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 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) :)
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).
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.
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 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.
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.
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.
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.
Yes those two models were tested on my own PC (local inference using my own CPU/GPU). So something my be bugged on my setup. gemma4-26b should be far better than gemma4-e4b.
Sounds like maybe using worse quantization on the bigger model? Quantization matters a lot for the quality, basically anything below Q8 is borderline unusable. If it isn't specified in a benchmark already it probably should.
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.
Yeah as I said this a benchmark for my usecase only, a single use case, which is obvisouly not representative of everybody's needs.
What strike me as very strange though is that 0 model were able to just use the search input already present in GravitYForms forms list page and all created a second input.
Also, I know it's not in the prompt, but adding a ctrl+f shortcut to a search input? Is that that crazy? I don't know.
In the only one that feels that OpenAI has bots/commenters on payroll on all this kind of news downplaying Claude and stating how much better Codex is?
There is too much and there are too many, and some of their takes don’t fly if you use Claude daily.
Yeah, it's eerie, same with how everyone seems to have forgotten that OpenAI betrayed democracy by committing to work on unsupervised autonomous weapons and domestic mass surveillance.
Honestly I find comments like yours much more eerie. By all accounts they never agreed to any of that but you say it with such confidence like it's a fact.
Input: $5/M tokens at <=272K, $10/M tokens above 272K.
Output: $30/M tokens at <=272K, $45/M tokens above 272K.
Cache read: $0.50/M tokens at <=272K, $1/M tokens above 272K.
Significantly more expensive than Opus 4.7 beyond 272K and at least in my tasks, I haven't seen the model that much more token efficient, certainly not to such a degree that it'd compensate this difference. GPT-5.4 had a solid context window at 400k with reliable compaction, both appear somewhat regressed, though still to early to truly say whether compaction is less reliable. Also, I have found frontend output to still skew towards that one very distinct, easily noticeable, card laden, bluesy hue overindulged template that made me skeptical of Horizon Alpha/Beta pre GPT-5s release. Ended up doing amazing at the time for task adherence, which made it very useful for me outside that one major deficit. The fact that GPT-5.5 is still so restricted in that area is weird considering it's supposed to be an entirely new foundation.
Gpt 5.5 combined with codex is really good. I actually have no doubt whenever I asked questions, plan, or implement a code with it. With opus 4.7, I have to keep double checking because it doesnt follow the CLAUDE.md instruction, it hallucinates a lot, by default it makes things up when it can’t find the answer to something. Its crazy how quickly people are saying that OpenAI is left behind last year when they declared code red and look at where we are now
>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.
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!
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.”
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 don't see any meaningful performance improvements in those paid models anymore.
They all roughly produce junior developer-level code, continue to have mental breakdowns in their “thinking” stage, occasionally hallucinate things, delete pieces of code/docs they don’t understand or don’t like, use 1.5 times the necessary words to explain things when generating docs and so on.
I'm now testing "avoid sycophancy, keep details short and focus on the facts" in my AGENTS.md files.
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.
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.
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.
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.
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
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.
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.
I'm absolutely stunned by what I've seen from 5.5. I thought it'd be a nothingburger and ~= Opus.
Gave it two very long-running problems I haven't had the courage to work on in the last 2.5 years, solved each within an hour.
- An incremental streaming JSON decoder that can optionally take a list of keys to stop decoding after. 1800 LOC about 30 minutes later, and now my local-first apps first sync time is 0.8s instead of 75s when there's 1.5 GB of data locally.
- Flutter Web can compile to WASM and then render via Skia WASM. I've been getting odd crashes during rapid animation for months. In an hour, it got Skia WASM checked out, building locally, a Flutter test script, and root caused the issue to text shadows and font glyphs (technically, not solved yet, I want to get to the point we have Skia / Flutter patch(es))
If you told me a week ago that an LLM could do either of these, without heavy guidance, I'd be stunned. And I regularly push them to limits, ex. one of Opus' last projects was a tolerant JSON decoder, and it ended up being 8% faster than the one built-in to Dart/Flutter, which has plenty of love and attention. (we're cheating a little, that's why it's faster. TL;DR: LLMs will emit control characters in JSON and that's fine for me, treating them as fine means file edit error rates go from ~2% to 0%)
> 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.
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.
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.
"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.
-> 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.
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 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
Has that task accomplished anything yet?
I think the OP is in for a rude surprise when the task is “finished”.
It will go somewhat like this:
“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 bet you've asked Codex for that joke :p
Too soon to tell, give it a billion tokens before we make up our minds
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) :)
what is that task doing???
The correction question is: what isn't that task doing?
It made Sam richer.
Kept the OP employed for a full extra month at their high AI metric firm, hopefully.
Just making Jensen proud is all.
That’s actually crazy, what kind of task is that? And is that a recurring kind of task like some analysis, or coding related?
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).
Please do an update when you're ready, this sounds like madness to me so I'd love to see what the output is. Whatever it is I have to know.
Is it hitting intermediate milestones with solid pre-written and human-reviewed acceptance tests? If not, sounds like a very risky commitment.
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.
Specifically, write a post about this and do not have Claude write a post about this.
I have yet to talk to someone who is taking this approach and doesn’t end up with a dumpster fire, but here is to hoping this time is different.
Hope it works and you post about it.
I hope it doesn't work and they don't post about it.
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 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.
Or nostalgia for simpler times
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.
...what? what kind of a task are you running?
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.
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.
Can't tell if above is good or bad.
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.
GPT-5.5 shatters benchmarks for amount of faith it puts in the user.
Just tested it on my homemade Wordpress+GravityForms benchmark and it's one of the worst model of the leaderboard performance wise and the worst value wise: https://github.com/guilamu/llms-wordpress-plugin-benchmark
I know it's only on a single benchmark, but I dont understand how it can be so bad...
gemma4-e4b is 50% better than gemma4-26b in your benchmark, something's wrong
Yes those two models were tested on my own PC (local inference using my own CPU/GPU). So something my be bugged on my setup. gemma4-26b should be far better than gemma4-e4b.
Sounds like maybe using worse quantization on the bigger model? Quantization matters a lot for the quality, basically anything below Q8 is borderline unusable. If it isn't specified in a benchmark already it probably should.
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.
Yes Opus 4.7 fast (no reasoning) did a worst job than Sonnet 4.6 high (with reasoning) according to Gemini 3.1 Pro evaluation.
Your table doesn't indicate reasoning vs non-reasoning, or reasoning level
When nothing is noted it's max reasoning (xhigh in copilot chat in vscode if available).
The models not availble on copilot were tested through opencode (max reasoning) and deepseek v4 was tested through Cline (with max reasoning too).
You even traveled in time to deliver us this benchmark.
I really like this benchmarking. Have you evaluated the judge benchmark somehow? I'd love to setup my own similar benchmark.
Haha, just fixed the date!
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...
Seems like benchmark for how good a model is for vibe coding.
Your prompt is extremely slim yet you score it on a bunch of features.
Yes, the prompt is slim by design. I might be wrong, but the point was to see what the model can do "on it's own".
The eval prompt is quite extensive: https://github.com/guilamu/llms-wordpress-plugin-benchmark/b...
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.
Yeah as I said this a benchmark for my usecase only, a single use case, which is obvisouly not representative of everybody's needs.
What strike me as very strange though is that 0 model were able to just use the search input already present in GravitYForms forms list page and all created a second input.
Also, I know it's not in the prompt, but adding a ctrl+f shortcut to a search input? Is that that crazy? I don't know.
In the only one that feels that OpenAI has bots/commenters on payroll on all this kind of news downplaying Claude and stating how much better Codex is?
There is too much and there are too many, and some of their takes don’t fly if you use Claude daily.
Yeah, it's eerie, same with how everyone seems to have forgotten that OpenAI betrayed democracy by committing to work on unsupervised autonomous weapons and domestic mass surveillance.
Honestly I find comments like yours much more eerie. By all accounts they never agreed to any of that but you say it with such confidence like it's a fact.
Of course they do. As do all of the other companies pushing their product these days.
Pricing by context length:
Input: $5/M tokens at <=272K, $10/M tokens above 272K.
Output: $30/M tokens at <=272K, $45/M tokens above 272K.
Cache read: $0.50/M tokens at <=272K, $1/M tokens above 272K.
Significantly more expensive than Opus 4.7 beyond 272K and at least in my tasks, I haven't seen the model that much more token efficient, certainly not to such a degree that it'd compensate this difference. GPT-5.4 had a solid context window at 400k with reliable compaction, both appear somewhat regressed, though still to early to truly say whether compaction is less reliable. Also, I have found frontend output to still skew towards that one very distinct, easily noticeable, card laden, bluesy hue overindulged template that made me skeptical of Horizon Alpha/Beta pre GPT-5s release. Ended up doing amazing at the time for task adherence, which made it very useful for me outside that one major deficit. The fact that GPT-5.5 is still so restricted in that area is weird considering it's supposed to be an entirely new foundation.
Gpt 5.5 combined with codex is really good. I actually have no doubt whenever I asked questions, plan, or implement a code with it. With opus 4.7, I have to keep double checking because it doesnt follow the CLAUDE.md instruction, it hallucinates a lot, by default it makes things up when it can’t find the answer to something. Its crazy how quickly people are saying that OpenAI is left behind last year when they declared code red and look at where we are now
Huh. Yesterday they said:
>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.
When stuff is delayed due to "safeguards" it just means they don't think they have the compute to release it right now.
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!
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.”
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)
Second model to get 25/25 on my benchmark (after Opus 4.7): https://sql-benchmark.nicklothian.com/?highlight=openai_gpt-...
Cheaper and slower than Opus.
Comprehensive coding reasoning benchmark results for GPT 5.5 with max reasoning are up at https://gertlabs.com/
Live decision and heavier agentic evals will continue being uploaded for 24 hours but I don't expect its leaderboard position to change at this point.
GPT 5.5 is the most intelligent public model. And significantly faster than its predecessor.
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.
Just refreshed and see 5.5 now - yay! Love the speedy resolution ;) Thanks folks, I'll complain faster next time....
I don't see any meaningful performance improvements in those paid models anymore.
They all roughly produce junior developer-level code, continue to have mental breakdowns in their “thinking” stage, occasionally hallucinate things, delete pieces of code/docs they don’t understand or don’t like, use 1.5 times the necessary words to explain things when generating docs and so on.
I'm now testing "avoid sycophancy, keep details short and focus on the facts" in my AGENTS.md files.
This is snark. Since when has a junior level dev managed to debug and deploy say a cloudformation stack and follow up with notes under 3 minutes?
Heard this analogy elsewhere, but worth repeating:
AI is like having the greatest developer who ever lived, but she is always on 4 beers.
personifying ai is incredibly cringe no matter how weird your comparison is
It's an analogy.
Imagine a drunk developer. Sparks of brilliance while missing obvious trees.
API page lists the knowledge cutoff as Dec 01, 2025 but when prompting the model it says June 2024.
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.
the model obviously knows things after the reported date but its just curious that it reports that date consistently
could be they do it intentionally to encourage more tool calls/searches or for tuning reasons
Can you really believe things that the model says? (A lot of prior model api pages say knowledge cutoffs of June 2024, maybe the model picks that up?)
you cant but its pretty reproducible across api and codex and other agents so i just thought it was odd. full text it gives:
Models don't know what their cutoff dates are unless told via a system prompt.
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.
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.
OpenAI does tell the model the current date via API, so it's odd for them not to also tell the model its cutoff
Stupid question: wouldn't it then search the web for that event?
If you have web search enabled, sure. But if you're testing on the API, you can just not enable it.
can u test it on say who won the 2024 US election
I can't really think of a less reliable test for anything at all than making a random guess as to something that had about 50/50 odds to begin with
Easiest Turing test ever...
ask it 10 times.
MASSIVE ADVERSARIAL x50
Usually the labs do some kind of post training on major events so the model isn't totally lost.
A better test is something like "what is the latest version of NumPy?"
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.
with thinking off and tools disabled:
Looks like the default config in the chat is instant 5.3, it only uses the 5.5 on the thinking variant
They moved a few months ago to have separate instant and thinking models. 5.3 is the latest instant, and 5.5 is a reasoning model.
Exactly double the cost of GPT 5.4 - $5 per MTok input, $0.50 cached, $30 output.
All the AI players definitely seem to be trying to claw more money out of their users at the moment.
It's 2x/token, but for default reasoning we've found GPT-5.5 uses fewer tokens overall, so net cheaper on median. [1]
(Note, that stops being true at higher reasoning levels, where our observed total cost goes up ~2-3x.)
[1] https://x.com/voratiq/status/2047737190323769488?s=20
https://openrouter.ai/openai/gpt-5.5-pro
30/180 usd on Openrouter. Did I miss something?
I think that's Pro. Regular 5.5 is 2x regular 5.4.
not available for Github Copilot pro(only in pro+, business and enterprise), I am really now feeling the era of subsidized AI is over.
With a 7.5x multiplier and even that is a promo!! Microsoft is insane! https://github.blog/changelog/2026-04-24-gpt-5-5-is-generall...
This is where the emigration to Chinese providers begins.
Faster than anticipated because of Deepseek release?
Doubt it, DeepSeek v4 is quite underwhelming.
more like they wanted to release it yesterday but merely had some last min flags they wanted to hold off for
ok not bad
Maybe but no one serious is using deepseek
Is anyone here actually using pro models through the API? I'd be very curious what the use-case is.
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
Indeed, even just Terms of Service and Privacy Policy work. Infrequent enough that cost isn't an issue, but model quality absolutely is
Yes? The same reason you would use it via the tooling.
A very expensive model for API usage. Fine in codex I think.
what's the real world comparison to opus 4.7 fellow coders?
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.
I’m impressed.
Please consider the ethical aspects of giving money to OpenAI versus alternatives.
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.
You're right, unfortunately. How naive of me to think that at least the HN audience would care.
I'm absolutely stunned by what I've seen from 5.5. I thought it'd be a nothingburger and ~= Opus.
Gave it two very long-running problems I haven't had the courage to work on in the last 2.5 years, solved each within an hour.
- An incremental streaming JSON decoder that can optionally take a list of keys to stop decoding after. 1800 LOC about 30 minutes later, and now my local-first apps first sync time is 0.8s instead of 75s when there's 1.5 GB of data locally.
- Flutter Web can compile to WASM and then render via Skia WASM. I've been getting odd crashes during rapid animation for months. In an hour, it got Skia WASM checked out, building locally, a Flutter test script, and root caused the issue to text shadows and font glyphs (technically, not solved yet, I want to get to the point we have Skia / Flutter patch(es))
If you told me a week ago that an LLM could do either of these, without heavy guidance, I'd be stunned. And I regularly push them to limits, ex. one of Opus' last projects was a tolerant JSON decoder, and it ended up being 8% faster than the one built-in to Dart/Flutter, which has plenty of love and attention. (we're cheating a little, that's why it's faster. TL;DR: LLMs will emit control characters in JSON and that's fine for me, treating them as fine means file edit error rates go from ~2% to 0%)
I just wish it was cheaper, but, don't we all...
that is great news
GPT 5.5 is close to Opus 4.7, but at 7x the cost[0]...
Either Opus 4.7 miscounts reasoning tokens, or it's A LOT more efficient than GPT 5.5
I thought they made GPT 5.5 more token efficient than 5.4, but it uses 2x the reasoning tokens.
[0]: https://aibenchy.com/compare/openai-gpt-5-5-medium/openai-gp...
Very bad habit these safeguards. These "safety" filters are counter-productive and even can be dangerous.
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.
> 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.
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.
The doctor would be responsible.
I had a choice better a doctor that used AI or not, I would much prefer one that did...
The doctor would be responsible for the accuracy of their translation tool, something they can't verify but you expect them to use?
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.
"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.
(like in the other mentioned contexts).
What's the alternative then ?
-> 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.
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.
https://www.england.nhs.uk/interpreting/
We generally use translator telephone services. There is an entire industry for is - i.e. I used 'BigWord' today.
Yup, deliberately making the model retarded