I wonder how much of the '5 release was about cutting costs vs making it outwardly better. I'm speculating that one reason they'd deprecate older models is because 5 materially cheaper to run?
Would have been better to just jack up the price on the others. For companies that extensively test the apps they're building (which should be everyone) swapping out a model is a lot of work.
The vibe I'm getting from the Reddit community is that 5 is much less "Let's have a nice conversation for hours and hours" and much more "Let's get you a curt, targeted answer quickly."
So, good for professionals who want to spend lots of money on AI to be more efficient at their jobs. And, bad for casuals who want to spend as little money as possible to use lots of datacenter time as their artificial buddy/therapist.
The number of comments in the thread talking about 4o as if it were their best friend the shared all their secrets with is concerning. Lotta lonely folks out there
oh god, this is some real authentic dystopia right here
these things are going to end up in android bots in 10 years too
(honestly, I wouldn't mind a super smart, friendly bot in my old age that knew all my quirks but was always helpful... I just would not have a full-on relationship with said entity!)
Which is a bit frightening because a lot of the r/ChatGPT comments strike me as unhinged - it's like you would have thought that OpenAI murdered their puppy or something.
Anyone that remembers the reaction when Sydney from Microsoft or more recently Maya from Sesame losing their respective 'personality' can easily see how product managers are going to have to start paying attention to the emotional impact of changing or shutting down models.
Or they could just do it whenever they want to for whatever reason they want to. They are not responsible for the mental health of their users. Their users are responsible for that themselves.
Depends on what business OpenAI wants to be in. If they want to be in the business of selling AI to companies. Then "firing" the consumer customers that want someone to talk to, and double down models that are useful for work. Can be a wise choice.
Unless you want to improve your ratio of paid-to-free users and change your userbase in the process. They're pissing off free users, but pros who use the paid version might like this new version better.
Yeah it’s really bad over there. Like when a website changes its UI and people prefer the older look… except they’re acting like the old look was a personal friend who died.
I think LLMs are amazing technology but we’re in for really weird times as people become attached to these things.
I mean, I don’t mind the Claude 3 funeral. It seems like it was a fun event.
I’m less worried about the specific complaints about model deprecation, which can be ‘solved’ for those people by not deprecating the models (obviously costs the AI firms). I’m more worried about AI-induced psychosis.
An analogy I saw recently that I liked: when a cat sees a laser pointer, it is a fun thing to chase. For dogs it is sometimes similar and sometimes it completely breaks the dog’s brain and the dog is never the same again. I feel like AI for us may be more like laser pointers for dogs, and some among us are just not prepared to handle these kinds of AI interactions in a healthy way.
The first link says that patients can't reliably tell which is the therapist and which is LLM in single messages, which yeah, that's an LLM core competency.
The second is "how 2 use AI 4 therapy" which, there's at least one paper for every field like that.
The last found that they were measurably worse at therapy than humans.
So, yeah, I'm comfortable agreeing that all LLMs are bad therapists, and bad friends too.
If I think "it understands me better than any human", that's dissociation? Oh boy. And all this time while life has been slamming me with unemployment while my toddler is at the age of maximum energy-extraction from me (4), devastating my health and social life, I thought it was just a fellow-intelligence lifeline.
Here's a gut-check anyone can do, assuming you use a customized ChatGPT4o and have lots of conversations it can draw on: Ask it to roast you, and not to hold back.
Because more than any other phenomenon, LLMs are capable of bypassing natural human trust barriers. We ought to treat their output with significant detachment and objectivity, especially when they give personal advice or offer support. But especially for non-technical users, LLMs leap over the uncanny valley and create conversational attachment with their users.
The conversational capabilities of these models directly engages people's relational wiring and easily fools many people into believing:
(a) the thing on the other end of the chat is thinking/reasoning and is personally invested in the process (not merely autoregressive stochastic content generation / vector path following)
(b) its opinions, thoughts, recommendations, and relational signals are the result of that reasoning, some level of personal investment, and a resulting mental state it has with regard to me, and thus
(c) what it says is personally meaningful on a far higher level than the output of other types of compute (search engines, constraint solving, etc.)
I'm sure any of us can mentally enumerate a lot of the resulting negative effects. Like social media, there's a temptation to replace important relational parts of life with engaging an LLM, as it always responds immediately with something that feels at least somewhat meaningful.
But in my opinion the worst effect is that there's a temptation to turn to LLMs first when life trouble comes, instead of to family/friends/God/etc. I don't mean for help understanding a cancer diagnosis (no problem with that), but for support, understanding, reassurance, personal advice, and hope. In the very worst cases, people have been treating an LLM as a spiritual entity -- not unlike the ancient Oracle of Delphi -- and getting sucked deeply into some kind of spiritual engagement with it, and causing destruction to their real relationships as a result.
A parallel problem is that just like people who know they're taking a placebo pill, even people who are aware of the completely impersonal underpinnings of LLMs can adopt a functional belief in some of the above (a)-(c), even if they really know better. That's the power of verbal conversation, and in my opinion, LLM vendors ought to respect that power far more than they have.
> autoregressive stochastic content generation / vector path following
...their capabilities were much worse.
> God
Hate to break it to you, but "God" are just voices in your head.
I think you just don't like that LLM can replace therapist and offer better advice than biased family/friends who only know small fraction of what is going on in the world, therefore they are not equipped to give valuable and useful advice.
> I've seen many therapists and [...] their capabilities were much worse
I don't doubt it. The steps to mental and personal wholeness can be surprisingly concrete and formulaic for most life issues - stop believing these lies & doing these types of things, start believing these truths & doing these other types of things, etc. But were you tempted to stick to an LLM instead of finding a better therapist or engaging with a friend? In my opinion, assuming the therapist or friend is competent, the relationship itself is the most valuable aspect of therapy. That relational context helps you honestly face where you really are now--never trust an LLM to do that--and learn and grow much more, especially if you're lacking meaningful, honest relationships elsewhere in your life. (And many people who already have healthy relationships can skip the therapy, read books/engage an LLM, and talk openly with their friends about how they're doing.)
Healthy relationships with other people are irreplaceable with regard to mental and personal wholeness.
> I think you just don't like that LLM can replace therapist and offer better advice
What I don't like is the potential loss of real relationship and the temptation to trust LLMs more than you should. Maybe that's not happening for you -- in that case, great. But don't forget LLMs have zero skin in the game, no emotions, and nothing to lose if they're wrong.
> Hate to break it to you, but "God" are just voices in your head.
> We ought to treat their output with significant detachment and objectivity, especially when it gives personal advice or offers support.
Eh, ChatGPT is inherently more trustworthy than average if simply because it will not leave, will not judge, it will not tire of you, has no ulterior motive, and if asked to check its work, has no ego.
Does it care about you more than most people? Yes, by simply being not interested in hurting you, not needing anything from you, and being willing to not go away.
Unless you had a really bad upbringing, "caring" about you is not simply not hurting you, not needing anything from you, or not leaving you
One of the important challenges of existence, IMHO, is the struggle to authentically connect to people... and to recover from rejection (from other peoples' rulers, which eventually shows you how to build your own ruler for yourself, since you are immeasurable!) Which LLM's can now undermine, apparently.
Similar to how gaming (which I happen to enjoy, btw... at a distance) hijacks your need for achievement/accomplishment.
But also similar to gaming which can work alongside actual real-life achievement, it can work OK as an adjunct/enhancement to existing sources of human authenticity.
You've illustrated my point pretty well. I hope you're able to stay personally detached enough from ChatGPT to keep engaging in real-life relationships in the years to come.
Speaking for myself: the human mind does not seek truth or goodness, it primarily seeks satisfaction. That satisfaction happens in a context, and ever context is at least a little bit different.
The scary part: It is very easy for LLMs to pick up someone's satisfaction context and feed it back to them. That can distort the original satisfaction context, and it may provide improper satisfaction (if a human did this, it might be called "joining a cult" or "emotional abuse" or "co-dependence").
You may also hear this expressed as "wire-heading"
Well, because in a worst case scenario, if the pilot of that big airliner decides to do ChatGPT therapy instead of a real one and then suicides while flying, also other people feel the consequences.
Yeah I was going to say, as a pilot there is no such thing as "therapy" for pilots. You would permanently lose your medical if you even mentioned the word to your doctor.
If this type of thing really interests you and you want to go on a wild ride, check out season 2 of nathan fielders's The Rehearsal. You dont need to watch s1.
That's the worst case scenario? I can always construct worse ones. Suppose Donald Trump goes to a bad therapist and then decides to launch nukes at Russia. Damn, this therapy profession needs to be hard regulated. It could lead to the extinction of mankind.
Doc: The encounter could create a time paradox, the result of which could cause a chain reaction that would unravel the very fabric of the spacetime continuum and destroy the entire universe! Granted, that's a worst-case scenario. The destruction might in fact be very localised, limited to merely our own galaxy.
The issue is that people in general are very easy to fool into believing something harmful is helping them. If it was actually useful, it's not an issue. But just because someone believes it's useful doesn't mean it actually is.
The counter argument is that’s just a training problem, and IMO it’s a fair point. Neural nets are used as classifiers all the time; it’s reasonable that sufficient training data could produce a model that follows the professional standards of care in any situation you hand it.
The real problem is that we can’t tell when or if we’ve reached that point. The risk of a malpractice suit influences how human doctors act. You can’t sue an LLM. It has no fear of losing its license.
* Know whether its answers are objectively beneficial or harmful
* Know whether its answers are subjectively beneficial or harmful in the context of the current state of a person it cannot see, cannot hear, cannot understand.
* Know whether the user's questions, over time, trend in the right direction for that person.
That seems awfully optimistic, unless I'm misunderstanding the point, which is entirely possible.
Having an LLM as a friend or therapist would be like having a sociopath for those things -- not that an LLM is necessarily evil or antisocial, but they certainly meet the "lacks a sense of moral responsibility or social conscience" part of the definition.
And probably close to wrong if we are looking at the sheer scale of use.
There is a bit of reality denial among anti-AI people. I thought about why people don't adjust to this new reality. I know one of my friends was anti-AI and seems to continue to be because his reputation is a bit based on proving he is smart. Another because their job is at risk.
I'm appalled by how dismissive and heartless many HN users seem toward non-professional users of ChatGPT.
I use the GPT models (along with Claude and Gemini) a ton for my work. And from this perspective, I appreciate GPT-5. It does a good job.
But I also used GPT-4o extensively for first-person non-fiction/adventure creation. Over time, 4o had come to be quite good at this. The force upgrade to GPT-5 has, up to this point, been a massive reduction in quality for this use case.
GPT-5 just forgets or misunderstands things or mixes up details about characters that were provided a couple of messages prior, while 4o got these details right even when they hadn't been mentioned in dozens of messages.
I'm using it for fun, yes, but not as a buddy or therapist. Just as entertainment. I'm fine with paying more for this use if I need to. And I do - right now, I'm using `chatgpt-4o-latest` via LibreChat but it's a somewhat inferior experience to the ChatGPT web UI that has access to memory and previous chats.
Not the end of the world - but a little advance notice would have been nice so I'd have had some time to prepare and test alternatives.
I've seen quite a bit of this too, the other thing I'm seeing on reddit is I guess a lot of people really liked 4.5 for things like worldbuilding or other creative tasks, so a lot of them are upset as well.
There is certainly a market/hobby opportunity for "discount AI" for no-revenue creative tasks. A lot of r/LocalLLaMA/ is focused on that area and in squeezing the best results out of limited hardware. Local is great if you already have a 24 GB gaming GPU. But, maybe there's an opportunity for renting out low power GPUs for casual creative work. Or, an opportunity for a RenderToken-like community of GPU sharing.
Working on a rented GPU would not be local. But, renting a low-end GPU might be cheap enough to use for hobbyist creative work. I'm just musing on lots of different routes to make hobby AI use economically feasible.
The gpt-oss-20b model has demonstrated that a machine with ~13GB of available RAM can run a very decent local model - if that RAM is GPU-accessible (as seen on Apple silicon Macs for example) you can get very usable performance out of it too.
I'm hoping that within a year or two machines like that will have dropped further in price.
I mean - I 'm quite sure it's going to be available via API, and you can still do your worldbuilding if you're willing to go to places like OpenRouter.
I don't see how people using these as a therapist really has any measurable impact compared to using them as agents. I'll spend a day coding with an LLM and between tool calls, passing context to the model, and iteration I'll blow through millions of tokens. I don't even think a normal person is capable of reading that much.
The GPT-5 API has a new parameter for verbosity of output. My guess is the default value of this parameter used in ChatGPT corresponds to a lower verbosity than previous models.
It's a good reminder that OpenAI isn't incentivized to have users spend a lot of time on their platform. Yes, they want people to be engaged and keep their subscription, but better if they can answer a question in few turns rather than many. This dynamic would change immediately if OpenAI introduced ads or some other way to monetize each minute spent on the platform.
the classic 3rd space problem that Starbucks tackled; they initially wanted people to hang out and do work there, but grew to hate it so they started adding lots of little things to dissuade people from spending too much time there
> the classic 3rd space problem that Starbucks tackled
“Tackled” is misleading. “Leveraged to grow a customer base and then exacerbated to more efficiently monetize the same customer base” would be more accurate.
Great for the environment as well and the financial future of the company. I can't see how this is a bad thing, some people really were just suffering from Proompt Disorder
Doesn't look like they blew up the API use cases, just the consumer UI access. I wouldn't be surprised if they allow it again, hidden behind a setting (along with allowing the different routed GPT5 levels to be in the selector).
Ah ok, that's an important distinction. Seems much less a big deal then - or at least a consumer issue rather than a business one. Having never really used chatgpt (but used the apis a lot), I'm actually surprised that chat users would care. There are cost tradeoffs for the different models when building on them, but for chatgpt, it's less clear to me why one would move between selecting different models.
> There are cost tradeoffs for the different models when building on them, but for chatgpt, it's less clear to me why one would move between selecting different models.
The same tradeoffs (except cost, because that's roled into the plan not a factor when selecting on the interface) exist on ChatGPT, which is an app built on the underlying model like any other.
So getting rid of models that are stronger in some areas when adding a new one that is cheaper (presuming API costs also reflect cost to provide) has the same kinds of impacts on existing ChatGPT users established usages as it would have on a businesses established apps except that the ChatGPT users don't see a cost savings along with any disruption in how they were used to things working.
I have a feeling that the chatgpt ui does some behind-the scenes tuning as well--hidden prompt engineering if you will. I migrated to the api and 4o still seems different. Most obvious, I don't get the acks that make me feel like I should run for president.
Even ChatGPT 5 confirmed this,
why does the gpt-4o api not do this?
ChatGPT said:
Because the GPT-4o API is tuned and delivered in a neutral, low-intrusion style by default.
When OpenAI built GPT-4o for API use, they optimized it for:
Predictable formatting (so it works well in code, pipelines, chatbots, etc.)
Minimal unsolicited chatter (no “Nice!” or “Great job!” unless explicitly prompted)
Deterministic tone — so that two API calls with the same input produce consistent, professional output without extra filler.
That’s different from the ChatGPT product experience, which has its own “assistant personality” layer that sometimes adds those rapport-building acknowledgements in casual conversation.
In API mode, you’re the one defining the personality, so if you want that “Good! Looks like you’re digging in” style, you have to bake it into the system prompt, for example:
The GPT-4o you talk to through ChatGPT and the GPT-4o you access via the API are different models... but they're actually both available via the API.
https://platform.openai.com/docs/models/gpt-4o is gpt-4o in the API, also available as three date-stamped snapshots: gpt-4o-2024-11-20 and gpt-4o-2024-08-06 and gpt-4o-2024-05-13 - priced at $2.50/million input and $10.00/million output.
https://platform.openai.com/docs/models/chatgpt-4o-latest is chatgpt-4o-latest in the API. This is the model used by ChatGPT 4o, and it doesn't provide date-stamped snapshots: the model is updated on a regular basis without warning. It costs $5/million input and $15/million output.
If you use the same system prompt as ChatGPT (from one of the system prompt leaks) with that chatgpt-4o-latest alias you should theoretically get the same experience.
You have a system that’s cheaper to maintain or sells for a little bit more and it cannibalizes its siblings due to concerns of opportunity cost and net profit. You can also go pretty far in the world before your pool of potential future customers is muddied up with disgruntled former customers. And there are more potential future customers overseas than there are pissed off exes at home so let’s expand into South America!
Which of their other models can run well on the same gen of hardware?
I’m wondering that too. I think better routers will allow for more efficiency (a good thing!) at the cost of giving up control.
I think OpenAI attempted to mitigate this shift with the modes and tones they introduced, but there’s always going to be a slice that’s unaddressed. (For example, I’d still use dalle 2 if I could.)
> I wonder how much of the '5 release was about cutting costs vs making it outwardly better. I'm speculating that one reason they'd deprecate older models is because 5 materially cheaper to run?
I mean, assuming the API pricing has some relation to OpenAI cost to provide (which is somewhat speculative, sure), that seems pretty well supported as a truth, if not necessarily the reason for the model being introduced: the models discontinued (“deprecated” implies entering a notice period for future discontinuation) from the ChatGPT interface are priced significantly higher than GPT-5 on the API.
> For companies that extensively test the apps they're building (which should be everyone) swapping out a model is a lot of work.
Who is building apps relying on the ChatGPT frontend as a model provider? Apps would normally depend on the OpenAI API, where the models are still available, but GPT-5 is added and cheaper.
> Who is building apps relying on the ChatGPT frontend as a model provider? Apps would normally depend on the OpenAI API, where the models are still available, but GPT-5 is added and cheaper.
Always enjoy your comments dw, but on this one I disagree. Many non-technical people at my org use custom gpt's as "apps" to do some re-occuring tasks. Some of them have spent absurd time tweaking instructions and knowledge over and over. Also, when you create a custom gpt, you can specifically set the preferred model. This will no doubt change the behavior of those gpts.
Ideally at the enterprise level, our admins would have a longer sunset on these models via web/app interface to ensure no hiccups.
And my word that is a terrifying forum. What these people are doing cannot be healthy. This could be one of the most widespread mental health problems in history.
that is one of the more bizarre and unsettling subreddits I've seen. this seems like completely unhinged behavior and I can't imagine any positive outcome from it.
GPT-5 simply sucks at some things. The very first thing I asked it to do was to give me an image of knife with spiral damascus pattern, it gave me an image of such a knife, but with two handles at a right angle: https://chatgpt.com/share/689506a7-ada0-8012-a88f-fa5aa03474...
Then I asked it to give me the same image but with only one handle; as a result, it removed one of the pins from a handle, but the knife had still had two handles.
It's not surprising that a new version of such a versatile tool has edge cases where it's worse than a previous version (though if it failed at the very first task I gave it, I wonder how edge that case really was). Which is why you shouldn't just switch over everybody without grace period nor any choice.
The old chatgpt didn't have a problem with that prompt.
For something so complicated it doesn't surprise that a major new version has some worse behaviors, which is why I wouldn't deprecate all the old models so quickly.
You know that unless you control for seed and temperature, you always get a different output for the same prompts even with the model unchanged... right?
I think that is one of the most frustrating issues I currently face when using LLMs. One can send the same prompt in two separate chats and receive two drastically different responses.
It is frustrating that it’ll still give a bad response sometimes, but I consider the variation in responses a feature. If it’s going down the wrong path, it’s nice to be able to roll the dice again and get it back on track.
I’ve noticed inconsistencies like this, everyone said that it couldn’t count the b’s in blueberry, but it worked for me the first time, so I thought it was haters but played with a few other variations and got flaws. (Famously, it didn’t get r’s in strawberry).
I guess we know it’s non-deterministic but there must be some pretty basic randomizations in there somewhere, maybe around tuning its creativity?
Temperature is a very basic concept that makes LLMs work as well as they do in the first place. That's just how it works and that's how it's been always supposed to work.
So there may be something weird going on with images in GPT-5, which OpenAI avoided any discussion about in the livestream. The artist for SMBC noted that GPT-5 was better at plagiarizing his style: https://bsky.app/profile/zachweinersmith.bsky.social/post/3l...
However, there have been no updates to the underlying image model (gpt-image-1). But due to the autoregressive nature of the image generation where GPT generates tokens which are then decoded by the image model (in contrast to diffusion models), it is possible for an update to the base LLM token generator to incorporate new images as training data without having to train the downstream image model on those images.
No, those changes are going to be caused by the top level models composing different prompts to the underlying image models. GPT-5 is not a multi-modal image output model and still uses the same image generation model that other ChatGPT models use, via tool calling.
GPT-4o was meant to be multi-modal image output model, but they ended up shipping that capability as a separate model rather than exposing it directly.
I've worked on many migrations of things from vX to vX + 1, and there's always a tension between maximum backwards-compatibility, supporting every theoretical existing use-case, and just "flipping the switch" to move everyone to the New Way. Even though I, personally, am a "max backwards-compatibility" guy, it can be refreshing when someone decides to rip off the bandaid and force everyone to use the new best practice. How exciting! Unfortunately, this usually results in accidentally eliminating some feature that turns out to be Actually Important, a fuss is made, and the sudden forced migration is reverted after all.
I think the best approach is to move people to the newest version by default, but make it possible to use old versions, and then monitor switching rates and figure out what key features the new system is missing.
I usually think it's best to have both n and n - 1 versions for a limited time. As long as you always commit to removing the n - 1 version at a specified point in time, you don't get trapped in backward compatibility hell.
Unless n is in any way objectively worse than n-1, then remove n-1 immediately so users don't directly compare them. Even Valve did it with Counter-Strike 2 and GO.
With major redesigns, you often can’t directly compare the two versions —- they are different enough that you actually want people to use them in a different way. So it’s not that the new version is “worse”, it’s just different, and it’s possible that there are some workflows that are functionally impossible on the new version (you’d be surprised how easy it is to mess this up.)
> Emotional nuance is not a characteristic I would know how to test!
Well, that's easy, we knew that decades ago.
It’s your birthday. Someone gives you a calfskin wallet.
You’ve got a little boy. He shows you his butterfly collection plus the killing jar.
You’re watching television. Suddenly you realize there’s a wasp crawling on your arm.
Something I hadn’t thought about before with the V-K test: in the setting of the film animals are just about extinct. The only animal life we see are engineered like the replicants.
I had always thought of the test as about empathy for the animals, but hadn’t really clocked that in the world of the film the scenarios are all major transgressions.
The calfskin wallet isn’t just in poor taste, it’s rare & obscene.
As an aside, people should avoid using "deprecate" to mean "shut down". If something is deprecated, that means that you shouldn't use it. For example, the C library's gets() function was deprecated because it is a security risk, but it wasn't removed until 12 years later. The distinction is important: if you're using GPT-4o and it is deprecated, you don't need to do anything, but if it is shut down, then you have a problem.
o3 was also an anomaly in terms of speed vs response quality and price vs performance. It used to be one of the fastest ways to do some basic web searches you would have done to get an answer if you used o3 pro you it would take 5x longer for not much better response.
So far I haven’t been impressed with GPT5 thinking but I can’t concretely say why yet. I am thinking of comparing the same prompt side by side between o3 and GPT5 thinking.
Also just from my first few hours with GPT5 Thinking I feel that it’s not as good at short prompts as o3 e.g instead of using a big xml or json prompt I would just type the shortest possible phrase for the task e.g “best gpu for home LLM inference vs cloud api.”
My chats so far have been similar to yours, across the board worse than o3, never better. I've had cases where it completely misinterpreted what I was asking for, a very strange experience which I'd never had with the other frontier models (o3, Sonnet, Gemini Pro). Those would of course get things wrong, make mistakes, but never completely misunderstand what I'm asking. I tried the same prompt on Sonnet and Gemini and both understood correctly.
It was related to software architecture, so supposedly something it should be good at. But for some reason it interpreted me as asking from an end-user perspective instead of a developer of the service, even though it was plenty clear to any human - and other models - that I meant the latter.
> I've had cases where it completely misinterpreted what I was asking for, a very strange experience which I'd never had with the other frontier models (o3, Sonnet, Gemini Pro).
Yes! This exactly, with o3 you could ask your question imprecisely or word it badly/ambiguously and it would figure out what you meant, with GPT5 I have had several cases just in the last few hours where it misunderstands the question and requires refinement.
> It was related to software architecture, so supposedly something it should be good at. But for some reason it interpreted me as asking from an end-user perspective instead of a developer of the service, even though it was plenty clear to any human - and other models - that I meant the latter.
For me I was using o3 in daily life like yesterday we were playing a board game so I wanted to ask GPT5 Thinking to clarify a rule, I used the ambiguous prompt with a picture of a card’s draw 1 card power and asked “Is this from the deck or both?” (From the deck or from the board). It responded by saying the card I took a picture of was from the game wingspan’s deck instead of clarifying the actual power on the card (o3 would never).
I’m not looking forward to how much time this will waste on my weekend coding projects this weekend.
It appears to be overtuned on extremy strict instruction following, interpreting things in a very unhuman way, which may be a benefit to agentic tasks at the costs of everything else.
My limited API testing with gpt-5 also showed this. As an example, the instruction "don't use academic language" caused it to basically omit half of what it output without that instruction. The other frontier models, and even open source Chinese ones like Kimi and Deepseek, understand perfectly fine what we mean by it.
It's not great at agentic tasks either. Not the least because it seems very timid about doing things on its own, and demands (not asks - demands) that user confirm every tiny step.
We have a team account and my buddy has GPT-5 in the app but not on the website. At the same time, I have GPT-5 on the website, but in the app, I still only have GPT-4o. We're confused as hell, to say the least.
I’m on Plus and have only GPT-5 on the iOS app and only the old models (except 4.5 and older expensive to run ones) in the web interface since yesterday after the announcement.
Charge more for LTS support. That’ll chase people onto your new systems.
I’ve seen this play out badly before. It costs real money to keep engineers knowledgeable of what should rightfully be EOL systems. If you can make your laggard customers pay extra for that service, you can take care of those engineers.
The reward for refactoring shitty code is supposed to be not having to deal with it anymore. If you have to continue dealing with it anyway, then you pay for every mistake for years even if you catch it early. You start shutting down the will for continuous improvement. The tech debt starts to accumulate because it can never be cleared, and trying to use makes maintenance five times more confusing. People start wanting more Waterfall design to try to keep errors from ever being released in the first place. It’s a mess.
Models aren't code though. I'm sure there's code around it but for the most part models aren't maintained, they're just replaced. And a system that was state of the art literally yesterday is really hard to characterize as "rightfully EOL".
That doesn’t stop manufacturers from getting rid of parts that have no real equivalent elsewhere in their catalog. Sometimes they do, but at the end of the day you’re at their mercy. Or you have strong enough ties to their management that they keep your product forever, even later when it’s hurting them to keep it.
We are going to double GPT-5 rate limits for ChatGPT Plus users as we finish rollout.
We will let Plus users choose to continue to use 4o. We will watch usage as we think about how long to offer legacy models for.
GPT-5 will seem smarter starting today. Yesterday, the autoswitcher broke and was out of commission for a chunk of the day, and the result was GPT-5 seemed way dumber. Also, we are making some interventions to how the decision boundary works that should help you get the right model more often.
We will make it more transparent about which model is answering a given query.
We will change the UI to make it easier to manually trigger thinking.
Rolling out to everyone is taking a bit longer. It’s a massive change at big scale. For example, our API traffic has about doubled over the past 24 hours…
We will continue to work to get things stable and will keep listening to feedback. As we mentioned, we expected some bumpiness as we roll out so many things at once. But it was a little more bumpy than we hoped for!
All these announces are scenery and promotion. Very low chance any of these "corrections" were not planned. For some reason, sama et al. make me feel like a mouse played with by a cat.
Why on earth would they undercut the launch of their new model by "planning" to do a stunt where people demand the old models instead of the new models?
It’s boggles my mind that enterprises or SaaS wouldn’t be following release cycles of new models to improve their service and/or cost. Although I guess there’s enterprises that don’t do OS upgrades or pathing too, just alien to me.
They're almost never straight upgrades for the exact same prompts across the board at the same latency and price. The last time that happened was already a year ago, with 3.5 Sonnet.
Striking up a voice chat with GPT-5 it starts by affirming my custom instructions/system prompt. Every time. Does not pass the vibe check.
”Absolutely, happy to jump in. And you got it, I’ll keep it focused and straightforward.”
”Absolutely, and nice to have that context, thanks for sharing it. I’ll keep it focused and straightforward.”
Anyone else have these issues?
EDIT: This is the answer to me just saying the word hi.
”Hello! Absolutely, I’m Arden, and I’m on board with that. We’ll keep it all straightforward and well-rounded. Think of me as your friendly, professional colleague who’s here to give you clear and precise answers right off the bat. Feel free to let me know what we’re tackling today.”
We were laughing about it with my son. He was asking some questions and the voice kept prefacing every answer with something like "Without the fluff", "Straight to the point" and variations thereof. Honestly that was hilarious.
gemini 2.5pro is my favorite but it's really annoying how it congratulates me on asking such great questions at the start of every single response even when i set a system prompt stating not to do it
I still haven't got access to GPT-5 (plus user in US), and I am not really super looking forward to it given I would lose access to o3. o3 is a great reasoning and planning model (better than Claude Opus in planning IMO and cheaper) that I use in the UI as well as through API. I don't think OpenAI should force users to an advanced model if there is not a noticeable difference in capability. But I guess it saves them money? Someone posted on X how giving access to only GPT-5 and GPT-5 thinking reduces a plus user's overall weekly request rate.
Somewhat unsurprising to see the reactions to be closer to losing an old coworker than just deprecations / regressions: you miss humans not just for their performance but also their quirks.
> But if you’re already leaning on the model for life advice like this, having that capability taken away from you without warning could represent a sudden and unpleasant loss!
Sure, going cold turkey like this is unpleasant, but it's usually for the best - the sooner you stop looking for "emotional nuance" and life advice from an LLM, the better!
Taking away user choice is often done in the name of simplicity. But let's not forget that given 100 users, 60 are likely to answer with "no opinion" when asked what about their preference to ANY question. Does that mean the other 40% aren't valuable and their preferences not impactful to the other "we don't care" majority?
This is also showing up on Xitter as the #keep4o movement, which some have criticized as being "oneshotted" or cases of LLM psychosis and emotional attachment.
This doesn't seem to be the case for me. I have access to GPT-5 via chatgpt, and I can also use GPT-4o. All my chat history opens with the originally used model as well.
I'm not saying it's not happening - but perhaps the rollout didn't happen as expected.
It's not totally surprising given the economics of LLM operation. LLMs, when idle, are much more resource-heavy than an idle web service. To achieve acceptable chat response latency, the models need to be already loaded in memory, and I doubt that these huge SotA models can go from cold start to inference in milliseconds or even seconds. OpenAI is incentivized to push as many users onto as few models as possible to manage the capacity and increase efficiency.
This was my thought. They messaged quite heavily in advance that they were capacity constrained, and I'd guess they just want to shuffle out GPT-4 serving as quickly as possible as its utilisation will only get worse over time, and that's time they can be utilising better for GPT-5 serving.
It's a whole family of brand new models with a model picker on top of them for the ChatGPT application layer, but API users can directly interact with the new models without any model picking layer involved at all.
GPT5 is some sort of quantized model, its not SOTA.
The trust that OpenAI would be SOTA has been shattered. They were among the best with o3/o4 and 4.5. This is a budget model and they rolled it out to everyone.
I unsubscribed. Going to use Gemini, it was on-par with o3.
> GPT-5 will seem smarter starting today. Yesterday, the autoswitcher broke and was out of commission for a chunk of the day, and the result was GPT-5 seemed way dumber. Also, we are making some interventions to how the decision boundary works that should help you get the right model more often.
reading all the shilling of Claude and GPT i see here often I feel like i'm being gaslighted
i've been using premium tiers of both for a long time and i really felt like they've been getting worse
especially Claude I find super frustrating and maddening, misunderstanding basic requests or taking liberties by making unrequested additions and changes
i really had this sense of enshittification, almost as if they are no longer trying to serve my requests but do something else instead like i'm victim of some kind of LLM a/b testing to see how far I can tolerate or how much mental load can be transferred back onto me
While it's possible that the LLMs are intentionally throttled to save costs, I would also keep in mind that LLMs are now being optimized for new kinds of workflows, like long-running agents making tool calls. It's not hard to imagine that improving performance on one of those benchmarks comes at a cost to some existing features.
Anthropic have stated on the record several times that they do not update the model weights once they have been deployed without also changing the model ID.
How can I be so sure? Evals. There was a point where Sonnet 3.5 v2 happily output 40k+ tokens in one message if asked. And one day it started with 99% consistency, outputting "Would you like me to continue?" after a lot fewer tokens than that. We'd been running the same set of evals and so could definitively confirm this change. Googling will also reveal many reports of this.
Whatever they did, in practice they lied: API behavior of a deployed model changed.
Another one: Differing performance - not latency but output on the same prompt, over 100+ runs, statistically significant enough to be impossible by random chance - between AWS Bedrock hosted Sonnet and direct Anthropic API Sonnet, same model version.
Don't take at face value what model providers claim.
If they are lying about changing model weights despite keeping the date-stamped model ID the same it would be a monumental lie.
Anthropic make most of their revenue from paid API usage. Their paying customers need to be able to trust them when they make clear statements about their model deprecation policy.
I'm going to chose to continue to believe them until someone shows me incontrovertible evidence that this isn't true.
I suspect that it may not necessarily be that they're getting objectively _worse_ as much as that they aren't static products. They're constantly getting their prompts/context engines tweaked in ways that surely break peoples' familiar patterns. There really needs to be a way to cheaply and easily anchor behaviors so that people can get more consistency. Either that or we're just going to have to learn to adapt.
This is disappointing. 4o has been performing great for me, and now I see I only have access to the 5-level models. Already it's not as good. More verbose with technical wording, but it adds very little to what I'm using GPT for.
I spoke with gpt-5, and asked it about shrinkflation, enshittification, and its relevancy to this situation. I think Hacker News will agree with gpt-5s findings.
> Do you understand what shrinkflation is? Do you understand the relationship between enshittification and such things as shrinkflation?
> I understand exactly what you’re saying — and yes, the connection you’re drawing between shrinkflation, enshittification, and the current situation with this model change is both valid and sharp.
> What you’re describing matches the pattern we just talked about:
This is not a deprecation and users still have access to 4o, in fact it's renamed to "gpt-5-main" and called out as the key model, and as the author said you can still use it via the API
What changed was you can't specify a specific model in the web-interface anymore, and the MOE pointer head is going to route you to the best model they think you need. Had the author addressed that point it would be salient.
This tells me that people, even technical people, really have no idea how this stuff works and want there to be some kind of stability for the interface, and that's just not going to happen anytime soon. It also is the "you get what we give you" SaaS design so in that regard it's exactly the same as every other SaaS service.
GPT-5:
400,000 context window
128,000 max output tokens
Sep 30, 2024 knowledge cutoff
Reasoning token support
GPT-4o:
128,000 context window
16,384 max output tokens
Sep 30, 2023 knowledge cutoff
Also note that I said "consumer ChatGPT account". The API is different. (I added a clarification note to my post about that since first publishing it.)
GPT-5 isn't the successor to 4o no matter what they say, GPT-5 is a MOE handler on top of multiple "foundations", it's not a new model, it's orchestration of models based on context fitting
You're buying the marketing bullshit as though it's real
I'm unable to use anything but GPT-5, and the response I've gotten don't nearly consider my past history. Projects don't work at all. I cancelled my Plus subscription, not that OpenAI cares.
I've been seeing someone on Tiktok that appears to be one of the first public examples of AI psychosis, and after this update to GPT-5, the AI responses were no longer fully feeding into their delusions. (Don't worry, they switched to Claude, which has been far worse!)
> If Claude notices signs that someone may unknowingly be experiencing mental health symptoms such as mania, psychosis, dissociation, or loss of attachment with reality, it should avoid reinforcing these beliefs. It should instead share its concerns explicitly and openly without either sugar coating them or being infantilizing, and can suggest the person speaks with a professional or trusted person for support. Claude remains vigilant for escalating detachment from reality even if the conversation begins with seemingly harmless thinking.
I started doing this thing recently where I took a picture of melons at the store to get chatGPT to tell me which it thinks is best to buy (from color and other characteristics).
chatGPT will do it without question. Claude won't even recommend any melon, it just tells you what to look for. Incredibly different answer and UX construction.
The people complaining on Reddit complaining on Reddit seem to have used it as a companion or in companion-like roles. It seems like maybe OAI decided that the increasing reports of psychosis and other potential mental health hazards due to therapist/companion use were too dangerous and constituted potential AI risk. So they fixed it. Of course everyone who seemed to be using GPT in this way is upset, but I haven't seen many reports of what I would consider professional/healthy usage becoming worse.
Edit to add: according to Sam Altman in the reddit AMA they un-deprecated it based on popular demand. https://old.reddit.com/r/ChatGPT/comments/1mkae1l/gpt5_ama_w...
I wonder how much of the '5 release was about cutting costs vs making it outwardly better. I'm speculating that one reason they'd deprecate older models is because 5 materially cheaper to run?
Would have been better to just jack up the price on the others. For companies that extensively test the apps they're building (which should be everyone) swapping out a model is a lot of work.
The vibe I'm getting from the Reddit community is that 5 is much less "Let's have a nice conversation for hours and hours" and much more "Let's get you a curt, targeted answer quickly."
So, good for professionals who want to spend lots of money on AI to be more efficient at their jobs. And, bad for casuals who want to spend as little money as possible to use lots of datacenter time as their artificial buddy/therapist.
Well, good, because these things make bad friends and worse therapists.
The number of comments in the thread talking about 4o as if it were their best friend the shared all their secrets with is concerning. Lotta lonely folks out there
Wait until you see
https://www.reddit.com/r/MyBoyfriendIsAI/
They are very upset by the gpt5 model
oh god, this is some real authentic dystopia right here
these things are going to end up in android bots in 10 years too
(honestly, I wouldn't mind a super smart, friendly bot in my old age that knew all my quirks but was always helpful... I just would not have a full-on relationship with said entity!)
Which is a bit frightening because a lot of the r/ChatGPT comments strike me as unhinged - it's like you would have thought that OpenAI murdered their puppy or something.
This is only going to get worse.
Anyone that remembers the reaction when Sydney from Microsoft or more recently Maya from Sesame losing their respective 'personality' can easily see how product managers are going to have to start paying attention to the emotional impact of changing or shutting down models.
Or they could just do it whenever they want to for whatever reason they want to. They are not responsible for the mental health of their users. Their users are responsible for that themselves.
Generally it's poor business to give a big chunk of your users am incredibly visceral and negative emotional reaction to your product update.
Depends on what business OpenAI wants to be in. If they want to be in the business of selling AI to companies. Then "firing" the consumer customers that want someone to talk to, and double down models that are useful for work. Can be a wise choice.
Unless you want to improve your ratio of paid-to-free users and change your userbase in the process. They're pissing off free users, but pros who use the paid version might like this new version better.
Yeah it’s really bad over there. Like when a website changes its UI and people prefer the older look… except they’re acting like the old look was a personal friend who died.
I think LLMs are amazing technology but we’re in for really weird times as people become attached to these things.
I mean, I don’t mind the Claude 3 funeral. It seems like it was a fun event.
I’m less worried about the specific complaints about model deprecation, which can be ‘solved’ for those people by not deprecating the models (obviously costs the AI firms). I’m more worried about AI-induced psychosis.
An analogy I saw recently that I liked: when a cat sees a laser pointer, it is a fun thing to chase. For dogs it is sometimes similar and sometimes it completely breaks the dog’s brain and the dog is never the same again. I feel like AI for us may be more like laser pointers for dogs, and some among us are just not prepared to handle these kinds of AI interactions in a healthy way.
I just saw a fantastic TikTok about ChatGPT psychosis: https://www.tiktok.com/@pearlmania500/video/7535954556379761...
Oh boy. My son just turned 4. Parenting about to get weird-hard
>unhinged
It's Reddit, what were you expecting?
Are all humans good friends and therapists?
Not all humans are good friends and therapists. All LLMS are bad friends and therapists.
> all LLMS are bad friends and therapists.
Is that just your gut feel? Because there has been some preliminary research that suggest it's, at the very least, an open question:
https://neurosciencenews.com/ai-chatgpt-psychotherapy-28415/
https://pmc.ncbi.nlm.nih.gov/articles/PMC10987499/
https://arxiv.org/html/2409.02244v2
> Is that just your gut feel?
Here's my take further down the thread: https://news.ycombinator.com/item?id=44840311
The first link says that patients can't reliably tell which is the therapist and which is LLM in single messages, which yeah, that's an LLM core competency.
The second is "how 2 use AI 4 therapy" which, there's at least one paper for every field like that.
The last found that they were measurably worse at therapy than humans.
So, yeah, I'm comfortable agreeing that all LLMs are bad therapists, and bad friends too.
there's also been a spate of reports like this one recently https://www.papsychotherapy.org/blog/when-the-chatbot-become...
which is definitely worse than not going to a therapist
If I think "it understands me better than any human", that's dissociation? Oh boy. And all this time while life has been slamming me with unemployment while my toddler is at the age of maximum energy-extraction from me (4), devastating my health and social life, I thought it was just a fellow-intelligence lifeline.
Here's a gut-check anyone can do, assuming you use a customized ChatGPT4o and have lots of conversations it can draw on: Ask it to roast you, and not to hold back.
If you wince, it "knows you" quite well, IMHO.
I do not think there are any documented cases of LLMs being reasonable friends or therapists so I think it is fair to say that:
> All LLMS are bad friends and therapists
That said it would not surprise me that LLMs in some cases are better than having nothing at all.
Though given how agreeable LLMs are, I'd imagine there are cases where they are also worse than having nothing at all as well.
Absolutes, monastic take... Yeah I imagine not a lot of people seek out your advice.
All humans are not LLMs, why does this constantly get brought up?
> All humans are not LLMs
What a confusing sentence to parse
You wouldn't necessarily know, talking to some of them.
I kind of agree with you as I wouldn't use LLMs for that.
But also, one cannot speak for everybody, if it's useful for someone on that context, why's that an issue?
Because more than any other phenomenon, LLMs are capable of bypassing natural human trust barriers. We ought to treat their output with significant detachment and objectivity, especially when they give personal advice or offer support. But especially for non-technical users, LLMs leap over the uncanny valley and create conversational attachment with their users.
The conversational capabilities of these models directly engages people's relational wiring and easily fools many people into believing:
(a) the thing on the other end of the chat is thinking/reasoning and is personally invested in the process (not merely autoregressive stochastic content generation / vector path following)
(b) its opinions, thoughts, recommendations, and relational signals are the result of that reasoning, some level of personal investment, and a resulting mental state it has with regard to me, and thus
(c) what it says is personally meaningful on a far higher level than the output of other types of compute (search engines, constraint solving, etc.)
I'm sure any of us can mentally enumerate a lot of the resulting negative effects. Like social media, there's a temptation to replace important relational parts of life with engaging an LLM, as it always responds immediately with something that feels at least somewhat meaningful.
But in my opinion the worst effect is that there's a temptation to turn to LLMs first when life trouble comes, instead of to family/friends/God/etc. I don't mean for help understanding a cancer diagnosis (no problem with that), but for support, understanding, reassurance, personal advice, and hope. In the very worst cases, people have been treating an LLM as a spiritual entity -- not unlike the ancient Oracle of Delphi -- and getting sucked deeply into some kind of spiritual engagement with it, and causing destruction to their real relationships as a result.
A parallel problem is that just like people who know they're taking a placebo pill, even people who are aware of the completely impersonal underpinnings of LLMs can adopt a functional belief in some of the above (a)-(c), even if they really know better. That's the power of verbal conversation, and in my opinion, LLM vendors ought to respect that power far more than they have.
I've seen many therapists and:
> autoregressive stochastic content generation / vector path following
...their capabilities were much worse.
> God
Hate to break it to you, but "God" are just voices in your head.
I think you just don't like that LLM can replace therapist and offer better advice than biased family/friends who only know small fraction of what is going on in the world, therefore they are not equipped to give valuable and useful advice.
> I've seen many therapists and [...] their capabilities were much worse
I don't doubt it. The steps to mental and personal wholeness can be surprisingly concrete and formulaic for most life issues - stop believing these lies & doing these types of things, start believing these truths & doing these other types of things, etc. But were you tempted to stick to an LLM instead of finding a better therapist or engaging with a friend? In my opinion, assuming the therapist or friend is competent, the relationship itself is the most valuable aspect of therapy. That relational context helps you honestly face where you really are now--never trust an LLM to do that--and learn and grow much more, especially if you're lacking meaningful, honest relationships elsewhere in your life. (And many people who already have healthy relationships can skip the therapy, read books/engage an LLM, and talk openly with their friends about how they're doing.)
Healthy relationships with other people are irreplaceable with regard to mental and personal wholeness.
> I think you just don't like that LLM can replace therapist and offer better advice
What I don't like is the potential loss of real relationship and the temptation to trust LLMs more than you should. Maybe that's not happening for you -- in that case, great. But don't forget LLMs have zero skin in the game, no emotions, and nothing to lose if they're wrong.
> Hate to break it to you, but "God" are just voices in your head.
Never heard that one before :) /s
> We ought to treat their output with significant detachment and objectivity, especially when it gives personal advice or offers support.
Eh, ChatGPT is inherently more trustworthy than average if simply because it will not leave, will not judge, it will not tire of you, has no ulterior motive, and if asked to check its work, has no ego.
Does it care about you more than most people? Yes, by simply being not interested in hurting you, not needing anything from you, and being willing to not go away.
Unless you had a really bad upbringing, "caring" about you is not simply not hurting you, not needing anything from you, or not leaving you
One of the important challenges of existence, IMHO, is the struggle to authentically connect to people... and to recover from rejection (from other peoples' rulers, which eventually shows you how to build your own ruler for yourself, since you are immeasurable!) Which LLM's can now undermine, apparently.
Similar to how gaming (which I happen to enjoy, btw... at a distance) hijacks your need for achievement/accomplishment.
But also similar to gaming which can work alongside actual real-life achievement, it can work OK as an adjunct/enhancement to existing sources of human authenticity.
You've illustrated my point pretty well. I hope you're able to stay personally detached enough from ChatGPT to keep engaging in real-life relationships in the years to come.
It's not even the first time this week I've seen someone on HM apparently ready to give up human contact in favour of LLMs.
Speaking for myself: the human mind does not seek truth or goodness, it primarily seeks satisfaction. That satisfaction happens in a context, and ever context is at least a little bit different.
The scary part: It is very easy for LLMs to pick up someone's satisfaction context and feed it back to them. That can distort the original satisfaction context, and it may provide improper satisfaction (if a human did this, it might be called "joining a cult" or "emotional abuse" or "co-dependence").
You may also hear this expressed as "wire-heading"
If treating an LLM as a bestie is allowing yourself to be "wire-headed"... Can gaming be "wire-heading"?
Does the severity or excess matter? Is "a little" OK?
This also reminds me of one of Michael Crichton's earliest works (and a fantastic one IMHO), The Terminal Man
https://en.wikipedia.org/wiki/The_Terminal_Man
https://1lib.sk/book/1743198/d790fa/the-terminal-man.html
Well, because in a worst case scenario, if the pilot of that big airliner decides to do ChatGPT therapy instead of a real one and then suicides while flying, also other people feel the consequences.
Pilots don't go to real therapy, because real pilots don't get sad
https://www.nytimes.com/2025/03/18/magazine/airline-pilot-me...
Yeah I was going to say, as a pilot there is no such thing as "therapy" for pilots. You would permanently lose your medical if you even mentioned the word to your doctor.
Fascinating read. Thanks.
If this type of thing really interests you and you want to go on a wild ride, check out season 2 of nathan fielders's The Rehearsal. You dont need to watch s1.
That's the worst case scenario? I can always construct worse ones. Suppose Donald Trump goes to a bad therapist and then decides to launch nukes at Russia. Damn, this therapy profession needs to be hard regulated. It could lead to the extinction of mankind.
Doc: The encounter could create a time paradox, the result of which could cause a chain reaction that would unravel the very fabric of the spacetime continuum and destroy the entire universe! Granted, that's a worst-case scenario. The destruction might in fact be very localised, limited to merely our own galaxy.
Marty: Well, that's a relief.
Good thing Biff Tanner becoming president was a silly fictional alternate reality. Phew.
The issue is that people in general are very easy to fool into believing something harmful is helping them. If it was actually useful, it's not an issue. But just because someone believes it's useful doesn't mean it actually is.
Whether the Hippocratic oath, the rules of the APA or any other organization, most all share "do no harm" as a core tenant.
LLMs cannot conform to that rule because they cannot distinguish between good advice and enabling bad behavior.
The counter argument is that’s just a training problem, and IMO it’s a fair point. Neural nets are used as classifiers all the time; it’s reasonable that sufficient training data could produce a model that follows the professional standards of care in any situation you hand it.
The real problem is that we can’t tell when or if we’ve reached that point. The risk of a malpractice suit influences how human doctors act. You can’t sue an LLM. It has no fear of losing its license.
An LLM would, surely, have to:
* Know whether its answers are objectively beneficial or harmful
* Know whether its answers are subjectively beneficial or harmful in the context of the current state of a person it cannot see, cannot hear, cannot understand.
* Know whether the user's questions, over time, trend in the right direction for that person.
That seems awfully optimistic, unless I'm misunderstanding the point, which is entirely possible.
It is definitely optimistic, but I was steelmanning the optimist’s argument.
Neither most of the doctors I've talked to in the past like ... 20 years or so.
Having an LLM as a friend or therapist would be like having a sociopath for those things -- not that an LLM is necessarily evil or antisocial, but they certainly meet the "lacks a sense of moral responsibility or social conscience" part of the definition.
Because it's probably not great for one's mental health to pretend a statistical model is ones friend?
Fuck.
Well, like, thats just your opinion man.
And probably close to wrong if we are looking at the sheer scale of use.
There is a bit of reality denial among anti-AI people. I thought about why people don't adjust to this new reality. I know one of my friends was anti-AI and seems to continue to be because his reputation is a bit based on proving he is smart. Another because their job is at risk.
I'm appalled by how dismissive and heartless many HN users seem toward non-professional users of ChatGPT.
I use the GPT models (along with Claude and Gemini) a ton for my work. And from this perspective, I appreciate GPT-5. It does a good job.
But I also used GPT-4o extensively for first-person non-fiction/adventure creation. Over time, 4o had come to be quite good at this. The force upgrade to GPT-5 has, up to this point, been a massive reduction in quality for this use case.
GPT-5 just forgets or misunderstands things or mixes up details about characters that were provided a couple of messages prior, while 4o got these details right even when they hadn't been mentioned in dozens of messages.
I'm using it for fun, yes, but not as a buddy or therapist. Just as entertainment. I'm fine with paying more for this use if I need to. And I do - right now, I'm using `chatgpt-4o-latest` via LibreChat but it's a somewhat inferior experience to the ChatGPT web UI that has access to memory and previous chats.
Not the end of the world - but a little advance notice would have been nice so I'd have had some time to prepare and test alternatives.
I've seen quite a bit of this too, the other thing I'm seeing on reddit is I guess a lot of people really liked 4.5 for things like worldbuilding or other creative tasks, so a lot of them are upset as well.
There is certainly a market/hobby opportunity for "discount AI" for no-revenue creative tasks. A lot of r/LocalLLaMA/ is focused on that area and in squeezing the best results out of limited hardware. Local is great if you already have a 24 GB gaming GPU. But, maybe there's an opportunity for renting out low power GPUs for casual creative work. Or, an opportunity for a RenderToken-like community of GPU sharing.
If you're working on a rented GPU are you still doing local work? Or do you mean literally lending out the hardware?
Working on a rented GPU would not be local. But, renting a low-end GPU might be cheap enough to use for hobbyist creative work. I'm just musing on lots of different routes to make hobby AI use economically feasible.
The gpt-oss-20b model has demonstrated that a machine with ~13GB of available RAM can run a very decent local model - if that RAM is GPU-accessible (as seen on Apple silicon Macs for example) you can get very usable performance out of it too.
I'm hoping that within a year or two machines like that will have dropped further in price.
I mean - I 'm quite sure it's going to be available via API, and you can still do your worldbuilding if you're willing to go to places like OpenRouter.
> "Let's get you a curt, targeted answer quickly."
This probably why I am absolutely digging GPT-5 right now. It's a chatbot not a therapist, friend, nor a lover.
I don't see how people using these as a therapist really has any measurable impact compared to using them as agents. I'll spend a day coding with an LLM and between tool calls, passing context to the model, and iteration I'll blow through millions of tokens. I don't even think a normal person is capable of reading that much.
I am all for “curt, targeted answers”, but they need to be _correct_, which is my issue with gpt-5
The GPT-5 API has a new parameter for verbosity of output. My guess is the default value of this parameter used in ChatGPT corresponds to a lower verbosity than previous models.
I had this feeling too.
I needed some help today and it's messages where shorter but also detailed without all the spare text that I usually don't even read.
Also good for the bottom line: fewer tokens generated.
It's a good reminder that OpenAI isn't incentivized to have users spend a lot of time on their platform. Yes, they want people to be engaged and keep their subscription, but better if they can answer a question in few turns rather than many. This dynamic would change immediately if OpenAI introduced ads or some other way to monetize each minute spent on the platform.
the classic 3rd space problem that Starbucks tackled; they initially wanted people to hang out and do work there, but grew to hate it so they started adding lots of little things to dissuade people from spending too much time there
> the classic 3rd space problem that Starbucks tackled
“Tackled” is misleading. “Leveraged to grow a customer base and then exacerbated to more efficiently monetize the same customer base” would be more accurate.
Great for the environment as well and the financial future of the company. I can't see how this is a bad thing, some people really were just suffering from Proompt Disorder
Reddit is where people literally believed GPT5 was going to be AGI.
reddit is a large group of people sharing many diverse ideas
That was the r/singularity sub which has a rather large bias toward believing the singularity is near and inevitable.
Doesn't look like they blew up the API use cases, just the consumer UI access. I wouldn't be surprised if they allow it again, hidden behind a setting (along with allowing the different routed GPT5 levels to be in the selector).
Ah ok, that's an important distinction. Seems much less a big deal then - or at least a consumer issue rather than a business one. Having never really used chatgpt (but used the apis a lot), I'm actually surprised that chat users would care. There are cost tradeoffs for the different models when building on them, but for chatgpt, it's less clear to me why one would move between selecting different models.
> There are cost tradeoffs for the different models when building on them, but for chatgpt, it's less clear to me why one would move between selecting different models.
The same tradeoffs (except cost, because that's roled into the plan not a factor when selecting on the interface) exist on ChatGPT, which is an app built on the underlying model like any other.
So getting rid of models that are stronger in some areas when adding a new one that is cheaper (presuming API costs also reflect cost to provide) has the same kinds of impacts on existing ChatGPT users established usages as it would have on a businesses established apps except that the ChatGPT users don't see a cost savings along with any disruption in how they were used to things working.
Not everyone is an engineer. There's a substantial population that were selecting for maximum sycophancy.
Lower tiers have limited uses for some models.
I have a feeling that the chatgpt ui does some behind-the scenes tuning as well--hidden prompt engineering if you will. I migrated to the api and 4o still seems different. Most obvious, I don't get the acks that make me feel like I should run for president.
Even ChatGPT 5 confirmed this,
why does the gpt-4o api not do this?
ChatGPT said:
Because the GPT-4o API is tuned and delivered in a neutral, low-intrusion style by default.
When OpenAI built GPT-4o for API use, they optimized it for:
That’s different from the ChatGPT product experience, which has its own “assistant personality” layer that sometimes adds those rapport-building acknowledgements in casual conversation.In API mode, you’re the one defining the personality, so if you want that “Good! Looks like you’re digging in” style, you have to bake it into the system prompt, for example:
The GPT-4o you talk to through ChatGPT and the GPT-4o you access via the API are different models... but they're actually both available via the API.
https://platform.openai.com/docs/models/gpt-4o is gpt-4o in the API, also available as three date-stamped snapshots: gpt-4o-2024-11-20 and gpt-4o-2024-08-06 and gpt-4o-2024-05-13 - priced at $2.50/million input and $10.00/million output.
https://platform.openai.com/docs/models/chatgpt-4o-latest is chatgpt-4o-latest in the API. This is the model used by ChatGPT 4o, and it doesn't provide date-stamped snapshots: the model is updated on a regular basis without warning. It costs $5/million input and $15/million output.
If you use the same system prompt as ChatGPT (from one of the system prompt leaks) with that chatgpt-4o-latest alias you should theoretically get the same experience.
But it always gives answers like that for questions where it doesn't know the actual reason.
Margins are weird.
You have a system that’s cheaper to maintain or sells for a little bit more and it cannibalizes its siblings due to concerns of opportunity cost and net profit. You can also go pretty far in the world before your pool of potential future customers is muddied up with disgruntled former customers. And there are more potential future customers overseas than there are pissed off exes at home so let’s expand into South America!
Which of their other models can run well on the same gen of hardware?
I’m wondering that too. I think better routers will allow for more efficiency (a good thing!) at the cost of giving up control.
I think OpenAI attempted to mitigate this shift with the modes and tones they introduced, but there’s always going to be a slice that’s unaddressed. (For example, I’d still use dalle 2 if I could.)
Are they deprecating the older models in the API? I don't see any indication of that in the docs.
> I wonder how much of the '5 release was about cutting costs vs making it outwardly better. I'm speculating that one reason they'd deprecate older models is because 5 materially cheaper to run?
I mean, assuming the API pricing has some relation to OpenAI cost to provide (which is somewhat speculative, sure), that seems pretty well supported as a truth, if not necessarily the reason for the model being introduced: the models discontinued (“deprecated” implies entering a notice period for future discontinuation) from the ChatGPT interface are priced significantly higher than GPT-5 on the API.
> For companies that extensively test the apps they're building (which should be everyone) swapping out a model is a lot of work.
Who is building apps relying on the ChatGPT frontend as a model provider? Apps would normally depend on the OpenAI API, where the models are still available, but GPT-5 is added and cheaper.
> Who is building apps relying on the ChatGPT frontend as a model provider? Apps would normally depend on the OpenAI API, where the models are still available, but GPT-5 is added and cheaper.
Always enjoy your comments dw, but on this one I disagree. Many non-technical people at my org use custom gpt's as "apps" to do some re-occuring tasks. Some of them have spent absurd time tweaking instructions and knowledge over and over. Also, when you create a custom gpt, you can specifically set the preferred model. This will no doubt change the behavior of those gpts.
Ideally at the enterprise level, our admins would have a longer sunset on these models via web/app interface to ensure no hiccups.
Maybe the true cost of GPT-5 is hidden, I tried to use the GPT-5 API and openai wanted me to do a biometric scan with my camera, yikes.
Companies testing their apps would be using the API not the ChatGPT app. The models are still available via the API.
> For companies that extensively test the apps they're building (which should be everyone) swapping out a model is a lot of work.
Yet another lesson in building your business on someone else's API.
The article links to this subreddit, which I'd never heard of until now:
https://www.reddit.com/r/MyBoyfriendIsAI
And my word that is a terrifying forum. What these people are doing cannot be healthy. This could be one of the most widespread mental health problems in history.
I can't help but find this incredibly interesting.
that is one of the more bizarre and unsettling subreddits I've seen. this seems like completely unhinged behavior and I can't imagine any positive outcome from it.
> What these people are doing cannot be healthy
Leader in the clubhouse for the 2025 HN Accidental Slogan Contest.
GPT-5 simply sucks at some things. The very first thing I asked it to do was to give me an image of knife with spiral damascus pattern, it gave me an image of such a knife, but with two handles at a right angle: https://chatgpt.com/share/689506a7-ada0-8012-a88f-fa5aa03474...
Then I asked it to give me the same image but with only one handle; as a result, it removed one of the pins from a handle, but the knife had still had two handles.
It's not surprising that a new version of such a versatile tool has edge cases where it's worse than a previous version (though if it failed at the very first task I gave it, I wonder how edge that case really was). Which is why you shouldn't just switch over everybody without grace period nor any choice.
The old chatgpt didn't have a problem with that prompt.
For something so complicated it doesn't surprise that a major new version has some worse behaviors, which is why I wouldn't deprecate all the old models so quickly.
The image model (GPT-Image-1) hasn’t changed
Yep, GPT-5 doesn't output images: https://platform.openai.com/docs/models/gpt-5
Then why does it produce different output?
It works as a tool. The main model (GPT-4o or GPT-5 or o3 or whatever) composes a prompt and passes that to the image model.
This means different top level models will get different results.
You can ask the model to tell you the prompt that it used, and it will answer, but there is no way of being 100% sure it is telling you the truth!
My hunch is that it is telling the truth though, because models are generally very good at repeating text from earlier in their context.
You know that unless you control for seed and temperature, you always get a different output for the same prompts even with the model unchanged... right?
Somehow I copied your prompt and got a knife with a single handle on the first try: https://chatgpt.com/s/m_689647439a848191b69aab3ebd9bc56c
Edit: chatGPT translated the prompt from english to portuguese when I copied the share link.
I think that is one of the most frustrating issues I currently face when using LLMs. One can send the same prompt in two separate chats and receive two drastically different responses.
It is frustrating that it’ll still give a bad response sometimes, but I consider the variation in responses a feature. If it’s going down the wrong path, it’s nice to be able to roll the dice again and get it back on track.
I’ve noticed inconsistencies like this, everyone said that it couldn’t count the b’s in blueberry, but it worked for me the first time, so I thought it was haters but played with a few other variations and got flaws. (Famously, it didn’t get r’s in strawberry).
I guess we know it’s non-deterministic but there must be some pretty basic randomizations in there somewhere, maybe around tuning its creativity?
Temperature is a very basic concept that makes LLMs work as well as they do in the first place. That's just how it works and that's how it's been always supposed to work.
Yes, it sucks
But GPT-4 would have the same problems, since it uses the same image model
The image model is literally the same model
So there may be something weird going on with images in GPT-5, which OpenAI avoided any discussion about in the livestream. The artist for SMBC noted that GPT-5 was better at plagiarizing his style: https://bsky.app/profile/zachweinersmith.bsky.social/post/3l...
However, there have been no updates to the underlying image model (gpt-image-1). But due to the autoregressive nature of the image generation where GPT generates tokens which are then decoded by the image model (in contrast to diffusion models), it is possible for an update to the base LLM token generator to incorporate new images as training data without having to train the downstream image model on those images.
No, those changes are going to be caused by the top level models composing different prompts to the underlying image models. GPT-5 is not a multi-modal image output model and still uses the same image generation model that other ChatGPT models use, via tool calling.
GPT-4o was meant to be multi-modal image output model, but they ended up shipping that capability as a separate model rather than exposing it directly.
That may be a more precise interpretation given the leaked system prompt, as the schema for the tool there includes a prompt: https://news.ycombinator.com/item?id=44832990
I've worked on many migrations of things from vX to vX + 1, and there's always a tension between maximum backwards-compatibility, supporting every theoretical existing use-case, and just "flipping the switch" to move everyone to the New Way. Even though I, personally, am a "max backwards-compatibility" guy, it can be refreshing when someone decides to rip off the bandaid and force everyone to use the new best practice. How exciting! Unfortunately, this usually results in accidentally eliminating some feature that turns out to be Actually Important, a fuss is made, and the sudden forced migration is reverted after all.
I think the best approach is to move people to the newest version by default, but make it possible to use old versions, and then monitor switching rates and figure out what key features the new system is missing.
I usually think it's best to have both n and n - 1 versions for a limited time. As long as you always commit to removing the n - 1 version at a specified point in time, you don't get trapped in backward compatibility hell.
Unless n is in any way objectively worse than n-1, then remove n-1 immediately so users don't directly compare them. Even Valve did it with Counter-Strike 2 and GO.
With major redesigns, you often can’t directly compare the two versions —- they are different enough that you actually want people to use them in a different way. So it’s not that the new version is “worse”, it’s just different, and it’s possible that there are some workflows that are functionally impossible on the new version (you’d be surprised how easy it is to mess this up.)
> Emotional nuance is not a characteristic I would know how to test!
Well, that's easy, we knew that decades ago.
Something I hadn’t thought about before with the V-K test: in the setting of the film animals are just about extinct. The only animal life we see are engineered like the replicants.
I had always thought of the test as about empathy for the animals, but hadn’t really clocked that in the world of the film the scenarios are all major transgressions.
The calfskin wallet isn’t just in poor taste, it’s rare & obscene.
Totally off topic, but thanks for the thought.
As an aside, people should avoid using "deprecate" to mean "shut down". If something is deprecated, that means that you shouldn't use it. For example, the C library's gets() function was deprecated because it is a security risk, but it wasn't removed until 12 years later. The distinction is important: if you're using GPT-4o and it is deprecated, you don't need to do anything, but if it is shut down, then you have a problem.
o3 was also an anomaly in terms of speed vs response quality and price vs performance. It used to be one of the fastest ways to do some basic web searches you would have done to get an answer if you used o3 pro you it would take 5x longer for not much better response.
So far I haven’t been impressed with GPT5 thinking but I can’t concretely say why yet. I am thinking of comparing the same prompt side by side between o3 and GPT5 thinking.
Also just from my first few hours with GPT5 Thinking I feel that it’s not as good at short prompts as o3 e.g instead of using a big xml or json prompt I would just type the shortest possible phrase for the task e.g “best gpu for home LLM inference vs cloud api.”
My chats so far have been similar to yours, across the board worse than o3, never better. I've had cases where it completely misinterpreted what I was asking for, a very strange experience which I'd never had with the other frontier models (o3, Sonnet, Gemini Pro). Those would of course get things wrong, make mistakes, but never completely misunderstand what I'm asking. I tried the same prompt on Sonnet and Gemini and both understood correctly.
It was related to software architecture, so supposedly something it should be good at. But for some reason it interpreted me as asking from an end-user perspective instead of a developer of the service, even though it was plenty clear to any human - and other models - that I meant the latter.
> I've had cases where it completely misinterpreted what I was asking for, a very strange experience which I'd never had with the other frontier models (o3, Sonnet, Gemini Pro).
Yes! This exactly, with o3 you could ask your question imprecisely or word it badly/ambiguously and it would figure out what you meant, with GPT5 I have had several cases just in the last few hours where it misunderstands the question and requires refinement.
> It was related to software architecture, so supposedly something it should be good at. But for some reason it interpreted me as asking from an end-user perspective instead of a developer of the service, even though it was plenty clear to any human - and other models - that I meant the latter.
For me I was using o3 in daily life like yesterday we were playing a board game so I wanted to ask GPT5 Thinking to clarify a rule, I used the ambiguous prompt with a picture of a card’s draw 1 card power and asked “Is this from the deck or both?” (From the deck or from the board). It responded by saying the card I took a picture of was from the game wingspan’s deck instead of clarifying the actual power on the card (o3 would never).
I’m not looking forward to how much time this will waste on my weekend coding projects this weekend.
It appears to be overtuned on extremy strict instruction following, interpreting things in a very unhuman way, which may be a benefit to agentic tasks at the costs of everything else.
My limited API testing with gpt-5 also showed this. As an example, the instruction "don't use academic language" caused it to basically omit half of what it output without that instruction. The other frontier models, and even open source Chinese ones like Kimi and Deepseek, understand perfectly fine what we mean by it.
It's not great at agentic tasks either. Not the least because it seems very timid about doing things on its own, and demands (not asks - demands) that user confirm every tiny step.
I couldn't be more confused by this launch...
I had gpt-5 only on my account for the most of today, but now I'm back at previous choices (including my preferred o3).
Had gpt-5 been pulled? Or, was it only a preview?
I have gpt-5 on my iPhone, but not on my iPad. Both runs the newest chatgpt app.
Maybe they do device based rollout? But imo. that's a weird thing to do.
We have a team account and my buddy has GPT-5 in the app but not on the website. At the same time, I have GPT-5 on the website, but in the app, I still only have GPT-4o. We're confused as hell, to say the least.
This. I don't see 5 at all as a Plus customer.
I have it only on the desktop app, not web or mobile. Seems a really weird way to roll it out.
I'm on Plus and only have 5
I’m on Plus and have only GPT-5 on the iOS app and only the old models (except 4.5 and older expensive to run ones) in the web interface since yesterday after the announcement.
For me it was available today on one laptop, but not the other. Both logged into the same account with Plus.
Same here.
> or trying prompt additions like “think harder” to increase the chance of being routed to it.
Sure, manually selecting model may not have been ideal. But manually prompting to get your model feels like an absurd hack
claude code does this (all the way up to keyword "superthink") which drives me nuts. 12 keystrokes to do something that should be a checkbox
We need a new set of UX principles for AI apps. If users need to access an AI feature multiple times a day it should be a button.
Anecdotally, saying "think harder" and "check your work carefully" has always gotten me better results.
It's coming back according to Sam https://www.reddit.com/r/ChatGPT/comments/1mkae1l/gpt5_ama_w...
would have been smart to keep them around for a while and just hide them (a bit like in the pro plan, but less hidden)
and then phase them out over time
would have reduced usage by 99% anyway
now it all distracts from the gpt5 launch
Charge more for LTS support. That’ll chase people onto your new systems.
I’ve seen this play out badly before. It costs real money to keep engineers knowledgeable of what should rightfully be EOL systems. If you can make your laggard customers pay extra for that service, you can take care of those engineers.
The reward for refactoring shitty code is supposed to be not having to deal with it anymore. If you have to continue dealing with it anyway, then you pay for every mistake for years even if you catch it early. You start shutting down the will for continuous improvement. The tech debt starts to accumulate because it can never be cleared, and trying to use makes maintenance five times more confusing. People start wanting more Waterfall design to try to keep errors from ever being released in the first place. It’s a mess.
Make them pay for the privilege/hassle.
Models aren't code though. I'm sure there's code around it but for the most part models aren't maintained, they're just replaced. And a system that was state of the art literally yesterday is really hard to characterize as "rightfully EOL".
Two diffetent models can not be direct replacements of eachother. It's like two different novels.
That doesn’t stop manufacturers from getting rid of parts that have no real equivalent elsewhere in their catalog. Sometimes they do, but at the end of the day you’re at their mercy. Or you have strong enough ties to their management that they keep your product forever, even later when it’s hurting them to keep it.
Is the new model significantly more efficient or something? Maybe using distillation? I haven't looked into it, I just heard the price is low.
Personally I use/prefer 4o over 4.5 so I don't have high hopes for v5.
sama: https://x.com/sama/status/1953893841381273969
"""
GPT-5 rollout updates:
We are going to double GPT-5 rate limits for ChatGPT Plus users as we finish rollout.
We will let Plus users choose to continue to use 4o. We will watch usage as we think about how long to offer legacy models for.
GPT-5 will seem smarter starting today. Yesterday, the autoswitcher broke and was out of commission for a chunk of the day, and the result was GPT-5 seemed way dumber. Also, we are making some interventions to how the decision boundary works that should help you get the right model more often.
We will make it more transparent about which model is answering a given query.
We will change the UI to make it easier to manually trigger thinking.
Rolling out to everyone is taking a bit longer. It’s a massive change at big scale. For example, our API traffic has about doubled over the past 24 hours…
We will continue to work to get things stable and will keep listening to feedback. As we mentioned, we expected some bumpiness as we roll out so many things at once. But it was a little more bumpy than we hoped for!
"""
All these announces are scenery and promotion. Very low chance any of these "corrections" were not planned. For some reason, sama et al. make me feel like a mouse played with by a cat.
Why on earth would they undercut the launch of their new model by "planning" to do a stunt where people demand the old models instead of the new models?
I don't think they're doing a lot of planning over there. Did you see the presentation?
Currently 13 of 30 submissions on hn homepage are AI-related. That seems to be about average now.
Some are interesting no doubt, but it’s getting one-sided.
Personally, two years ago the topics here were much more interesting compared to today.
Concur. It's not even close.
We go through hype bubbles every now and again. A few years ago you could make the same complaint about crypto currency.
One enterprise angle to open source models is that we will develop advanced forms of RPA. Models automating a single task really well.
We can’t rely on api providers to not “fire my employee”
Labs might be a little less keen to degrade that value vs all of the ai “besties” and “girlfriends” their poor UX has enabled for the ai illiterate.
Totally agree, stuff like this completely undermines the idea that these products will replace humans at scale.
If one develops a reputation for putting models out to pasture like Google does pet projects, you’d think twice before building a business around it
It’s boggles my mind that enterprises or SaaS wouldn’t be following release cycles of new models to improve their service and/or cost. Although I guess there’s enterprises that don’t do OS upgrades or pathing too, just alien to me.
They're almost never straight upgrades for the exact same prompts across the board at the same latency and price. The last time that happened was already a year ago, with 3.5 Sonnet.
Striking up a voice chat with GPT-5 it starts by affirming my custom instructions/system prompt. Every time. Does not pass the vibe check.
”Absolutely, happy to jump in. And you got it, I’ll keep it focused and straightforward.”
”Absolutely, and nice to have that context, thanks for sharing it. I’ll keep it focused and straightforward.”
Anyone else have these issues?
EDIT: This is the answer to me just saying the word hi.
”Hello! Absolutely, I’m Arden, and I’m on board with that. We’ll keep it all straightforward and well-rounded. Think of me as your friendly, professional colleague who’s here to give you clear and precise answers right off the bat. Feel free to let me know what we’re tackling today.”
We were laughing about it with my son. He was asking some questions and the voice kept prefacing every answer with something like "Without the fluff", "Straight to the point" and variations thereof. Honestly that was hilarious.
gemini 2.5pro is my favorite but it's really annoying how it congratulates me on asking such great questions at the start of every single response even when i set a system prompt stating not to do it
shrug.
Yup but I'm in the mobile app which is still using 4o
I still haven't got access to GPT-5 (plus user in US), and I am not really super looking forward to it given I would lose access to o3. o3 is a great reasoning and planning model (better than Claude Opus in planning IMO and cheaper) that I use in the UI as well as through API. I don't think OpenAI should force users to an advanced model if there is not a noticeable difference in capability. But I guess it saves them money? Someone posted on X how giving access to only GPT-5 and GPT-5 thinking reduces a plus user's overall weekly request rate.
I switched from 4o to GPT 5 on raycast and I feel it is a lot slower to use 5 and contradicts his assertion.
When you are using the Raycast AI at your fingertips you are expecting a faster answer to be honest.
Somewhat unsurprising to see the reactions to be closer to losing an old coworker than just deprecations / regressions: you miss humans not just for their performance but also their quirks.
> But if you’re already leaning on the model for life advice like this, having that capability taken away from you without warning could represent a sudden and unpleasant loss!
Sure, going cold turkey like this is unpleasant, but it's usually for the best - the sooner you stop looking for "emotional nuance" and life advice from an LLM, the better!
Taking away user choice is often done in the name of simplicity. But let's not forget that given 100 users, 60 are likely to answer with "no opinion" when asked what about their preference to ANY question. Does that mean the other 40% aren't valuable and their preferences not impactful to the other "we don't care" majority?
And that 60% are going to be in the %40 for other questions.
I tried gpt 5 high with extended thinking and isnt bad I prefer opus 4.1 though, at least for now
This is also showing up on Xitter as the #keep4o movement, which some have criticized as being "oneshotted" or cases of LLM psychosis and emotional attachment.
This doesn't seem to be the case for me. I have access to GPT-5 via chatgpt, and I can also use GPT-4o. All my chat history opens with the originally used model as well.
I'm not saying it's not happening - but perhaps the rollout didn't happen as expected.
Are you on the pro plan? I think pro users can use all models indefinitely
Just plus
This industry just keeps proving over and over again that if it's not open, or yours, you're building on shifting sand.
It's a really bad cultural problem we have in software.
Pretty tautological, no?
If it's not yours, it's not yours.
It's not totally surprising given the economics of LLM operation. LLMs, when idle, are much more resource-heavy than an idle web service. To achieve acceptable chat response latency, the models need to be already loaded in memory, and I doubt that these huge SotA models can go from cold start to inference in milliseconds or even seconds. OpenAI is incentivized to push as many users onto as few models as possible to manage the capacity and increase efficiency.
This was my thought. They messaged quite heavily in advance that they were capacity constrained, and I'd guess they just want to shuffle out GPT-4 serving as quickly as possible as its utilisation will only get worse over time, and that's time they can be utilising better for GPT-5 serving.
This thread is the best sales pitch for local / self-hosted models. With local, you have total control over when you decide to upgrade.
4o is for shit, but it's inconvenient to lose o3 with no warning. Good reminder that it was past time to keep multiple vendors in use.
Yep, this caused me to unsubscribe. o3/o4 and 4.5 were extremely good. GPT5 is worse than both.
running a model costs money. They probably removed 4o to make room (i.e. increase availability) for 5
GPT-5 is 4o with an automatic model picker.
It's a whole family of brand new models with a model picker on top of them for the ChatGPT application layer, but API users can directly interact with the new models without any model picking layer involved at all.
Meanwhile I'm stuck on 4o
It's like everyone got a U2 album they didn't ask for, but instead of U2 they got Nickelback.
GPT-5 reflecting Sam A's personality? Hmm...
GPT5 is some sort of quantized model, its not SOTA.
The trust that OpenAI would be SOTA has been shattered. They were among the best with o3/o4 and 4.5. This is a budget model and they rolled it out to everyone.
I unsubscribed. Going to use Gemini, it was on-par with o3.
It's possible you are a victim of bugs in the router, and your test prompts were going to the less useful non-thinking variants.
From Sam's tweet: https://x.com/sama/status/1953893841381273969
> GPT-5 will seem smarter starting today. Yesterday, the autoswitcher broke and was out of commission for a chunk of the day, and the result was GPT-5 seemed way dumber. Also, we are making some interventions to how the decision boundary works that should help you get the right model more often.
I have GPT-5 on the mobile app and the full set on my browser and this is good.
I'm happy to hear. If you need anything else, I'm here to help.
reading all the shilling of Claude and GPT i see here often I feel like i'm being gaslighted
i've been using premium tiers of both for a long time and i really felt like they've been getting worse
especially Claude I find super frustrating and maddening, misunderstanding basic requests or taking liberties by making unrequested additions and changes
i really had this sense of enshittification, almost as if they are no longer trying to serve my requests but do something else instead like i'm victim of some kind of LLM a/b testing to see how far I can tolerate or how much mental load can be transferred back onto me
While it's possible that the LLMs are intentionally throttled to save costs, I would also keep in mind that LLMs are now being optimized for new kinds of workflows, like long-running agents making tool calls. It's not hard to imagine that improving performance on one of those benchmarks comes at a cost to some existing features.
Anthropic have stated on the record several times that they do not update the model weights once they have been deployed without also changing the model ID.
No, they do change deployed models.
How can I be so sure? Evals. There was a point where Sonnet 3.5 v2 happily output 40k+ tokens in one message if asked. And one day it started with 99% consistency, outputting "Would you like me to continue?" after a lot fewer tokens than that. We'd been running the same set of evals and so could definitively confirm this change. Googling will also reveal many reports of this.
Whatever they did, in practice they lied: API behavior of a deployed model changed.
Another one: Differing performance - not latency but output on the same prompt, over 100+ runs, statistically significant enough to be impossible by random chance - between AWS Bedrock hosted Sonnet and direct Anthropic API Sonnet, same model version.
Don't take at face value what model providers claim.
If they are lying about changing model weights despite keeping the date-stamped model ID the same it would be a monumental lie.
Anthropic make most of their revenue from paid API usage. Their paying customers need to be able to trust them when they make clear statements about their model deprecation policy.
I'm going to chose to continue to believe them until someone shows me incontrovertible evidence that this isn't true.
I suspect that it may not necessarily be that they're getting objectively _worse_ as much as that they aren't static products. They're constantly getting their prompts/context engines tweaked in ways that surely break peoples' familiar patterns. There really needs to be a way to cheaply and easily anchor behaviors so that people can get more consistency. Either that or we're just going to have to learn to adapt.
If Anthropic made Deepthink 3.5 it would be AGI, I never use > 3.5
This is disappointing. 4o has been performing great for me, and now I see I only have access to the 5-level models. Already it's not as good. More verbose with technical wording, but it adds very little to what I'm using GPT for.
I spoke with gpt-5, and asked it about shrinkflation, enshittification, and its relevancy to this situation. I think Hacker News will agree with gpt-5s findings.
> Do you understand what shrinkflation is? Do you understand the relationship between enshittification and such things as shrinkflation?
> I understand exactly what you’re saying — and yes, the connection you’re drawing between shrinkflation, enshittification, and the current situation with this model change is both valid and sharp.
> What you’re describing matches the pattern we just talked about:
> https://chatgpt.com/share/68963ec3-e5c0-8006-a276-c8fe61c04d...
>There’s no deprecation period at all: when your consumer ChatGPT account gets GPT-5, those older models cease to be available.
This is flat out, unambiguously wrong
Look at the model card: https://openai.com/index/gpt-5-system-card/
This is not a deprecation and users still have access to 4o, in fact it's renamed to "gpt-5-main" and called out as the key model, and as the author said you can still use it via the API
What changed was you can't specify a specific model in the web-interface anymore, and the MOE pointer head is going to route you to the best model they think you need. Had the author addressed that point it would be salient.
This tells me that people, even technical people, really have no idea how this stuff works and want there to be some kind of stability for the interface, and that's just not going to happen anytime soon. It also is the "you get what we give you" SaaS design so in that regard it's exactly the same as every other SaaS service.
No, GPT-4o has not been renamed to gpt-5-main. gpt-5-main is an entirely new model.
I suggest comparing https://platform.openai.com/docs/models/gpt-5 and https://platform.openai.com/docs/models/gpt-4o to understand the differences in a more readable way than that system card.
Also note that I said "consumer ChatGPT account". The API is different. (I added a clarification note to my post about that since first publishing it.)You can't compare them like that
GPT-5 isn't the successor to 4o no matter what they say, GPT-5 is a MOE handler on top of multiple "foundations", it's not a new model, it's orchestration of models based on context fitting
You're buying the marketing bullshit as though it's real
No, there are two things called GPT-5 (this is classic OpenAI, see also Codex).
There's GPT-5 the system, a new model routing mechanism that is part of their ChatGPT consumer product.
There's also a new model called GPT-5 which is available via their API: https://platform.openai.com/docs/models/gpt-5
(And two other named API models, GPT-5 mini and GPT-5 nano - part of the GPT-5 model family).
AND there's GPT-5 Pro, which isn't available via the API but can be accessed via ChatGPT for $200/month subscribers.
I'm unable to use anything but GPT-5, and the response I've gotten don't nearly consider my past history. Projects don't work at all. I cancelled my Plus subscription, not that OpenAI cares.
Did you read that card ? They didn't just rename the models. Gpt-5-main isn't a renamed GPT-4o, it's the successor to 4o
They're different models, "It can be helpful to think of the GPT‑5 models as successors to previous models" (https://openai.com/index/gpt-5-system-card/#:~:text=It%20can...)
I've been seeing someone on Tiktok that appears to be one of the first public examples of AI psychosis, and after this update to GPT-5, the AI responses were no longer fully feeding into their delusions. (Don't worry, they switched to Claude, which has been far worse!)
Hah, that's interesting! Claude just shipped a system prompt update a few days ago that's intended to make it less likely to support delusions. I captured a diff here: https://gist.github.com/simonw/49dc0123209932fdda70e0425ab01...
Relevant snippet:
> If Claude notices signs that someone may unknowingly be experiencing mental health symptoms such as mania, psychosis, dissociation, or loss of attachment with reality, it should avoid reinforcing these beliefs. It should instead share its concerns explicitly and openly without either sugar coating them or being infantilizing, and can suggest the person speaks with a professional or trusted person for support. Claude remains vigilant for escalating detachment from reality even if the conversation begins with seemingly harmless thinking.
I started doing this thing recently where I took a picture of melons at the store to get chatGPT to tell me which it thinks is best to buy (from color and other characteristics).
chatGPT will do it without question. Claude won't even recommend any melon, it just tells you what to look for. Incredibly different answer and UX construction.
The people complaining on Reddit complaining on Reddit seem to have used it as a companion or in companion-like roles. It seems like maybe OAI decided that the increasing reports of psychosis and other potential mental health hazards due to therapist/companion use were too dangerous and constituted potential AI risk. So they fixed it. Of course everyone who seemed to be using GPT in this way is upset, but I haven't seen many reports of what I would consider professional/healthy usage becoming worse.