-problems, receiving immediate solutions for those components accelerates the path to the final result.
For example, I was recently struggling with a UI feature where I wanted cards to follow a fan-like arc. I couldn't quite get the implementation right until I gave it to Gemini. It didn't solve the entire problem for me, but it suggested an approach involving polar coordinates and sine/cosine values. I was able to take that foundational logic turn it into a feature I wanted.
Was it a 100x productivity gain? No. But it was easily a 2x gain, because it replaced hours of searching and waiting for a mental breakthrough with immediate direction.
There was also a relevant thread on Hacker News recently regarding "vibe coding":
The developer created a unique game using scroll behavior as the primary input. While the technical aspects of scroll events are certainly "solved" problems, the creative application was novel.
Well, it took opus 4.5 five messages to solve a trivial git problem for me. It hallucinated nonexistent flags three times. Hallucinating nonexistent flags is certainly a novel solution to my git ineptness.
Not to be outdone, chatgpt 5.2 thinking high only needed about 8 iterations to get a mostly-working ffmpeg conversion script for bash. It took another 5 messages to translate it to run in windows, on powershell (models escaping newlines on windows properly will be pretty nuch AGI, as far as I’m concerned).
Why even come to this site if you're so anti-innovation?
Today with LLMs you can literally spend 5 minutes defining what you want to get, press send, go grab a coffee and come back to a working POC of something, in literally any programming language.
This is literally stuff of wonders and magic that redefines how we interface with computers and code. And the only thing you can think of is to ask if it can do something completely novel (that it's so hard to even quantity for humans that we don't have software patents mainly for that reason).
And the same model can also answer you if you ask it about maths, making you an itinerary or a recipe for lasagnas. C'mon now.
I don't think that the user you are responding to is anti-innovation, but rather points out that the usefulness of AI is oversold.
I'm using Copilot for Visual Studio at work. It is useful for me to speed some typing up using the auto-complete. On the other hand in agentic mode it fails to follow simple basic orders, and needs hand-holding to run. This might not be the most bleeding-edge setup, but the discrepancy between how it's sold and how much it actually helps for me is very real.
I want AI that cures cancer and solves climate change. Instead we got AI that lets you plagiarize GPL code, does your homework for you, and roleplay your antisocial horny waifu fantasies.
Can you point me to a human written program an LLM cannot write? And no, just answering with a massively large codebase does not count because this issue is temporary.
> Can you point me to a human written program an LLM cannot write?
Sure:
"The resulting compiler has nearly reached the limits of Opus’s abilities. I tried (hard!) to fix several of the above limitations but wasn’t fully successful. New features and bugfixes frequently broke existing functionality.
As one particularly challenging example, Opus was unable to implement a 16-bit x86 code generator needed to boot into 16-bit real mode. While the compiler can output correct 16-bit x86 via the 66/67 opcode prefixes, the resulting compiled output is over 60kb, far exceeding the 32k code limit enforced by Linux. Instead, Claude simply cheats here and calls out to GCC for this phase (This is only the case for x86. For ARM or RISC-V, Claude’s compiler can compile completely by itself.)"[1]
yea but i feel like we are over the hill on benchmaxxing, many times a model has beaten anthropic on a specific bench, but the 'feel' is that it is still not as good at coding
I've always been fascinated to see significantly more people talking about using Claude than I see people talking about Codex.
I know that's anecdotal, but it just seems Claude is often the default.
I'm sure there are key differences in how they handle coding tasks and maybe Claude is even a little better in some areas.
However, the note I see the most from Claude users is running out of usage.
Coding differences aside, this would be the biggest factor for me using one over the other. After several months on Codex's $20/mo. plan (and some pretty significant usage days), I have only come close to my usage limit once (never fully exceeded it).
That (at least to me) seems to be a much bigger deal than coding nuances.
I only switched to using the terminal based agents in the last week. Prior to this I was pretty much only using it through Cursor and GH Copilot. The Anthropic models when used through GH Copilot were far superior to the codex ones and I didn't really get the hype of Codex. Using them through the CLI though, Codex is much better, IMO.
My guess is that it's potentially that and just momentum from developers who started using CC when it was far superior to Codex has allowed it to become so much more popular. Potentially, it's might be that, as it's more autonomous, it's better for true vibe-coding and it's more popular with the Twitter/LinkedIn wantrepreneur crew which meant it gets a lot of publicity which increases adoption quicker.
Codex is great and I hit the usage once doing multiagent full 5 hour absolute degen session for the nornal workflow alongside never hit it and now x2 useage even and now with the planmode switch back and forth absolute great.
When 2 multi billion giants advertise same day, it is not competition but rather a sign of struggle and survival.
With all the power of the "best artificial intelligence" at your disposition, and a lot of capital also all the brilliant minds, THIS IS WHAT YOU COULD COME UP WITH?
What's funny is that most of this "progress" is new datasets + post-training shaping the model's behavior (instruction + preference tuning). There is no moat besides that.
"post-training shaping the models behavior" it seems from your wording that you find it not that dramatic. I rather find the fact that RL on novel environments providing steady improvements after base-model an incredibly bullish signal on future AI improvements. I also believe that the capability increase are transferring to other domains (or at least covers enough domains) that it represents a real rise in intelligence in the human sense (when measured in capabilities - not necessarily innate learning ability)
The behind the scenes on deciding when to release these models has got to be pretty insanely stressful if they're coming out within 30 minutes-ish of each other.
I wonder if their "5.3" was continuously being updated, with regenerated benchmarks with each improvement, and they just stayed ready to release it when claude released
This seems plausible. It would be shocking if these companies didn't have an automated testing suite which is recomputing these benchmarks on a regular basis, and uploading to a dashboard for supervision.
Given that they already pre-approved various language and marketing materials beforehand there's no real reason they couldn't just leave it lined up with a function call to go live once the key players make the call.
Could be, could also be situations where things are lined up to launch in the near future and then a mad dash happens upon receiving outside news of another launch happening.
I suppose coincidences happen too but that just seems too unlikely to believe honestly. Some sort of knowledge leakage does seem like the most likely reason.
No. AI does not work well enough, you still need a person to look on it and CODE. It probably never will, until AGI which probably also in my opinion will never come.
Or the same number of tokens in less time. Kinda feels like the CPU / modem wars of the 90s all over again - I remember those differences you felt going from a 386 -> 486 or from a 2400 -> 9600 baud modem.
We're in the 2400 baud era for coding agents and I for one look forward to the 56k era around the corner ;)
GPT-5.3-Codex dominates terminal coding with a roughly 12% lead (Terminal-Bench 2.0), while Opus 4.6 retains the edge in general computer use by 8% (OSWorld).
Anyone knows the difference between OSWorld vs OSWorld Verified?
OSWorld is the full 369-task benchmark. OSWorld Verified is a ~200-task subset where humans have confirmed the eval scripts reliably score success/failure — the full set has some noisy grading where correct actions can still get marked wrong.
Scores on Verified tend to run higher, so they're not directly comparable.
The notes explicitly call out you may want to dial the effort setting back to medium to reduce latency/tokens (high being default, apparently there is a max setting too).
Specifically this paragraph is what I find hilarious.
> According to the report, the issue became apparent in OpenAI’s Codex, an AI code-generation tool. OpenAI staff reportedly attributed some of Codex’s performance limitations to Nvidia’s GPU-based hardware.
I never really used Codex (found it to slow) just 5.2, which I going to be an excellent model for my work. This looks like another step up.
This week, I'm all local though, playing with opencode and running qwen3 coder next on my little spark machine. With the way these local models are progressing, I might move all my llm work locally.
Doesn't feel like a useful data point without more context. For some hard bugs I'd be thrilled to wait 30 minutes for a fix, for a trivial CSS fix not so much. I've spent weeks+ of my career fix single bugs. Context is everything.
It's so difficult to compare these models because they're not running the same set of evals. I think literally the only eval variant that was reported for both Opus 4.6 and GPT-5.3-Codex is Terminal-Bench 2.0, with Opus 4.6 at 65.4% and GPT-5.3-Codex at 77.3%. None of the other evals were identical, so the numbers for them are not comparable.
Isn't the best eval the one you build yourself, for your own use cases and value production?
I encourage people to try. You can even timebox it and come up with some simple things that might look initially insufficient but that discomfort is actually a sign that there's something there. Very similar to moving from not having unit/integration tests for design or regression and starting to have them.
I also wasn't that familiar with it, but the Opus 4.6 announcement leaned pretty heavily on the TerminalBench 2.0 score to quantify how much of an improvement it was for coding, so it looks pretty bad for Anthropic that OpenAI beat them on that specific benchmark so soundly.
Looking at the Opus model card I see that they also have by far the highest score for a single model on ARC-AGI-2. I wonder why they didn't advertise that.
I find it very, very interesting how they demoed visuals in the form of the “soft SaaS” website and mentioned how it can do user research. Codex has usually lagged behind Claude and Gemini when it comes to UX, so I’m curious to see if 5.3 will take the lead in real world use. Perhaps it’ll be available in Figma Make now?
May I at least understand what it has "written". AI help is good but don't replace real programmers completely. I'm enough copy pasting code i don't understand. What if one day AI will fall down and there will be no real programmers to write the software. AI for help is good but I don't want AI to write whole files into my project. Then something may broke and I won't know what's broken. I've experienced it many times already. Told the AI to write something for me. The code was not working at all. It was compiling normally but the program was bugged. Or when I was making some bigger project with ChatGPT only, it was mostly working but after a longer time when I was promting more and more things, everything got broken.
I've tried that too but it was almost the same, chatgpt kept forgetting many things about the code and project structure.
In summary AI can get problematic for me and i get with troubles with it.
This is like one of the reasons why I still prefer traditional text editor for writing code like Vim over a "software on steroids" like VS Code and things like that...
> What if one day AI will fall down and there will be no real programmers to write the software.
What if you want to write something very complex now that most people don't understand? You keep offering more money until someone takes the time to learn it and accomplish it, or you give up.
I mean, there are still people that hammer out horseshoes over a hot fire. You can get anything you're willing to pay money for.
I'm afraid of all of the modern world especially in technology, I guess if now I would "come back" to all of modern and new things: the commercialized world, AI, corporations, etc...my head would explode. I mean I can't imagine living in such world. I am not sure if everything would be alright eith myself in all this everything,This is just too much...
Having used codex a fair bit I find it really struggles with … almost anything. However using the equivalent chat gpt model is fantastic. I guess it’s a matter of focus and being provided with a smaller set of code to tackle.
OpenAI has a whole history of trying to scoop other providers. This was a whole thing for Google launches, where OpenAI regularly launched something just before Google to grab the media attention.
GPT-4o vs. Google I/O (May 2024): OpenAI scheduled its "Spring Update" exactly 24 hours before Google’s biggest event of the year, Google I/O. They launched GPT-4o voice mode.
Sora vs. Gemini 1.5 Pro (Feb 2024): Just two hours after Google announced its breakthrough Gemini 1.5 Pro model, Sam Altman tweeted the reveal of Sora (text-to-video).
ChatGPT Enterprise vs. Google Cloud Next (Aug 2023): As Google began its major conference focused on selling AI to businesses, OpenAI announced ChatGPT Enterprise.
You can also use via Opencode Zen, Github Copilot, or probably any number of other model providers that Opencode integrates with.
Not sure why everyone stays focused on getting it from Anthropic or OpenAI directly when there are so many places to get access to these models and many others for the same or less money.
OpenAI models in general, yes - `opencode auth login`, select OpenAI, then ChatGPT Pro/Plus. I just checked and 5.3-codex isn't available in opencode yet, but I assume it will be soon.
I've tried opus 4.5 in opencode via the GitHub Copilot API, mostly to see if it works all. I don't think that broke any terms of service? But also I haven't checked how much more expensive I made it for myself over just calling them directly.
I am on a max subscription for Claude, and hate the fact that OpenAI have not figured out that $20 => $200 is a big jump. Good luck to them. In terms of model, just last night, Codex 5.2 solved a problem for me which other models were going round and round. Almost same instructions. That said, I still plan to be on $100 Claude (overall value across many tasks, ability to create docs, co-work), and may bump up OpenAI subscription to the next tier should they decide to introduce one. Not going to $200 even with 5.3, unless my company pays for it.
You should look into Kilo Pass by Kilo Code (https://kilo.ai/features/kilo-pass). It's basically a fixed subscription and your credits roll over each month, and you get free extra credits too which are used up first before paid credits. It's similar to paying for Cursor except the credits roll over which is why I'm contemplating moving to it, because I don't want to be locked into any one LLM provider the way Claude Code or Codex make you become.
I'm coding about 6-9h per day with Codex CLI on the $20 Plus sub, occasionally switching to extra-high reasoning and feeding it massive contexts, all tools enabled, sometimes 2-3 terminal sessions running in parallel and I've never hit limits... I operate on small-ish codebases but even so I try to work in the most local scope possible with AGENTS.md at the sub-directory levels.
Are you really hitting limits, or are you turned off by the fact you think you will?
You are correct :-) I am turned off by the fact that I will hit the limit if I used more. But you gave me confidence. I guess $20 can go a long way. I think only once in the last 3 months I got rate limited in Codex.
Yeah, Claude Code is what everyone is talking about these days and since OpenAI has always been the spending driver being 2nd or 3rd fiddle just isn't acceptable if they're gonna justify it.
I agree, I was confused about where 5.3 non Codex was. 5.2-Codex disappointed me enough that I won't be giving 5.3 Codex a try, but I'm looking forward to trying 5.3 non Codex with Pi.
GPT-5.x in general are very disappointing, the only good chat model was GPT-5 in the first week before they made "the personality warmer" and Codex in general was always kinda meh.
I know we just got a reset and a 2× bump with the native app release, but shipping 5.3 with no reset feels mismatched. If I’d known this was coming, I wouldn’t have used up the quota on the previous model.
Whats interesting to me is that these gpt-5.3 and opus-4.6 are diverging philosophically and really in the same way that actual engineers and orgs have diverged philosophically
With Codex (5.3), the framing is an interactive collaborator: you steer it mid-execution, stay in the loop, course-correct as it works.
With Opus 4.6, the emphasis is the opposite: a more autonomous, agentic, thoughtful system that plans deeply, runs longer, and asks less of the human.
that feels like a reflection of a real split in how people think llm-based coding should work...
some want tight human-in-the-loop control and others want to delegate whole chunks of work and review the result
Interested to see if we eventually see models optimize for those two philosophies and 3rd, 4th, 5th philosophies that will emerge in the coming years.
Maybe it will be less about benchmarks and more about different ideas of what working-with-ai means
> With Codex (5.3), the framing is an interactive collaborator: you steer it mid-execution, stay in the loop, course-correct as it works.
> With Opus 4.6, the emphasis is the opposite: a more autonomous, agentic, thoughtful system that plans deeply, runs longer, and asks less of the human.
Ain't the UX is the exact opposite? Codex thinks much longer before gives you back the answer.
Yes, you’re right for 4.5 and 5.2. Hence they’re focusing on improving the opposite thing and thus are actually converging.
I've also had the exact opposite experience with tone. Claude Code wants to build with me, and Codex wants to go off on its own for a while before returning with opinions.
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I'm personally 100% convinced (assuming prices stay reasonable) that the Codex approach is here to stay.
Having a human in the loop eliminates all the problems that LLMs have and continously reviewing small'ish chunks of code works really well from my experience.
It saves so much time having Codex do all the plumbing so you can focus on the actual "core" part of a feature.
LLMs still (and I doubt that changes) can't think and generalize. If I tell Codex to implement 3 features he won't stop and find a general solution that unifies them unless explicitly told to. This makes it kinda pointless for the "full autonomy" approach since effecitly code quality and abstractions completely go down the drain over time. That's fine if it's just prototyping or "throwaway" scripts but for bigger codebases where longevity matters it's a dealbreaker.
I'm personally 100% convinced of the opposite, that it's a waste of time to steer them. we know now that agentic loops can converge given the proper framing and self-reflectiveness tools.
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I think it's the opposite. Especially considering Codex started out as a web app that offers very little interactivity: you are supposed to drop a request and let it run automatously in a containerized environment; you can then follow up on it via chat --- no interactive code editing.
Fair I agree that was true of early codex and my perception too.. but today there are two announcements that came out and thats what im referring to.
specifically, the GPT-5.3 post explicitly leans into "interactive collaborator" langauge and steering mid execution
OpenAI post: "Much like a colleague, you can steer and interact with GPT-5.3-Codex while it’s working, without losing context."
OpenAI post: "Instead of waiting for a final output, you can interact in real time—ask questions, discuss approaches, and steer toward the solution"
Claude post: "Claude Opus 4.6 is designed for longer-running, agentic work — planning complex tasks more carefully and executing them with less back-and-forth from the user."
This kind of sounds like both of them stepping into the other’s turf, to simplify a bit.
I haven’t used Codex but use Claude Code, and the way people (before today) described Codex to me was like how you’re describing Opus 4.6
So it sounds like they’re converging toward “both these approaches are useful at different times” potentially? And neither want people who prefer one way of working to be locked to the other’s model.
> With Opus 4.6, the emphasis is the opposite: a more autonomous, agentic, thoughtful system that plans deeply, runs longer, and asks less of the human.
This feels wrong, I can't comment on Codex, but Claude will prompt you and ask you before changing files, even when I run it in dangerous mode on Zed, I can still review all the diffs and undo them, or you know, tell it what to change. If you're worried about it making too many decisions, you can pre-prompt Claude Code (via .claude/instructions.md) and instruct it to always ask follow up questions regarding architectural decisions.
Sometimes I go out of my way to tell Claude DO NOT ASK ME FOR FOLLOW UPS JUST DO THE THING.
yeah I'm mostly just talking about how they're framing it: "Claude Opus 4.6 is designed for longer-running, agentic work — planning complex tasks more carefully and executing them with less back-and-forth from the user"
I guess its also quite interesting that how they are framing these projects are opposite from how people currently perceive them and I guess that may be a conscious choice...
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> With Codex (5.3), the framing is an interactive collaborator: you steer it mid-execution, stay in the loop, course-correct as it works.
This is true, but I find that Codex thinks more than Opus. That's why 5.2 Codex was more reliable than Opus 4.5
Just because you can inject steering doesn't mean they stered away from long running...
Theres hundreds of people who upload Codex 5.2 running for hours unattended and coming back with full commits
I am definitely using Opus as an interactive collaborator that I steer mid-execution, stay in the loop and course correct as it works.
I mean Opus asks a lot if he should run things, and each time you can tell it to change. And if that's not enough you can always press esc to interrupt.
I would love to see a nutritional facts label on how many prompts / % of code / ratio of human involvement needed to use the models to develop their latest models for the various parts of their systems.
I think Anthropic rushed out the release before 10am this morning to avoid having to put in comparisons to GPT-5.3-codex!
The new Opus 4.6 scores 65.4 on Terminal-Bench 2.0, up from 64.7 from GPT-5.2-codex.
GPT-5.3-codex scores 77.3.
I do not trust the AI benchmarks much, they often do not line up with my experience.
That said ... I do think Codex 5.2 was the best coding model for more complex tasks, albeit quite slow.
So very much looking forward to trying out 5.3.
Just some anecdata++ here but I found 5.2 to be really good at code review. So I can have something crunched by cheaper models, reviewed async by codex and then re-prompt with the findings from the review. It finds good things, doesn't flag nits (if prompted not to) and the overall flow is worth it for me. Speed loss doesn't impact this flow that much.
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5.2 Codex became my default coding model. It “feels” smarter than Opus 4.5.
I use 5.2 Codex for the entire task, then ask Opus 4.5 at the end to double check the work. It's nice to have another frontier model's opinion and ask it to spot any potential issues.
Looking forward to trying 5.3.
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Yeah, these benchmarks are bogus.
Every new model overfits to the latest overhyped benchmark.
Someone should take this to a logical extreme and train a tiny model that scores better on a specific benchmark.
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Opus 4.5 still worked better for most of my work, which is generally "weird stuff". A lot of my programming involves concepts that are a bit brain-melting for LLMs, because multiple "99% of the time, assumption X is correct" are reversed for my project. I think Opus does better at not falling into those traps. Excited to try out 5.3
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Another day, another hn thread of "this model changes everything" followed immediately by a reply stating "actually I have the literal opposite experience and find competitor's model is the best" repeated until it's time to start the next day's thread.
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they tested it at xhigh reasoning though, which is probably double the cost of Anthropic's model.
Cost to Run Artificial Analysis Intelligence Index:
GPT-5.2 Codex (xhigh): $3244
Claude Opus 4.5-reasoning: $1485
(and probably similar values for the newer models?)
With $20 gpt plan you can use xhigh no problem. With $20 Claude plan you reach the 5h limit with a single feature.
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A provider's API costs seemingly do not reflect each respective SOTA provider's subscription usage allowances.
Impressive jump for GPT-5.3-codex and crazy to see two top coding models come out on the same day...
Insane! I think this has to be the shortest-lived SOTA for any model so far. Competition is amazing.
In my personal experience the GPT models have always been significantly better than the Claude models for agentic coding, I’m baffled why people think Claude has the edge on programming.
I think for many/most programmers = 'speed + output' and webdev == "great coding".
Not throwing shade anyone's way. I actually do prefer Claude for webdev (even if it does cringe things like generate custom CSS on every page) -- because I hate webdev and Claude designs are always better looking.
But the meat of my code is backend and "hard" and for that Codex is always better, not even a competition. In that domain, I want accuracy and not speed.
Solution, use both as needed!
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GPT 5.2 codex plans well but fucks off a lot, goes in circles (more than opus 4.5) and really just lacks the breadth of integrated knowledge that makes opus feel so powerful.
Opus is the first model I can trust to just do things, and do them right, at least small things. For larger/more complex things I have to keep either model on extremely short leashes. But the difference is enough that I canceled my GPT Pro sub so I could switch to Claude. Maybe 5.3 will change things, but I also cannot continue to ethically support Sam Altman's business.
Did you look at the ARC AGI 2? Codex might be overfit for terminal bench
ARC AGI 2 has a training set that model providers can choose to train on, so really wouldn't recommend using it as a general measure of coding ability.
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Opus was quite useless today. Created lots of globals, statics, forward declarations, hidden implementations in cpp files with no testable interface, erasing types, casting void pointers, I had to fix quite a lot and decouple the entangled mess.
Hopefully performance will pick up after the rollout.
Did you give it any architecture guidance? An architecture skill that it can load to make sure it lays out things according to your taste?
[flagged]
why call him that when "saltman" is right there
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Something that caught my eye from the announcement:
> GPT‑5.3‑Codex is our first model that was instrumental in creating itself. The Codex team used early versions to debug its own training
I'm happy to see the Codex team moving to this kind of dogfooding. I think this was critical for Claude Code to achieve its momentum.
Sounds like the researchers behind https://ai-2027.com/ haven't been too far off so far.
More importantly, this is the early steps of a model self improving itself.
Do we still think we'll have soft take off?
> Do we still think we'll have soft take off?
There's still no evidence we'll have any take off. At least in the "Foom!" sense of LLMs independently improving themselves iteratively to substantial new levels being reliably sustained over many generations.
To be clear, I think LLMs are valuable and will continue to significantly improve. But self-sustaining runaway positive feedback loops delivering exponential improvements resulting in leaps of tangible, real-world utility is a substantially different hypothesis. All the impressive and rapid achievements in LLMs to date can still be true while major elements required for Foom-ish exponential take-off are still missing.
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Exponential growth may look like a very slow increase at first, but it's still exponential growth.
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I'm only saying no to keep optimistic tbh
It feels crazy to just say we might see a fundamental shift in 5 years.
But the current addition to compute and research etc. def goes in this direction I think.
making the specifications is still hard, and checking how well results match against specifications is still hard.
i dont think the model will figure that out on its own, because the human in the loop is the verification method for saying if its doing better or not, and more importantly, defining better
I think the limiting factor is capital, not code. And I doubt GPTX is anymore competent at raising funds than the other, fleshy, snake oilers...
This has already been going on for years. It's just that they were using GPT 4.5 to work on GPT 5. All this announcement mean is that they're confident enough in early GPT 5.3 model output to further refine GPT 5.3 based on initial 5.3. But yes, takeoff will still happen because of this recursive self improvement works, it's just that we're already past the inception point.
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,,GPT‑5.3-Codex is the first model we classify as High capability for cybersecurity-related tasks under our Preparedness Framework , and the first we’ve directly trained to identify software vulnerabilities. While we don’t have definitive evidence it can automate cyber attacks end-to-end, we’re taking a precautionary approach and deploying our most comprehensive cybersecurity safety stack to date. Our mitigations include safety training, automated monitoring, trusted access for advanced capabilities, and enforcement pipelines including threat intelligence.''
While I love Codex and believe it's amazing tool, I believe their preparedness framework is out of date. As it is more and more capable of vibe coding complex apps, it's getting clear that the main security issues will come up by having more and more security critical software vibe coded.
It's great to look at systems written by humans and how well Codex can be used against software written by humans, but it's getting more important to measure the opposite: how well humans (or their own software) are able to infiltrate complex systems written mostly by Codex, and get better on that scale.
In simpler terms: Codex should write secure software by default.
Is "high-capability" a stronger or weaker claim than "team of phd-level experts"?
https://www.nbcnews.com/tech/tech-news/openai-releases-chatg...
That’s just classical OpenAI trying to make us believe they’re closing on AGI… Like all « so called » research from them and Anthropic about safety alignment and that their tech is so incredibly powerful that guardrails should be put on them.
I heard the other day that every time someone claps another vibe coded project embeds the api keys in the webpage.
I wonder if this will continue to be the case.
>Our mitigations include safety training, automated monitoring, trusted access for advanced capabilities, and enforcement pipelines including threat intelligence.
"We added some more ACLs and updated our regex"
I remember when AI labs coordinated so they didn't push major announcements on the same day to avoid cannibalizing each other. Now we have AI labs pushing major announcements within 30 minutes.
The labs have fully embraced the cutthroat competition, the arms race has fully shed the civilized facade of beneficient mutual cooperation.
Dirty tricks and underhanded tactics will happen - I think Demis isn't savvy in this domain, but might end up stomping out the competition on pure performance.
Elon, Sam, and Dario know how to fight ugly and do the nasty political boardroom crap. 26 is gonna be a very dramatic year, lots of cinematic potential for the eventual AI biopics.
>civilized facade of mutual cooperation
>Dirty tricks and underhanded tactics
As long the tactics are legal ( i.e. not corporate espionage, bribes etc), the no holds barred full free market competition is the best thing for the market and the consumers.
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They're also coordinating around Chinese New Year to compete with new releases of the major open/local models.
Year of the Pelican!
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This goes way back. When OpenAI launched GPT-4 in 2023, both Anthropic and Google lined up counter launches (Claude and Magic Wand) right before OpenAI's standard 10am launch time.
The thrill of competition
Wouldn't that be illegal ? i.e. cartel to collude like that ?
A sign of the inevitible implosion !
I wish they’d just stop pretending to care about safety, other than a few researchers at the top they care about safety only as long as they aren’t losing ground to the competition. Game theory guarantees the AI labs will do what it takes to ensure survival. Only regulation can enforce the limits, self policing won’t work when money is involved.
The last thing I would want is for excessively neurotic bureaucrats to interfere with all the mind-blowing progress we've had in the last couple of years with LLM technology.
As long as China continues to blitz forward, regulation is a direct path to losing.
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> Using the develop web game skill and preselected, generic follow-up prompts like "fix the bug" or "improve the game", GPT‑5.3-Codex iterated on the games autonomously over millions of tokens.
I wish they would share the full conversation, token counts and more. I'd like to have a better sense of how they normalize these comparisons across version. Is this a 3-prompt 10m token game? a 30-prompt 100m token game? Are both models using similar prompts/token counts?
I vibe coded a small factorio web clone [1] that got pretty far using the models from last summer. I'd love to compare against this.
[1] https://factory-gpt.vercel.app/
I just wanted to say that's a pretty cool demo! I hadn't realised people were using it for things like this.
Thank you. There's a demo save to get the full feel of it quickly. There's also a 2D-ASCII and 3D render you can hotswap between. The 3D models are generated with Meshy. The entire game is 'AI slop'. I intentionally did no code reviews to see where that would get me. Some prompts were very specific but other prompts were just 'add a research of your choice'.
This was built using old versions of Codex, Gemini and Claude. I'll probably work on it more soon to try the latest models.
I've been listening to the insane 100x productivity gains you all are getting with AI and "this new crazy model is a real game changer" for a few years now, I think it's about time I asked:
Can you guys point me ton a single useful, majority LLM-written, preferably reliable, program that solves a non-trivial problem that hasn't been solved before a bunch of times in publicly available code?
> that hasn't been solved before a bunch of times in publicly available code?
And this matters because? Most devs are not working on novel never before seen problems.
Heh, I agree. There is a vast ocean of dev work that is just "upgrade criticalLib to v2.0" or adding support for a new field from the FE through to the BE.
I can name a few times where I worked on something that you could consider groundbreaking (for some values of groundbreaking), and even that was usually more the combination of small pieces of work or existing ideas.
As maybe a more poignant example- I used to do a lot of on-campus recruiting when I worked in HFT, and I think I disappointed a lot of people when I told them my day to day was pretty mundane and consisted of banging out Jiras, usually to support new exchanges, and/or securities we hadn't traded previously. 3% excitement, 97% unit tests and covering corner cases.
In the 1930s, when electronic calculators were first introduced, there was a widespread belief that accounting as a career was finished. Instead, the opposite became true. Accounting as a profession grew, becoming far more analytical/strategic than it had been previously.
You are correct that these models primarily address problems that have already been solved. However, that has always been the case for the majority of technical challenges. Before LLMs, we would often spend days searching Stack Overflow to find and adapt the right solution.
Another way to look at this is through the lens of problem decomposition as well. If a complex problem is a collection of sub-problems, receiving immediate solutions for those components accelerates the path to the final result.
For example, I was recently struggling with a UI feature where I wanted cards to follow a fan-like arc. I couldn't quite get the implementation right until I gave it to Gemini. It didn't solve the entire problem for me, but it suggested an approach involving polar coordinates and sine/cosine values. I was able to take that foundational logic turn it into a feature I wanted.
Was it a 100x productivity gain? No. But it was easily a 2x gain, because it replaced hours of searching and waiting for a mental breakthrough with immediate direction.
There was also a relevant thread on Hacker News recently regarding "vibe coding":
https://news.ycombinator.com/item?id=45205232
The developer created a unique game using scroll behavior as the primary input. While the technical aspects of scroll events are certainly "solved" problems, the creative application was novel.
The story you're describing doesn't seem much better than one could get from googling around and going on stackoverflow
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Yeah, I would LOVE to see attempts at significant video games that are then open-sourced for communities to work on. E.g. OpenGTA or OpenFIFA/OpenNHL.
Well, it took opus 4.5 five messages to solve a trivial git problem for me. It hallucinated nonexistent flags three times. Hallucinating nonexistent flags is certainly a novel solution to my git ineptness.
Not to be outdone, chatgpt 5.2 thinking high only needed about 8 iterations to get a mostly-working ffmpeg conversion script for bash. It took another 5 messages to translate it to run in windows, on powershell (models escaping newlines on windows properly will be pretty nuch AGI, as far as I’m concerned).
Why even come to this site if you're so anti-innovation?
Today with LLMs you can literally spend 5 minutes defining what you want to get, press send, go grab a coffee and come back to a working POC of something, in literally any programming language.
This is literally stuff of wonders and magic that redefines how we interface with computers and code. And the only thing you can think of is to ask if it can do something completely novel (that it's so hard to even quantity for humans that we don't have software patents mainly for that reason).
And the same model can also answer you if you ask it about maths, making you an itinerary or a recipe for lasagnas. C'mon now.
I don't think that the user you are responding to is anti-innovation, but rather points out that the usefulness of AI is oversold.
I'm using Copilot for Visual Studio at work. It is useful for me to speed some typing up using the auto-complete. On the other hand in agentic mode it fails to follow simple basic orders, and needs hand-holding to run. This might not be the most bleeding-edge setup, but the discrepancy between how it's sold and how much it actually helps for me is very real.
There are different kinds of innovation.
I want AI that cures cancer and solves climate change. Instead we got AI that lets you plagiarize GPL code, does your homework for you, and roleplay your antisocial horny waifu fantasies.
Can you point me to a human written program an LLM cannot write? And no, just answering with a massively large codebase does not count because this issue is temporary.
Some people just hate progress.
> Can you point me to a human written program an LLM cannot write?
Sure:
"The resulting compiler has nearly reached the limits of Opus’s abilities. I tried (hard!) to fix several of the above limitations but wasn’t fully successful. New features and bugfixes frequently broke existing functionality.
As one particularly challenging example, Opus was unable to implement a 16-bit x86 code generator needed to boot into 16-bit real mode. While the compiler can output correct 16-bit x86 via the 66/67 opcode prefixes, the resulting compiled output is over 60kb, far exceeding the 32k code limit enforced by Linux. Instead, Claude simply cheats here and calls out to GCC for this phase (This is only the case for x86. For ARM or RISC-V, Claude’s compiler can compile completely by itself.)"[1]
1. https://www.anthropic.com/engineering/building-c-compiler
Pretty much any software that people pay for? If LLMs could clone an app, why would anyone still pay good money for the original?
Even a normal website like landonorris.com. Try copying all those effects with AI.
Another example: Red Dead Redemption 2
Another one: Roller coaster tycoon
Another one: ShaderToy
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And some people clearly hate humans.
Great question, here is the link from the future:
Terminal Bench 2.0
yea but i feel like we are over the hill on benchmaxxing, many times a model has beaten anthropic on a specific bench, but the 'feel' is that it is still not as good at coding
When Anthropic beats Benchmarks its somehow earned, when OpenAi games it, its somehow about not feeling good at coding.
'feel' is no more accurate
not saying there's a better way but both suck
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Your feeling is not my feeling, codex is unambiguously smarter model for me
Benchmarks are useless compared to real world performance.
Real world performance for these models is a disappoint.
I've always been fascinated to see significantly more people talking about using Claude than I see people talking about Codex.
I know that's anecdotal, but it just seems Claude is often the default.
I'm sure there are key differences in how they handle coding tasks and maybe Claude is even a little better in some areas.
However, the note I see the most from Claude users is running out of usage.
Coding differences aside, this would be the biggest factor for me using one over the other. After several months on Codex's $20/mo. plan (and some pretty significant usage days), I have only come close to my usage limit once (never fully exceeded it).
That (at least to me) seems to be a much bigger deal than coding nuances.
I only switched to using the terminal based agents in the last week. Prior to this I was pretty much only using it through Cursor and GH Copilot. The Anthropic models when used through GH Copilot were far superior to the codex ones and I didn't really get the hype of Codex. Using them through the CLI though, Codex is much better, IMO.
My guess is that it's potentially that and just momentum from developers who started using CC when it was far superior to Codex has allowed it to become so much more popular. Potentially, it's might be that, as it's more autonomous, it's better for true vibe-coding and it's more popular with the Twitter/LinkedIn wantrepreneur crew which meant it gets a lot of publicity which increases adoption quicker.
I'm with you. Codex's plans seems to be a much more generous offering than Claude
I just.. can't tell a different in quality between them.. so I go for the cheapest
Codex is great and I hit the usage once doing multiagent full 5 hour absolute degen session for the nornal workflow alongside never hit it and now x2 useage even and now with the planmode switch back and forth absolute great.
When 2 multi billion giants advertise same day, it is not competition but rather a sign of struggle and survival. With all the power of the "best artificial intelligence" at your disposition, and a lot of capital also all the brilliant minds, THIS IS WHAT YOU COULD COME UP WITH?
Interesting
Yeah they are both fighting for survival. No surprise really.
Need to keep the hype going if they are both IPO'ing later this year.
The AI market is an infinite sum market.
Consider the fact that 7 year old TPUs are still sitting at near 100p utilization today.
How many IPOs can a company really do?
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What happened to you?
AI fried brains, unfortunately.
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What's funny is that most of this "progress" is new datasets + post-training shaping the model's behavior (instruction + preference tuning). There is no moat besides that.
"post-training shaping the models behavior" it seems from your wording that you find it not that dramatic. I rather find the fact that RL on novel environments providing steady improvements after base-model an incredibly bullish signal on future AI improvements. I also believe that the capability increase are transferring to other domains (or at least covers enough domains) that it represents a real rise in intelligence in the human sense (when measured in capabilities - not necessarily innate learning ability)
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>There is no moat besides that.
Compute.
Google didn't announce $185 billion in capex to do cataloguing and flash cards.
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AI designed websites are so easy to spot that I need to actively design my UI so that it doesn't look AI
The behind the scenes on deciding when to release these models has got to be pretty insanely stressful if they're coming out within 30 minutes-ish of each other.
I wonder if their "5.3" was continuously being updated, with regenerated benchmarks with each improvement, and they just stayed ready to release it when claude released
This seems plausible. It would be shocking if these companies didn't have an automated testing suite which is recomputing these benchmarks on a regular basis, and uploading to a dashboard for supervision.
Given that they already pre-approved various language and marketing materials beforehand there's no real reason they couldn't just leave it lined up with a function call to go live once the key players make the call.
It’s also functionally not likely without some sort of insider knowledge or coordination
Could be, could also be situations where things are lined up to launch in the near future and then a mad dash happens upon receiving outside news of another launch happening.
I suppose coincidences happen too but that just seems too unlikely to believe honestly. Some sort of knowledge leakage does seem like the most likely reason.
Do software engineers here feel threatened by this? I certainly am. I'm surprised that this topic is almost entirely missing in these threads.
No. AI does not work well enough, you still need a person to look on it and CODE. It probably never will, until AGI which probably also in my opinion will never come.
AI is mostly garbage at creating useful abstractions. I'd feel threatened if I was a competitive programmer or IMO kid
I would feel threatened if I didn't invest in learning how to best use AI
Jevons paradox hints that the situation is not as bleak as it sounds.
Both Opus 4.6 and GPT-5.3 one shot a Gameboy emulator for me. Guess I need a better benchmark.
As coding agents get "good enough" the next differentiator will be which one can complete a task in fewer tokens.
Or quicker, or more comprehensively for the same price.
Or the same number of tokens in less time. Kinda feels like the CPU / modem wars of the 90s all over again - I remember those differences you felt going from a 386 -> 486 or from a 2400 -> 9600 baud modem.
We're in the 2400 baud era for coding agents and I for one look forward to the 56k era around the corner ;)
> our team was blown away > by how much Codex was able > to accelerate its own development
they forgot to add “Can’t wait to see what you do with it”
I want to recompile a Rust project to be f32 instead of f64.
Am I better off buying 1 month of Codex, Claude, or Antigravity?
I want to have the agent continuesly recompile and fix compile errors on loop until all the bugs from switching to f32 are gone.
Literally just find and replace
Doesn't matter which one. All of them can do things like this now, given a good enough feedback loop. Which your problem has.
All of them can do it but Codex has the least frustrating usage limits.
For those who cared:
GPT-5.3-Codex dominates terminal coding with a roughly 12% lead (Terminal-Bench 2.0), while Opus 4.6 retains the edge in general computer use by 8% (OSWorld).
Anyone knows the difference between OSWorld vs OSWorld Verified?
From Claude 4.6 Thinking:
OSWorld is the full 369-task benchmark. OSWorld Verified is a ~200-task subset where humans have confirmed the eval scripts reliably score success/failure — the full set has some noisy grading where correct actions can still get marked wrong.
Scores on Verified tend to run higher, so they're not directly comparable.
Using opus 4.6 in claude code right now. It's taking about 5x longer to think things through, if not more.
The notes explicitly call out you may want to dial the effort setting back to medium to reduce latency/tokens (high being default, apparently there is a max setting too).
> GPT‑5.3-Codex was co-designed for, trained with, and served on NVIDIA GB200 NVL72 systems. We are grateful to NVIDIA for their partnership.
This is hilarious lol
How so?
They're on shaky ground right now https://arstechnica.com/information-technology/2026/02/five-...
Its kind of a suck up that more or less confirms the beef stories that were floating around this past week.
In case you missed it. For example:
Nvidia's $100 billion OpenAI deal has seemingly vanished - Ars Technica
https://arstechnica.com/information-technology/2026/02/five-...
Specifically this paragraph is what I find hilarious.
> According to the report, the issue became apparent in OpenAI’s Codex, an AI code-generation tool. OpenAI staff reportedly attributed some of Codex’s performance limitations to Nvidia’s GPU-based hardware.
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Did they post the knowledge cutoff date somewhere
Model card: https://cdn.openai.com/pdf/23eca107-a9b1-4d2c-b156-7deb4fbc6...
is so fun that the two releases used almost completely non-overlapping benchmarks!
Interesting that this was released without a prior GPT-5.3 release. I wonder if that means we won't see a GPT-5.3?
I'm having a hard time parsing the openai website.
Anyone know if it is possible to use this model with opencode with the plus subscription?
I think models are smart enough for most of the stuff, these little incremental changes barely matter now. What I want is the model that is fast.
Gotta love how the game demo's page title is "threejs" – I guess the point was to demo its vibe-coding abilities anyway, but yea..
I never really used Codex (found it to slow) just 5.2, which I going to be an excellent model for my work. This looks like another step up.
This week, I'm all local though, playing with opencode and running qwen3 coder next on my little spark machine. With the way these local models are progressing, I might move all my llm work locally.
I think codex got much faster for smaller tasks in the last few months. Especially if you turn thinking down to medium.
I think the slow feeling is a UI thing in codex
Anthropic mostly had an advantage in speed. It feels like with a 25% increase in speed with Codex 5.3, they are now losing that advantage as well.
I just asked Opus 4.6 to debug a bug in my current changes and it went for 20 minutes before I interrupted it. Take that as you will.
Doesn't feel like a useful data point without more context. For some hard bugs I'd be thrilled to wait 30 minutes for a fix, for a trivial CSS fix not so much. I've spent weeks+ of my career fix single bugs. Context is everything.
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It's so difficult to compare these models because they're not running the same set of evals. I think literally the only eval variant that was reported for both Opus 4.6 and GPT-5.3-Codex is Terminal-Bench 2.0, with Opus 4.6 at 65.4% and GPT-5.3-Codex at 77.3%. None of the other evals were identical, so the numbers for them are not comparable.
Isn't the best eval the one you build yourself, for your own use cases and value production?
I encourage people to try. You can even timebox it and come up with some simple things that might look initially insufficient but that discomfort is actually a sign that there's something there. Very similar to moving from not having unit/integration tests for design or regression and starting to have them.
I usually wait to see what ArtificialAnalysis says for a direct comparison.
It's better on a benchmark I've never heard of!? That is groundbreaking, I'm switching immediately!
I also wasn't that familiar with it, but the Opus 4.6 announcement leaned pretty heavily on the TerminalBench 2.0 score to quantify how much of an improvement it was for coding, so it looks pretty bad for Anthropic that OpenAI beat them on that specific benchmark so soundly.
Looking at the Opus model card I see that they also have by far the highest score for a single model on ARC-AGI-2. I wonder why they didn't advertise that.
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I find it very, very interesting how they demoed visuals in the form of the “soft SaaS” website and mentioned how it can do user research. Codex has usually lagged behind Claude and Gemini when it comes to UX, so I’m curious to see if 5.3 will take the lead in real world use. Perhaps it’ll be available in Figma Make now?
I’m hoping they add better IDE integration to track active file and selection. That’s the biggest annoyance I have in working with Codex.
gpt-5.3-codex isn't available on the API yet. From TFA:
> We are working to safely enable API access soon.
May AI not write the code for me.
May I at least understand what it has "written". AI help is good but don't replace real programmers completely. I'm enough copy pasting code i don't understand. What if one day AI will fall down and there will be no real programmers to write the software. AI for help is good but I don't want AI to write whole files into my project. Then something may broke and I won't know what's broken. I've experienced it many times already. Told the AI to write something for me. The code was not working at all. It was compiling normally but the program was bugged. Or when I was making some bigger project with ChatGPT only, it was mostly working but after a longer time when I was promting more and more things, everything got broken.
Honest question: have you tried evolving your code architecture when adding features instead of just "promting more and more things"?
I've tried that too but it was almost the same, chatgpt kept forgetting many things about the code and project structure. In summary AI can get problematic for me and i get with troubles with it. This is like one of the reasons why I still prefer traditional text editor for writing code like Vim over a "software on steroids" like VS Code and things like that...
> What if one day AI will fall down and there will be no real programmers to write the software.
What if you want to write something very complex now that most people don't understand? You keep offering more money until someone takes the time to learn it and accomplish it, or you give up.
I mean, there are still people that hammer out horseshoes over a hot fire. You can get anything you're willing to pay money for.
Sorry but companies will not hire you but instead a person who learned how to code with AI. Get with the times or lose.
I'm afraid of all of the modern world especially in technology, I guess if now I would "come back" to all of modern and new things: the commercialized world, AI, corporations, etc...my head would explode. I mean I can't imagine living in such world. I am not sure if everything would be alright eith myself in all this everything,This is just too much...
It's that Austin Powers clip of the guy slowly getting smooshed by the steam roller.
GPT-5.2-Codex was so cool at price/value rate, hope 5.3 will not ruin the race with claude
Having used codex a fair bit I find it really struggles with … almost anything. However using the equivalent chat gpt model is fantastic. I guess it’s a matter of focus and being provided with a smaller set of code to tackle.
That was fast!
I really do wonder whats the chain here. Did Sam see the Opus announcement and DM someone a minute later?
OpenAI has a whole history of trying to scoop other providers. This was a whole thing for Google launches, where OpenAI regularly launched something just before Google to grab the media attention.
Some recent examples:
GPT-4o vs. Google I/O (May 2024): OpenAI scheduled its "Spring Update" exactly 24 hours before Google’s biggest event of the year, Google I/O. They launched GPT-4o voice mode.
Sora vs. Gemini 1.5 Pro (Feb 2024): Just two hours after Google announced its breakthrough Gemini 1.5 Pro model, Sam Altman tweeted the reveal of Sora (text-to-video).
ChatGPT Enterprise vs. Google Cloud Next (Aug 2023): As Google began its major conference focused on selling AI to businesses, OpenAI announced ChatGPT Enterprise.
I assume some sort of corporate espionage. This is high stakes after all
Tell me that you are hurt without telling me that you are hurt this applies to Sam right now
Anyone remember the dot-com era when you would see one provider claim the most miles of fibre and then later that week another would have the title?
Funny that this and Opus 4.6 released within minutes of each other. Each showing similar score improvements. Each claiming to be revolutionary.
I've been using 5.2 the way they're describing the new use case for 5.3 this whole time.
How'd they both release at the same time? Insiders?
According to Sam Altman, Anthropic is for "rich people." Judging by his $4 million man-baby Koeniggsegg, he must be a huge Claude Code user!
At first try it solved a problem that 5.2 couldn't previously.
Seems to be slower/thinks longer.
Does it insert adverts in your code?
The most important question: Can it do Svelte now?
Today is the best day to rewrite everything in React. You may not enjoy React, but AI agents do. And they are the ones writing the code.
5.2 was already very good with svelte 5, at least when you have the svelte MCP server set up.
Where is the google?
gemini-3-flash-preview will be GA soon i hope. /s
So can I use this from Opencode? Because Anthropic started to enforce their TOS to kill the Opencode integration
You can also use via Opencode Zen, Github Copilot, or probably any number of other model providers that Opencode integrates with.
Not sure why everyone stays focused on getting it from Anthropic or OpenAI directly when there are so many places to get access to these models and many others for the same or less money.
OpenAI models in general, yes - `opencode auth login`, select OpenAI, then ChatGPT Pro/Plus. I just checked and 5.3-codex isn't available in opencode yet, but I assume it will be soon.
I've tried opus 4.5 in opencode via the GitHub Copilot API, mostly to see if it works all. I don't think that broke any terms of service? But also I haven't checked how much more expensive I made it for myself over just calling them directly.
You can use Anthropic models in Opencode, make an api key and you're good to do(you can even use the in house Opencode router, Zen).
What you can't do is pretend opencode is claude code to make use of that specific claude code subscription.
Yes, OpenAI said they'd allow usage of their subscriptions in opencode.
Any notes on pricing?
It's not in the API yet - "We are working to safely enable API access soon.", but I assume the rate-limits won't be worse than for 5.2 Codex.
Ah, "It's ready, but not yet".
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I am on a max subscription for Claude, and hate the fact that OpenAI have not figured out that $20 => $200 is a big jump. Good luck to them. In terms of model, just last night, Codex 5.2 solved a problem for me which other models were going round and round. Almost same instructions. That said, I still plan to be on $100 Claude (overall value across many tasks, ability to create docs, co-work), and may bump up OpenAI subscription to the next tier should they decide to introduce one. Not going to $200 even with 5.3, unless my company pays for it.
You should look into Kilo Pass by Kilo Code (https://kilo.ai/features/kilo-pass). It's basically a fixed subscription and your credits roll over each month, and you get free extra credits too which are used up first before paid credits. It's similar to paying for Cursor except the credits roll over which is why I'm contemplating moving to it, because I don't want to be locked into any one LLM provider the way Claude Code or Codex make you become.
I'm coding about 6-9h per day with Codex CLI on the $20 Plus sub, occasionally switching to extra-high reasoning and feeding it massive contexts, all tools enabled, sometimes 2-3 terminal sessions running in parallel and I've never hit limits... I operate on small-ish codebases but even so I try to work in the most local scope possible with AGENTS.md at the sub-directory levels.
Are you really hitting limits, or are you turned off by the fact you think you will?
You are correct :-) I am turned off by the fact that I will hit the limit if I used more. But you gave me confidence. I guess $20 can go a long way. I think only once in the last 3 months I got rate limited in Codex.
I use Codex in OpenCode through the API and find the experience quite enjoyable.
Need to try OpenCode. Thanks.
I guess the jump is on purpose. You can buy Codex credits and also use codex via the API (manual switching required).
Whoa, I think GPT-5.2-Codex was a disappointment, but GPT-5.3-Codex is definitely the future!
It seems Fast!
I'd like to know if and how much illegal use of customer prompts are used for training.
"But we anonymize prompts before training!"
Meanwhile the prompt: Crop this photo of my passport
Oh yeah that’s in the “These Are The Illegal Things We Did” section 7.4 in the Model Card.
what are the benchmarks against opus 4.6?
Anybody else not seeing it available in Codex app or CLI yet (with Plus)?
My codex CLI didn’t notice version bump available, but I manually did pnpm add -g @openai/codex and 5.3 was there after.
Anthropic and GTP 2 new models at once?
Pelican seems much worse than the Opus 4.6 one (though the bicycle is more accurate):
https://gist.github.com/simonw/a6806ce41b4c721e240a4548ecdbe...
It is absurd to release 5.3-Codex before first releasing 5.3.
Also, there is no reason for OpenAI and Anthropic to be trying to one-up each other's releases on the same day. It is hell for the reader.
Because Claude Code is stealing the thunder so OpenAI is focusing on coding now.
Yeah, Claude Code is what everyone is talking about these days and since OpenAI has always been the spending driver being 2nd or 3rd fiddle just isn't acceptable if they're gonna justify it.
That is where the money is.
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Why is it absurd?
I agree, I was confused about where 5.3 non Codex was. 5.2-Codex disappointed me enough that I won't be giving 5.3 Codex a try, but I'm looking forward to trying 5.3 non Codex with Pi.
GPT-5.x in general are very disappointing, the only good chat model was GPT-5 in the first week before they made "the personality warmer" and Codex in general was always kinda meh.
lmao so cringe that they delay releasing the model until anthropic does
Almost like Anthropic and OpenAI are trying to front run each other
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I know we just got a reset and a 2× bump with the native app release, but shipping 5.3 with no reset feels mismatched. If I’d known this was coming, I wouldn’t have used up the quota on the previous model.
Is this me or Sam is being absolute sore loser he is and trying to steal Opus thunder?
Why is it loser? He very well could be a sore winner here.
OpenAI is still the only AI company that has structured outputs. Anthropic now supports JSON schema but you can't specify array length.
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They both are doing this to each other.
BTW, loser is spelled with a single o.
You could also claim that Anthropic is trying to scoop OpenAI by launching minutes earlier, as OpenAI has done with Google in the past.
For downvoters, you must be naive to think these companies are not surveilling each other through various means.