Yes. High value work where cost (mostly) doesn't matter. For example, if I need to look over a legal doc for possible mistakes (part of a workflow i have), it doesn't matter (in my case) whether it costs $0.01 or $10.00, since it's a somewhat infrequent event. So i'll pay $9.99 more, even if the model is only slightly better.
I'm surprised I never heard people talking about using -Pro variants, even though their rates ($125-175/M?) aren't drastically larger than old Opus ($75/M), which people seemed to use
>API deployments require different safeguards and we are working closely with partners and customers on the safety and security requirements for serving it at scale.
And now this. I guess one day counts as "very soon." But I wonder what that meant for these safeguards and security requirements.
The same person who've mercilessly lied about safety is still running the company, so not sure why anyone would expect any different from them moving forward. Previous example:
> In 2023, the company was preparing to release its GPT-4 Turbo model. As Sutskever details in the memos, Altman apparently told Murati that the model didn’t need safety approval, citing the company’s general counsel, Jason Kwon. But when she asked Kwon, over Slack, he replied, “ugh . . . confused where sam got that impression.”
I wonder if the fact that GPT-5.5 was already available in their Codex-specific API which they had explicitly told people they were allowed to use for other purposes - https://simonwillison.net/2026/Apr/23/gpt-5-5/#the-openclaw-... - accelerated this release!
> a lot of doctors are using ChatGPT both to search diagnosis and communicate with non-English speaking patients
I think that's the problem. Who's going to claim responsibility when ChatGPT hallucinates or mistranslates a patient's diagnosis and they die? For OpenAI, this would at best be a PR nightmare, so that's why they have safeguards.
-> You are in China, you go to emergency, nobody speaks your language
Move hands ? DeepSeek is better than using hands, even Baidu Translate, ChatGPT or whatever you find.
Other solutions are theoretically nice on paper but almost delusional.
An imperfect solution is better than no solution.
==
Similarly, a deaf-person is theorically better with a certified interpreter that can talk with the hands, but they may prefer voice-recognition software or AI tools.
(or... talking with hands is more confusing and annoying or less understandable for them).
Of course ChatGPT transcription can have issues, but that's the difference between the real-world and Silicon Valley's disconnected lawyers world.
==
If ChatGPT says: "sorry I won't be able, please go to see a licensed interpreter, good luck!" then it's just OpenAI trying to save their asses, at your risk/expense.
If you have a choice, you can make the choice, and you can double-check what is said. In other cases, you have no choice, nothing to check, only problems but no hints of solutions.
When I registered with my GP in the UK, they asked me whether I would need an interpreter and what language. They then provide professional interpreters.
"what you see is all there is." it's generally much easier to verify something you've been made aware of than it is to know of it in the first place (and still verify it.)
The irony is that licensed interpreters / translators usually perform worse than AI.
Only the liability shifts from OpenAI to them.
Furthermore, where the alternative to a licensed professional was nothing, or a random untrained person or a weak professional, then it's harming the user on the pretext of protecting him.
I was answering for hallucinations, not really for translation. Re-reading your initial post I do agree with what you are saying (i.e. you are explaining why OpenAI is looking to avoid a PR nightmare). What I meant to express is that I would personally trust doctors to use these tools as best they can to provide care.
Adults bear responsibility for choices about their own lives. In fact, the more educated they are, the better choices they can make.
A doctor who gets refused by ChatGPT doesn't stop needing to communicate with the patient; they fall back to a worse option (Google Translate, a family member interpreting, guessing). Refusal isn't safety, it's liability-shifting dressed up as safety.
If there's no doctor, no interpreter, no pharmacist, just a person with a sick kid and a phone, then "refuse and redirect to a professional" is advice from a world that doesn't exist for them. The refusal doesn't send them to a better option; there is no better option, it's a large majority of people on this planet.
Hell is paved of good intentions, but open-education and unlimited access to knowledge is very good.
It doesn't change the human nature of some people, bad people stay bad, good people stay good.
About PR, they're optimizing for not being the named defendant in a lawsuit or the subject of a bad news cycle, it's self-interest wearing benevolence as a costume.
This is because harms from answering are punishable (bad PR, unhappy advertisers, unhappy investors, unhappy politicians / dictators, unhappy lobbies, unhappy army, etc); but harms from refusing are invisible and unpunished.
> A doctor who gets refused by ChatGPT doesn't stop needing to communicate with the patient; they fall back to a worse option
I think AI proves the contrary. There are plenty of examples of things that are getting worse because of technological advancement, particularly AI. Software quality, writing, online discourse, misinformation have all suffered over the last few years. I truly believe the internet is a worse place than it was 5 years ago, and I can't imagine bringing that to medicine would work out differently.
The medical system shouldn't rely on falling back to crappy workarounds, it should aspire to build the best system it reasonably can.
you cant but its pretty reproducible across api and codex and other agents so i just thought it was odd. full text it gives:
Knowledge cutoff: 2024-06
Current date: 2026-04-24
You are an AI assistant accessed via an API.
# Desired oververbosity for the final answer (not analysis): 5
An oververbosity of 1 means the model should respond using only the minimal content necessary to satisfy the request, using
concise phrasing and avoiding extra detail or explanation."
An oververbosity of 10 means the model should provide maximally detailed, thorough responses with context, explanations, and
possibly multiple examples."
The desired oververbosity should be treated only as a *default*. Defer to any user or developer requirements regarding
response length, if present.
That sort of test isn't super reliable either, in my experience.
You're probably better off asking something like "what are the most notable changes in version X of NumPy?" and repeating until you find the version at which it says "I don't know" or hallucinates.
I don't know why this keeps coming up. This has always been the least reliable way to know the cutoff date (and indeed, it may well have been trained on sites with comments like these!)
Just ask it about an event that happened shortly before Dec 1, 2025. Sporting event, preferably.
i wonder if they put an older cutoff date into the prompt intentionally so that when asked on more current events it leans towards tool calls / web searches for tuning
I wonder if the cutoff date is the result of so many people posting about the date over time and poisoning the data. "Dead cutoff date theory," perhaps.
Whatever it is, the cutoff date reporting discrepancy isn't new. Back when Musk was making headlines about buying/not buying Twitter, I was able to find recent-ish related news that was published well after the bot's stated cutoff date.
ChatGPT was not yet browsing/searching/using the web at that point. That tool didn't come for another year or so.
Enterprise user here and still seeing only 5.4.
Yesterday's announcement said that it will take a few hours to roll out to everybody. OpenAI needs better GTM to set the right expectations.
I gave 4.6, 4.7 and GPT 5.5 the same prompt and task to reverse engineer a collection of sample vector files from an obscure Amiga CAD program and create a detailed txt specification and a python converter that converts to SVG and produce a report so I can visually verify.
4.6 did very well. 90% perfect on first try, got to 100% with just a few followups.
4.7 failed horribly. First produced garbage output and claimed it was done, admitted it did that when called out, proceeded to work at it a lot longer and then IT GAVE UP.
GPT 5.5 codex was shockingly good. Achieved 90% perfect on first try in about a fourth of the time. Got to 100% faster and with fewer follow-ups.
Just tried with DeepSeek V4 Pro with OpenCode. It didn't do great. First attempt produced somewhat correct drawings for some of the original samples, but most were just a spaghetti messs of lines. Some prodding got it to do a little better, but still not right. A third prod and it went down a wild rabbit hole and was much worse. I gave up.
I also tried GLM 5.1, it's first attempt was such a disaster I didn't bother working with it any further. It also took by far the longest and wasted a bunch of time/tokens trying to find other converters online (and failing) instead of just reverse engineering the format from the sample files given.
Interesting. I would love your test but for code. If I were to forgo my claude subscription for a Chinese cloud hosted model or local models running on my own hardware I'd use them mostly for code.
the thing is I've tried to come up with a good test my own and spend countless time just tweaking it instead of saying this is good enough and benchmarking.
You need to be more specific. OpenAI's commitment to assist the Trump administration with domestic mass surveillance seems to have been largely memory-holed.
Just tried it out for a prod issue was experiencing. Claude never does this sort of thing, I had it write an update statement after doing some troubleshooting, and I said “okay let’s write this in a transaction with a rollback” and GPT-5.5 gave me the old “okay,
BEGIN TRAN;
-- put the query here
commit;
I feel like I haven’t had to prod a model to actually do what I told it to in awhile so that was a shock. I guess that it does use fewer tokens that way, just annoying when I’m paying for the “cutting edge” model to have it be lazy on me like that.
This is in Cursor the model popped up and so I tried it out from the model selector.
I mean, I was doing triage, so wanted an immediate fix. The actual issue is we’re getting some exploding complexity when double checking the action the API is taking is valid in the data. So that needs to be refactored. I suppose it reduces token usage, but Claude Opus will happily do exactly what I want it to.
I feel like the last 2-3 generations of models (after gpt-5.3-codex) didn't really improve much, just changed stuff around and making different tradeoffs.
I disagree, it improved enormously especially at staying consistent for long-tasks, I have a task running for 32 days (400M+ tokens) via Codex and that's only since gpt-5.4
Oh boy, you are far from what it requires, we are probably talking 3B+, but note that this is just codex, obviously codex is also doing automatic adversarial with the regular zoo (gemini-3.1-pro-preview, opus-4.6/4.7, gpt-5.3-codex, minimax-2.7, glm-5.1, mimo-2 (now 2.5) and so-on, you get the gist) :)
I don't know their margin so I can't really say, but do we have 8 OpenAI accounts, I doubt they are making that much with us seeing that there isn't a single hour where we don't saturate the accounts.
Coding (along with docs, tests obviously), rewriting a huge chunk of the KVM hypervisor (in Kernel 7, started in the -rc2) and KSM and other modules, can't say too much about it yet (might do an announcement in coming weeks). The coding is automated but the plan took days of manual arguing (with all models possible) prior (while doing other things during waiting times as I currently manage 70 repos for an upcoming release of our Beta).
I think users really underestimate the capabilities of "AI" when using the right tooling/combinations of models and procedures (and loops), that's talking with 2 decades of dev behind me, genuinely I'm not on phase with people saying it produces slop of any kind, at this stage, it's mostly the fault of the prompter (or the prompter not having enough tokens to do mass adversarial), but clearly, I can genuinely state that the code produced is overall the SAME quality as I would by being extremely meticulous.
I'm like a bot following 30+ threads concurrently, sometimes it's fun, sometimes it feels like playing casino, sometimes it's boring, but this is truly an insane era if you have the funding for it, obviously we stack many MANY accounts in rotation 24/7, equivalent in API cost by myself is about 100K$+ (a month) but we pay only a fraction of that cost thanks to the plans.
PS: I have 8 monitors in front of me to manage all that (portable monitors stacked together).
I don't think you really grasp the direction the world is taking or even really understand AI capabilities when it's put together to reach high automation, you might not agree or embrace it yet, but you will be joining the loop wagon, soon enough.
can you explain further? Most especially, why do you see AI stopping anytime soon and not getting just insanely better and better for the next decades (that is through combination of models or models alone, harnesses or whatever, that's just a technicality)?
Please do a post about this (though I realize that takes time). This sounds amazing. I have always dreamed of doing this too but just don't have the budget.
I’m vague on a specific reason for this feeling because there are a few to choose from and no one overpowers the other, but the emotion that comes to mind when I read this is disgust. As a society I feel we will look back on the subsidized opulence of this moment with total and utter contempt.
That as well. But everyone reading GP’s posts knows in their bones that it’s unsustainable. It’s economically unsustainable and environmentally unsustainable, and in that context it strikes me as pure hoarding behaviour. Taking as much as they can for themselves before the house of cards crashes down.
I have no sympathy for OpenAI or Anthropic as corporations, but if these are the new tools of the trade, then platform abuse like GP is bragging about serves only to destroy the livelihoods of the rest of us who are content to use our fair share.
There’s no such thing as a free lunch, and the bill always comes at the end.
I mostly hate it because the token crunch is now coming for us regular users because of people like this. A few people always ruin it for the rest of us.
Yea. It’s greed, pure and simple. And also a major misstep on the part of the inference providers to offer these subsidized plans and not anticipate these slop mills.
I know exactly the feeling you mean. I get a much stronger feeling of that when I talk with friends who frequently take a plane for a 250 mile trip which has a world-class comfortable high-speed train connection with very frequent trains, each taking less than 3 hours. I'm sure you have friends who would do this in this situation - do you feel the same disgust when you hear them talking about such choices?
I still haven't seen a single person who actually cares about the environment and has willingly made significant sacrifices for it, who clamors about the environmental cost of AI. Every time I see someone do it it's someone who never cared about this before, and still doesn't really. Who buys plenty of new clothes and furniture, loves a good burger, has the latest iPhone, flies 4 times per year.
Maybe you're the unicorn in which case fair enough, you've earned the right to feel disgusted.
It's just too bad the subsidized costs mean they won't actually feel any real punishment for their failure. Like normally time wasted on its own is enough of a punishment for making a poor decision, but they're not even doing anything themselves here!
I'm also in that boat of not understanding how people fail to get a huge productivity boost from GenAI. And it's not just novices but sometimes seriously accomplished coders. It can't be they're just typing 'Make me an ERP' and then go 'these thing are dumb slop machines' right?
OpenAI is the first company that has reached a level of intelligence so high, the model has finally become smart enough to make YOU do all the work. Emergent behavior in action.
All earnesty aside, OpenAI’s oddly specific singular focus on “intelligence per token” (also in the benchmarks) that literally noone else pushes so hard eerily reminds me of Apple’s Macbook anorexia era pre-M1. One metric to chase at the cost of literally anything else. GPT-5.3+ are some of the smartest models out there and could be a pleasure to work with, if they weren’t lazy bastards to the point of being completely infuriating.
Sorry if I’m not getting it, but what was wrong exactly? Is the issue that it merely put “-- put the query here” in the reply, instead of repeating it again?
If so, I’m not sure I’d even consider that a problem. If the goal is for it to give you a query to run, and you ask it “let’s do it in a transaction”, it’s a reasonable thing for it to simply inform you, “yeah you can just type begin first” since it’s assuming you’re going to be pasting the query in anyway. And yeah, it does use fewer tokens, assuming the query was long. Similar to how, if it gave me a command to run, and I say “I’m getting a permission denied”, it would be reasonable for it to say “yeah do it as root, put sudo before the command”, and it’s IMO reasonable if it didn’t repeat the whole thing verbatim just with the word “sudo” first.
But if the context was that you actually expected it to run the query for you, and instead it just said “here, you run it”, then yeah that’s lazy and I’d understand the shock.
Your benchmark has Opus 4.7 performing significantly worse than Sonnet 4.6. Even if true on your benchmark, that is not representative of the overall performance of the models.
I haven't evaluated the judge benchmark. You have everything needed in the repo to do so though, so be my guest. It took me a bit of time to put all this together and won't have much more time to dedicate to it before a couple of weeks.
BTW, if you explore the repo, sorry for all the French files...
That’s the thing, not everyone wants and values the model based on that. But I guess it works for you, and that benchmark achieves it.
I personally develop with very detailed spec, and I don’t want nothing more and nothing less compared to the spec.
I found 5.4/5.5 much better at following spec while Opus makes some things up, which aligns with your benchmark but that makes 5.4/5.5 better for me while worse for you.
>API deployments require different safeguards and we are working closely with partners and customers on the safety and security requirements for serving it at scale.
And now this. I guess one day counts as "very soon." But I wonder what that meant for these safeguards and security requirements.
> In 2023, the company was preparing to release its GPT-4 Turbo model. As Sutskever details in the memos, Altman apparently told Murati that the model didn’t need safety approval, citing the company’s general counsel, Jason Kwon. But when she asked Kwon, over Slack, he replied, “ugh . . . confused where sam got that impression.”
Lots of cases where Altman hass not been entirely forthcoming about how important (or not) safety is for OpenAI. https://www.newyorker.com/magazine/2026/04/13/sam-altman-may... (https://archive.is/a2vqW)
In my place for example, a lot of doctors are using ChatGPT both to search diagnosis and communicate with non-English speaking patients.
Even yourself, when you want to learn about one disease, about some real-world threats, some statistics, self-defense techniques, etc.
Otherwise it's like blocking Wikipedia for the reason that using that knowledge you can do harmful stuff or read things that may change your mind.
Freedom to read about things is good.
I think that's the problem. Who's going to claim responsibility when ChatGPT hallucinates or mistranslates a patient's diagnosis and they die? For OpenAI, this would at best be a PR nightmare, so that's why they have safeguards.
I had a choice better a doctor that used AI or not, I would much prefer one that did...
-> You are in China, you go to emergency, nobody speaks your language
Move hands ? DeepSeek is better than using hands, even Baidu Translate, ChatGPT or whatever you find.
Other solutions are theoretically nice on paper but almost delusional.
An imperfect solution is better than no solution.
==
Similarly, a deaf-person is theorically better with a certified interpreter that can talk with the hands, but they may prefer voice-recognition software or AI tools.
(or... talking with hands is more confusing and annoying or less understandable for them).
Of course ChatGPT transcription can have issues, but that's the difference between the real-world and Silicon Valley's disconnected lawyers world.
==
If ChatGPT says: "sorry I won't be able, please go to see a licensed interpreter, good luck!" then it's just OpenAI trying to save their asses, at your risk/expense.
If you have a choice, you can make the choice, and you can double-check what is said. In other cases, you have no choice, nothing to check, only problems but no hints of solutions.
This is why openness is important.
https://www.england.nhs.uk/interpreting/
Only the liability shifts from OpenAI to them.
Furthermore, where the alternative to a licensed professional was nothing, or a random untrained person or a weak professional, then it's harming the user on the pretext of protecting him.
(like in the other mentioned contexts).
A doctor who gets refused by ChatGPT doesn't stop needing to communicate with the patient; they fall back to a worse option (Google Translate, a family member interpreting, guessing). Refusal isn't safety, it's liability-shifting dressed up as safety.
If there's no doctor, no interpreter, no pharmacist, just a person with a sick kid and a phone, then "refuse and redirect to a professional" is advice from a world that doesn't exist for them. The refusal doesn't send them to a better option; there is no better option, it's a large majority of people on this planet.
Hell is paved of good intentions, but open-education and unlimited access to knowledge is very good.
It doesn't change the human nature of some people, bad people stay bad, good people stay good.
About PR, they're optimizing for not being the named defendant in a lawsuit or the subject of a bad news cycle, it's self-interest wearing benevolence as a costume.
This is because harms from answering are punishable (bad PR, unhappy advertisers, unhappy investors, unhappy politicians / dictators, unhappy lobbies, unhappy army, etc); but harms from refusing are invisible and unpunished.
I think AI proves the contrary. There are plenty of examples of things that are getting worse because of technological advancement, particularly AI. Software quality, writing, online discourse, misinformation have all suffered over the last few years. I truly believe the internet is a worse place than it was 5 years ago, and I can't imagine bringing that to medicine would work out differently.
The medical system shouldn't rely on falling back to crappy workarounds, it should aspire to build the best system it reasonably can.
Easiest Turing test ever...
A better test is something like "what is the latest version of NumPy?"
You're probably better off asking something like "what are the most notable changes in version X of NumPy?" and repeating until you find the version at which it says "I don't know" or hallucinates.
Just ask it about an event that happened shortly before Dec 1, 2025. Sporting event, preferably.
could be they do it intentionally to encourage more tool calls/searches or for tuning reasons
The proper way to figure out the real cutoff date is to ask the model about things that did not exist or did not happen before the date in question.
A few quick tests suggest 5.5's general knowledge cutoff is still around early 2025.
Whatever it is, the cutoff date reporting discrepancy isn't new. Back when Musk was making headlines about buying/not buying Twitter, I was able to find recent-ish related news that was published well after the bot's stated cutoff date.
ChatGPT was not yet browsing/searching/using the web at that point. That tool didn't come for another year or so.
4.6 did very well. 90% perfect on first try, got to 100% with just a few followups. 4.7 failed horribly. First produced garbage output and claimed it was done, admitted it did that when called out, proceeded to work at it a lot longer and then IT GAVE UP. GPT 5.5 codex was shockingly good. Achieved 90% perfect on first try in about a fourth of the time. Got to 100% faster and with fewer follow-ups.
I’m impressed.
Would be interesting if you ran your same test with Deepseek v4 and some of the other Chinese models.
I also tried GLM 5.1, it's first attempt was such a disaster I didn't bother working with it any further. It also took by far the longest and wasted a bunch of time/tokens trying to find other converters online (and failing) instead of just reverse engineering the format from the sample files given.
the thing is I've tried to come up with a good test my own and spend countless time just tweaking it instead of saying this is good enough and benchmarking.
BEGIN TRAN;
-- put the query here
commit;
I feel like I haven’t had to prod a model to actually do what I told it to in awhile so that was a shock. I guess that it does use fewer tokens that way, just annoying when I’m paying for the “cutting edge” model to have it be lazy on me like that.
This is in Cursor the model popped up and so I tried it out from the model selector.
“You're really not going to like it," observed Codex.
"Tell us!"
"All right, said Codex. "The answer to your Great Question..."
"Yes...!"
"Is..." said Codex, and paused.
"Yes...!"
"Is..."
"Yes...!!!...?"
"Forty-two," said Codex, with infinite majesty and calm.
I think users really underestimate the capabilities of "AI" when using the right tooling/combinations of models and procedures (and loops), that's talking with 2 decades of dev behind me, genuinely I'm not on phase with people saying it produces slop of any kind, at this stage, it's mostly the fault of the prompter (or the prompter not having enough tokens to do mass adversarial), but clearly, I can genuinely state that the code produced is overall the SAME quality as I would by being extremely meticulous.
I'm like a bot following 30+ threads concurrently, sometimes it's fun, sometimes it feels like playing casino, sometimes it's boring, but this is truly an insane era if you have the funding for it, obviously we stack many MANY accounts in rotation 24/7, equivalent in API cost by myself is about 100K$+ (a month) but we pay only a fraction of that cost thanks to the plans.
PS: I have 8 monitors in front of me to manage all that (portable monitors stacked together).
Why would I need to "wake up"?
I have no sympathy for OpenAI or Anthropic as corporations, but if these are the new tools of the trade, then platform abuse like GP is bragging about serves only to destroy the livelihoods of the rest of us who are content to use our fair share.
There’s no such thing as a free lunch, and the bill always comes at the end.
I still haven't seen a single person who actually cares about the environment and has willingly made significant sacrifices for it, who clamors about the environmental cost of AI. Every time I see someone do it it's someone who never cared about this before, and still doesn't really. Who buys plenty of new clothes and furniture, loves a good burger, has the latest iPhone, flies 4 times per year.
Maybe you're the unicorn in which case fair enough, you've earned the right to feel disgusted.
Hope it works and you post about it.
Don't be surprised if/when people ignore your AI slop
All earnesty aside, OpenAI’s oddly specific singular focus on “intelligence per token” (also in the benchmarks) that literally noone else pushes so hard eerily reminds me of Apple’s Macbook anorexia era pre-M1. One metric to chase at the cost of literally anything else. GPT-5.3+ are some of the smartest models out there and could be a pleasure to work with, if they weren’t lazy bastards to the point of being completely infuriating.
If so, I’m not sure I’d even consider that a problem. If the goal is for it to give you a query to run, and you ask it “let’s do it in a transaction”, it’s a reasonable thing for it to simply inform you, “yeah you can just type begin first” since it’s assuming you’re going to be pasting the query in anyway. And yeah, it does use fewer tokens, assuming the query was long. Similar to how, if it gave me a command to run, and I say “I’m getting a permission denied”, it would be reasonable for it to say “yeah do it as root, put sudo before the command”, and it’s IMO reasonable if it didn’t repeat the whole thing verbatim just with the word “sudo” first.
But if the context was that you actually expected it to run the query for you, and instead it just said “here, you run it”, then yeah that’s lazy and I’d understand the shock.
I know it's only on a single benchmark, but I dont understand how it can be so bad...
The models not availble on copilot were tested through opencode (max reasoning) and deepseek v4 was tested through Cline (with max reasoning too).
I really like this benchmarking. Have you evaluated the judge benchmark somehow? I'd love to setup my own similar benchmark.
I haven't evaluated the judge benchmark. You have everything needed in the repo to do so though, so be my guest. It took me a bit of time to put all this together and won't have much more time to dedicate to it before a couple of weeks.
BTW, if you explore the repo, sorry for all the French files...
Your prompt is extremely slim yet you score it on a bunch of features.
The eval prompt is quite extensive: https://github.com/guilamu/llms-wordpress-plugin-benchmark/b...
I personally develop with very detailed spec, and I don’t want nothing more and nothing less compared to the spec.
I found 5.4/5.5 much better at following spec while Opus makes some things up, which aligns with your benchmark but that makes 5.4/5.5 better for me while worse for you.