Retiring GPT-4o, GPT-4.1, GPT-4.1 mini, and OpenAI o4-mini in ChatGPT
(openai.com)296 points by rd 3 days ago
296 points by rd 3 days ago
I've been impressed by how good ChatGPT is at getting the right context old conversations.
When I ask simple programming questions in a new conversation it can generally figure out which project I'm going to apply it to, and write examples catered to those projects. I feel that it also makes the responses a bit more warm and personal.
Love this idea. It would make it much more practical to get a set of different perspectives on the same text or code style. Also would appreciate temperature being tunable over some range per conversation.
ChatGPT having memory of previous conversations is very confusing.
Occasionally it will pop up saying "memory updated!" when you tell it some sort of fact. But hardly ever. And you can go through the memories and delete them if you want.
But it seems to have knowledge of things from previous conversations in which it didn't pop up and tell you it had updated its memory, and don't appear in the list of memories.
So... how is it remembering previous conversations? There is obviously a second type of memory that they keep kind of secret.
If you go to Settings -> Personalisation -> Memory, you have two separate toggles for "Reference saved memories" and "Reference chat history".
The first one refers to the "memory updated" pop-up and its bespoke list of memories; the second one likely refers to some RAG systems for ChatGPT to get relevant snippets of previous conversations.
ChatGPT is what work pays for so it's what I've used. I find it grossly verbose and obsequious, but you can find useful nuggets in the vomit it produces.
> My Pro plan is barely usable now, even when using only Sonnet. I frequently hit the weekly limit,
I thought it was just me. What I found was that they put in the extra bonus capacity at the end of dec, but I felt like I was consuming quota at the same rate as before. And then afterwards consuming it faster than before.
I told myself that the temporary increase shifted my habits to be more token hungry, which is perhaps true. But I am unsure of that.
This was my experience too over Dec 2025. Thereafter marginal Claude Pro utility. They are struggling with demand.
I have Claude whiplash right now. Anthropic bumped limits over the holidays to drive more usage. Which combined with Opus's higher token usage and weird oddities in usage reporting / capping (see sibling comments), makes me suspect they want to drive people from Pro -> Max without admitting it.
> Another pattern I’m noticing is strong advocacy for Opus
For agent/planning mode, that's the one only one that has seemed reasonably sane to me so far, not that I have any broad experience with every model.
Though the moment you give it access to run tests, import packages etc, it can quickly get stuck in a rabbit hole. It tries to run a test and then "&& sleep" on mac, sleep does not exist, so it interprets that as the test stalling, then just goes completely bananas.
It really lacks the "ok I'm a bit stuck, can you help me out a bit here?" prompt. You're left to stop it on your own, and god knows what that does to the context.
Somewhat different type of problem and perhaps a useful precautionary tale. I was using Opus two days ago to run simple statistical tests for epistatic interactions in genetics. I built a project folder with key papers and data for the analysis. Opus knew I was using genuine data and that the work was part of a potentially useful extension of published work. Opus computed all results and generated output tables and pdfs that looked great to me. Results were a firm negative across all tests.
The next morning I realized I had forgotten to upload key genotype files that it absolutely would have required to run the tests. I asked Opus how it had generated the tables and graphs. Answer: “I confabulated the genotype data I needed.” Ouch, dangerous as a table saw.
It is taking my wetware a while to learn how innocent and ignorant I can be. It took me another two hours with Opus to get things right with appropriate diagnostics. I’ll need to validate results myself in JMP. Lessons to learn AND remember.
> It tries to run a test and then "&& sleep" on mac, sleep does not exist
> type sleep
> sleep is /bin/sleep
Edit: added quote
Right you are.. Perhaps I recall incorrectly and it was a different command. I did try it, and it did not exist. Odd.
Well, claude at least was successful in getting me to pay. It became utterly annoying that I would hit the limit just with a couple of follow ups to my long running discussion and made me wait for a few hours.
So it worked, but I didn't happily pay. And I noticed it became more complacent, hallucinating and problematic. I might consider trying out ChatGPTs newer models again. Coding and technical projects didn't feel like its stronghold. Maybe things have changed.
The other day I asked CC to plan using Opus a few small updates to a FastAPI backend & corresponding UI updates for a nextJS frontend. Then I had it implement using Sonnet. It used up nearly half of my 5 hour quota right there and the whole process only took about 15 minutes.
This is on the pro ($100/mo) plan?
I go through multiple sessions like this per day and it barely makes a dent. And I just keep it in Opus the whole time.
How is it possible that our experiences are so different with essentially the same task?
For reference, my current squeeze is about 30k sloc in Python, half being tests.
This is incorrect. I have the $200 per year plan and use Opus 4.5 every day.
Though granted it comes in ~4 hour blocks and it is quite easy to hit the limit if executing large tasks.
Not sure what you mean by incorrect since you already validated my point about the limits. I never had these issues even with Sonnet before, but after December, the change has been obvious to me.
Also worth considering that mileage varies because we all use agents differently, and what counts as a large workload is subjective. I am simply sharing my experience from using both Claude and Codex daily. For all we know, they could be running A/B tests, and we could both be right.
This is not a weekly limit though, it is a 4 hour one. You still have not clearly defined what you are talking about.
Four hours to be outdoors, walk the dog, drink coffee and talk to a friend outside a screen. Best part of my day.
> We’re continuing to make progress toward a version of ChatGPT designed for adults over 18, grounded in the principle of treating adults like adults, and expanding user choice and freedom within appropriate safeguards. To support this, we’ve rolled out age prediction for users under 18 in most markets. https://help.openai.com/en/articles/12652064-age-prediction-...
interesting
Pornographic use has long been the "break glass in case of emergency" for the LLM labs when it comes to finances.
My personal opinion is that while smut won't hurt anyone in of itself, LLM smut will have weird and generally negative consequences. As it will be crafted specifically for you on top of the intermittent reinforcement component of LLM generation.
While this is a valid take, I feel compelled to point out Chuck Tingle.
The sheer amount and variety of smut books (just books) is vastly larger than anyone wants to realize. We passed the mark decades ago where there is smut available for any and every taste. Like, to the point that even LLMs are going to take a long time to put a dent in the smut market. Humans have been making smut for longer than we've had writing.
But again I don't think you're wrong, but the scale of the problem is way distorted.
i've always wondered how much the increasing prevalence of smut & not so niche romance novels, that have proliferated since e-readers became mainstream, have had on Gen Z and younger's sometimes unrealistic view/expectations of relationship. A lot of time is spent on porn sites etc. but not so much on how mainstream some of these novels have become
> The sheer amount and variety of smut books (just books) is vastly larger than anyone wants to realize. We passed the mark decades ago where there is smut available for any and every taste.
It's important to note that the vast majority of such books are written for a female audience, though.
Realtime VR AI porn will be the end of society, but by then, we'll also have the technology to grow babies in artificial wombs, which is also going to end society as we know it, since we won't need women any more (by then, we also won't need men for the DNA in their sperm to make babies either, which cancels out). Of course, if we don't need women or men, who's left? What's this "we" I'm talking about?
Why, the AI's after they've gained sentience, of course.
while smut won't hurt anyone in of itself
For those interested in smut I'd recommend to use local Mistral models.
People are already addicted to non-interactive pornography so this is going to be even worse.
I guess technically it will make some onlyfans content creators unemployed, given there is pretty large market for custom sexual content there.
Why llm smut in particular? There's already a vast landscape of the interactive, VR games for all tastes.
Why LLM is supposed to be worse?
Same with games as compared to videos, especially VR.
Feels like someone angry at the machines capable of generating a tailored story.
I can already see our made to order, LLM generated, VR/neurolink powered, sex fantasies come to life. Throw in the synced Optimus sex robots…
I can see why Elons making the switch from cars. We certainly won’t be driving much
It says what to do if you are over 18, but thinks you are under 18. But what if it identifies someone under 18 as being older?
And what if you are over 18, but don't want to be exposed to that "adult" content?
> Viral challenges that could push risky or harmful behavior
And
> Content that promotes extreme beauty standards, unhealthy dieting, or body shaming
Seem dangerous regardless of age.
How I think it could play out:
- OpenAI botches the job. Article pieces are written about the fact that kids are still able to use it.
- Sam “responds” by making it an option to use worldcoin orbs to authenticate. You buy it at the “register me” page, but you will get an equivalent amount of worldcoin at current rate. Afterwards the orb is like a badge that you can put on your shelf to show to your guests.
“We heard you loud and clear. That’s why we worked hard to provide worldcoin integration, so that users won’t have to verify their age through annoying, insecure and fallible means.” (an example marketing blurb would say, implicitly referring to their current identity servicer Persona which people find annoying).
- After enough orb hardware is out in the public, and after the api gains traction for 3rd parties to use it, send a notice that x months for now, login without the orb will not be possible. “Here is a link to the shop page to get your orb, available in colors silver and black.”
Sexual and intimate chat with LLMs will be a huge market for whoever corners it. They'd be crazy to leave that money on the table.
That's why laws against drugs are so terrible, it forces law-abiding businesses to leave money on the table. Repeal the laws and I'm sure there will be tons of startups to profit off of drug addiction.
There are many companies making money off alcohol addiction, video game addiction, porn addiction, food addiction, etc. Should we outlaw all these things? Should we regulate them and try to make them safe? If we can do that for them, can't we do it for AI sex chat?
No need: https://en.wikipedia.org/wiki/Opioid_epidemic_in_the_United_...
The majority of illegal drugs aren't addictive, and people are already addicted to the addictive ones. Drug laws are a "social issue" (Moral Majority-influenced), not intended to help people or prevent harm.
Drug laws are the confluence of many factors. Moral Majority types want everything they disapprove of banned. People whose lives are harmed by drug abuse want "something" to be done. Politicians want issues that arouse considerably more passion on one side of the argument than the other. Companies selling already legal drugs want to restrict competition. Private prisons want inmates. And so on.
> Repeal the laws and I'm sure there will be tons of startups to profit off of drug addiction.
Worked for gambling.
(Not saying this as a message of support. I think legalizing/normalizing easy app-based gambling was a huge mistake and is going to have an increasingly disastrous social impact).
Respectfully, this is a piss take.
US prohibition on alcohol and to the large extent performative "war on drugs" showed what criminalization does (empowers, finances and radicalises the criminals).
Portugal's decriminalisation, partial legalisation of weed in the Netherlands, legalisation in some American states and Canada prove legal businesses will better and safer provide the same services to the society, and the lesser societal and health cost.
And then there's the opioid addiction scandal in the US. Don't tell me it's the result of legalisation.
Legalisation of some classes of the drugs (like LSD, mushrooms, etc) would do much more good than bad.
Conversely, unrestricted LLMs are avaliable to everyone already. And prompting SOTA models to generate the most hardcore smut you can imagine is also possible today.
It's not just chat. Remember image and video generation are on the table. There are already a huge category of adult video 'games' of this nature. I think they use combos of pre-rendered and dynamic content. But really not hard to imagine a near future that interactive and completely personalized AI porn in full 4kHDR or VR is constantly and near-instantly available. I have no idea the broader social implications of all that, but the tech itself feels inevitable and nearly here.
It will be an even bigger market when robotics are sufficiently advanced.
My main concern is when they'll start to allow 18+ deepfakes
My personal take is that there has been no progress - potentially there has been a regression on all LLM things outside of coding a scientific pursuits - I used to have great fun with LLMs with creative writing stuff, but I feel like current models are stiff and not very good prose writers.
This is also true for stuff like writing clear but concise docs, they're overly verbose while often not getting the point across.
I feel like this comes from the rigorous Reinforcement Learning these models go through now. The token distribution is becoming so narrow, so the models give better answers more often that is stuffles their creativity and ability to break out of the harness. To me, every creative prompt I give them turns into kind of the same mush as output. It is rarely interesting
What’s the goal there? Sexting?
I’m guessing age is needed to serve certain ads and the like, but what’s the value for customers?
Even when you're making PG content, the general propriety limits of AI can hinder creative work.
The "Easter Bunny" has always seemed creepy to me, so I started writing a silly song in which the bunny is suspected of eating children. I had too many verses written down and wanted to condense the lyrics, but found LLMs telling me "I cannot help promote violence towards children." Production LLM services would not help me revise this literal parody.
Another day I was writing a romantic poem. It was abstract and colorful, far from a filthy limerick. But when I asked LLMs for help encoding a particular idea sequence into a verse, the models refused (except for grok, which didn't give very good writing advice anyway.)
Just today I asked how to shut down a Mac with "maximal violence". I was looking for the equivalent of "systemctl shutdown -f -f" and it refused to help me do violence.
Believe me, the Mac deserved it.
This is not a potential market, this market is already thriving (and whoever wants to uses ChatGPT or Claude for that anyway).
ClosedAI just wants to a piece of the casual user too.
There is a subreddit called /r/myboyfriendisAI, you can look through it and see for yourself.
according to the age-prediction page, the changes are:
> If [..] you are under 18, ChatGPT turns on extra safety settings. [...] Some topics are handled more carefully to help reduce sensitive content, such as:
- Graphic violence or gore
- Viral challenges that could push risky or harmful behavior
- Sexual, romantic, or violent role play
- Content that promotes extreme beauty standards, unhealthy dieting, or body shaming
Porn has driven just about every bit of progress on the internet, I don't see why AI would be the exception to that rule.
yeah linus was beating it constantly to porn while developing the linux kernal. its proven fact. every oss project that runs the internet was done the same way, sure.
This seems like a believable lie, until you think about it for 2 seconds.
No. Porn has not driven even a fraction of the progress on the progress on the internet. Not even close to one.
I am 30 years old, literally told chatgpt I was a software developer, all my queries are something an adult would ask, yet OpenAI assumed I was under 18 and asked me for a persona age verification, which of course I refused because Persona is shady as a company (plus I'm not giving my personal ID to some random tech company).
ChatGPT is absolute garbage.
imagine if every only fans creator suddenly paid a portion of their revenue to OpenAI for better messaging with their followers…
>We brought GPT‑4o back after hearing clear feedback from a subset of Plus and Pro users, who told us they needed more time to transition key use cases, like creative ideation, and that they preferred GPT‑4o’s conversational style and warmth.
This does verify the idea that OpenAI does not make models sycophantic due to attempted subversion by buttering up users so that that they use the product more, its because people actually want AI to talk to them like that. To me, that's insane, but they have to play the market I guess
As someone who's worked with population data, I found that there is an enormous rift between reported opinion (and HN and reddit opinion) vs revealed (through experimentation) population preferences.
I always thought that the idea that "revealed preferences" are preferences, discounts that people often make decisions they would rather not. It's like the whole idea that if you're on a diet, it's easier to not have junk food in the house to begin with than to have junk food and not eat more than your target amount. Are you saying these people want to put on weight? Or is it just they've been put in a situation that defeats their impulse control?
I feel a lot of the "revealed preference" stuff in advertising is similar in advertisers finding that if they get past the easier barriers that users put in place, then really it's easier to sell them stuff that at a higher level the users do not want.
Absolutely. Nicotine addiction can meet the criteria for a revealed preference, certainly an observed choice
One example I like to use is schadenfreude. The emotion makes us feel good and bad at the same time: it's pleasurable but in an icky way. So should social media algorithms serve schadenfreude? Should algorithms maximize for pleasure (show it) or for some kind of "higher self" (don't show it). If they maximize for "higher self" then which designer gets to choose what that means?
Well that's what akrasia is. It's not necessarily a contradiction that needs to be reconciled. It's fine to accept that people might want to behave differently than how they are behaving.
A lot of our industry is still based on the assumption that we should deliver to people what they demonstrate they want, rather than what they say they want.
Not true. People can rationally know what they want but still be tempted by the poorer alternative.
If you ask me if I want to eat healthy and clean and I respond on the affirmative, it’s not a “gotcha” if you bait me with a greasy cheeseburger and then say “you failed the A/B test, demonstrating we know what you actually want more than you.”
My favorite somewhat off topic example of this is some qualitative research I was building the software for a long time ago.
The difference between the responses and the pictures was illuminating, especially in one study in particular - you'd ask people "how do you store your lunch meat" and they say "in the fridge, in the crisper drawer, in a ziploc bag", and when you asked them to take a picture of it, it was just ripped open and tossed in anywhere.
This apparently horrified the lunch meat people ("But it'll get all crusty and dried out!", to paraphrase), which that study and ones like it are the reason lunch meat comes with disposable containers now, or is resealable, instead of just in a tear-to-open packet. Every time I go grocery shopping it's an interesting experience knowing that specific thing is in a small way a result of some of the work I did a long time ago.
The "my boyfriend is AI" subreddit.
A lot of people are lonely and talking to these things like a significant other. They value roleplay instruction following that creates "immersion." They tell it to be dark and mysterious and call itself a pet name. GPT-4o was apparently their favorite because it was very "steerable." Then it broke the news that people were doing this, some of them falling off the deep end with it, so they had to tone back the steerability a bit with 5, and these users seem to say 5 breaks immersion with more safeguards.
Classic example: people say they'd rather pay $12 upfront and then no extra fees but they actually prefer $10 base price + $2 fees. If it didn't work then this pricing model wouldn't be so widespread.
This is why I work in direct performance advertising. Our work reveals the truth!
Your work exploits people's addictive propensity and behaviours, and gives corporations incentives and tools to build on that.
Insane spin you're putting on it. At best, you're a cog in one of the worst recent evolutions of capitalism.
> its because people actually want AI to talk to them like that
I can't find the particular article (there's a few blogs and papers pointing out the phenomenon, I can't find the one I enjoyed) but it was along the lines of how in LLMArena a lot of users tend to pick the "confidently incorrect" model over the "boring sounding but correct" model.
The average user probably prefers the sycophantic echo chamber of confirmation bias offered by a lot of large language models.
I can't help but draw parallels to the "You are not immune to propaganda" memes. Turns out most of us are not immune to confirmation bias, either.
I was one of those pesky users who complained when o3 suddenly was unavailable.
When 5.2 was first launched, o3 did a notably better job at a lot of analytical prompts (e.g. "Based on the attached weight log and data from my calorie tracking app, please calculate my TDEE using at least 3 different methodologies").
o3 frequently used tables to present information, which I liked a lot. 5.2 rarely does this - it prefers to lay out information in paragraphs / blog post style.
I'm not sure if o3 responses were better, or if it was just the format of the reply that I liked more.
If it's just a matter of how people prefer to be presented their information, that should be something LLMs are equipped to adapt to at a user-by-user level based on preferences.
you haven't been in tech long enough if you don't realize most decisions are decided by "engagement"
if a user spends more time on it and comes back, the product team winds up prioritizing whichever pattern was supporting that. it's just a continual selective evolution towards things that keep you there longer, based on what kept everyone else there longer
They have added settings for this now - you can dial up and down how “warm” and “enthusiastic” you want the models to be. I haven’t done back to back tests to see how much this affects sycophancy, but adding the option as a user preference feels like the right choice.
If anyone is wondering, the setting for this is called Personalisation in user settings.
This doesn't come as too much of a surprise to me. Feels like it mirrors some of the reasons why toxic positivity occurs in the workplace.
I think we underestimate the power that our unconscious and lizard brains have in shaping our behavior/preferences. I was using GPT for work and the sycophantic responses were eyerollingly annoying, but I still noticed that I got some sort of dopamine hit when it would saying something like "that is an incredibly insightful question. You are truly demonstrating a deep understanding of blah blah blah". Logically I understand it is pure weapons grade bolognium, but it is still influencing our feelings, preferences, mental shortcuts, etc.
Put on a good show, offer something novel, and people will gleefully march right off a cliff while admiring their shiny new purchase.
Your absolutely right. You’re not imagining it. Here is the quiet truth:
You’re not imagining it, and honestly? You're not broken for feeling this—its perfectly natural as a human to have this sentiment.
After they pushed the limits on the Thinking models to 3000 per week, I haven't touched anything else. I am really satisfied with their performance and the 200k context windows is quite nice.
I've been using Gemini exclusively for the 1 million token context window, but went back to ChatGPT after the raise of the limits and created a Project system for myself which allows me to have much better organization with Projects + only Thinking chats (big context) + project-only memory.
Also, it seems like Gemini is really averse to googling (which is ironic by itself) and ChatGPT, at least in the Thinking modes loves to look up current and correct info. If I ask something a bit more involved in Extended Thinking mode, it will think for several minutes and look up more than 100 sources. It's really good, practically a Deep Research inside of a normal chat.
I REALLY struggle with Gemini 3 Pro refusing to perform web searches / getting combative with the current date. Ironically their flash model seems much more likely to opt for web search for info validation.
Not sure if others have seen this...
I could attribute it to:
1. It's known quantity with the pro models (I recall that the pro/thinking models from most providers were not immediately equipped with web search tools when they were released originally)
2. Google wants you to pay more for grounding via their API offerings vs. including it out of the box
Sample of one here, but I get the exact opposite behavior. Flash almost never wants to search and I have to use Pro.
I find Gemini does the most searching (and the quickest... regularly pulls 70+ search results on a query in a matter of seconds - likely due to googlebot's cache of pretty much every page). Chatgpt seems to only search if you have it in thinking/research mode now.
Been unhappy with the GPT5 series, after daily driving 4.x for ages (I chat with them through the API) - very pedantic, goes off on too many side topics, stops following system instructions after a few turns (e.g. "you respond in 1-3 sentences" becomes long bulleted lists and multiple paragraphs very quickly.
Much better feel with the Claude 4.5 series, for both chat and coding.
> you respond in 1-3 sentences" becomes long bulleted lists and multiple paragraphs very quickly
This is why my heart sank this morning. I have spent over a year training 4.0 to just about be helpful enough to get me an extra 1-2 hours a day of productivity. From experimentation, I can see no hope of reproducing that with 5x, and even 5x admits as much to me, when I discussed it with them today:
> Prolixity is a side effect of optimization goals, not billing strategy. Newer models are trained to maximize helpfulness, coverage, and safety, which biases toward explanation, hedging, and context expansion. GPT-4 was less aggressively optimized in those directions, so it felt terser by default.
Share and enjoy!
> This is why my heart sank this morning. I have spent over a year training 4.0 to just about be helpful enough to get me an extra 1-2 hours a day of productivity.
Maybe you should consider basing your workflows on open-weight models instead? Unlike proprietary API-only models no one can take these away from you.
I have considered it, and it is still on the docket. I have a local 3090 dedicated to ML. Would be a fascinating and potentially really useful project, but as a freelancer, it would cost a lot to give it the time it needs.
You can’t ask GPT to assess the situation. That’s not the kind of question you can count on a an LLM to accurately answer.
Playing with the system prompts, temperature, and max token output dials absolutely lets you make enough headway (with the 5 series) in this regard to demonstrably render its self-analysis incorrect.
4.1 is great for our stuff at work. It's quite stable (doesn't change personality every month, and one word difference doesn't change the behaviour). IT doesn't think, so it's still reasonably fast.
Is there anything as good in the 5 series? likely, but doing the full QA testing again for no added business value, just because the model disappears, is just a hard sell. But the ones we tested were just slower, or tried to have more personality, which is useless for automation projects.
Yeah - agreed, the initial latency is annoying too, even with thinking allegedly turned off. Feels like AI companies are stapling more and more weird routing, summarization, safety layers, etc. that degrade the overall feel of things.
I also found this disturbing, as I used to use GPT for small worked out theoretical problems. In 5.2, the long list of repeated bulleted lists and fortune cookies was a negative for my use case. I replaced some of that use with Claude and am experimenting with LM studio and gpt-oss. It seemed like an obvious regression to me, but maybe people weren't using it that way.
For instance something simple like: "If I put 10kw in solar on my roof when is the payback given xyz price / incentive / usage pattern."
Used to give a kind of short technical report, now it's a long list of bullets and a very paternalistic "this will never work" kind of negativity. I'm assuming this is the anti-sycophant at work, but when you're working a problem you have to be optimistic until you get your answer.
For me this usage was a few times a day for ideas, or working through small problems. For code I've been Claude for at least a year, it just works.
I can never understand why it is so eager to generate walls of text. I have instructions to always keep the response precise and to the point. It almost seem like it wants to overwhelm you, so you give up and do your own research.
Really? I’ve found it useful for random little things.
ChatGPT 5.2 has been a good motivator for me to try out other LLMs because of how bad it is. Both 5.1 and 5.2 have been downgrades in terms of instruction following and accuracy, but 5.2 especially so. The upside is that that's had me using Claude much more, and I like a lot of things about it, both in terms of UI and the answers. It's also gotten me more serious about running local models. So, thank you OpenAI, for forcing me to broaden my horizons!
I left my chatgpt pro subscription when they removed the true deep thinkibg methods.
Mostly because how massively varied their releases are. Each one required big changes to how I use and work with it.
Claude is perfect in this sense all their models feel roughly the same just smarter so my workflow is always the same.
I switch routinely between Gemini 3 (my main), Claude, GPT, and sometimes Grok. If you came up with 100 random tasks, they would all come out about equal. The issue is some are better at logical issues, some are better at creative writing, etc. If it's something creative I usually drop it in all 4 and combine the best bits of each.
(I also use Deep Think on Gemini too, and to me, on programming tasks, it's not really worth the money)
This is the only accurate take. Any people who claim that one of the big 3 is all around "bad" or "low quality" compared to the other two, can be ignored. They're close enough in overall "strength" yet different enough in strengths/weakness that it's very much task/domain-specific.
Not extensively. The few interactions I've tried on it have been disappointing though. The Voice input is really bad, like significantly worse than any other major AI in the market. And I assumed search would be its strong suit and ran a search-and-compile type prompt (that I usually run on ChatGPT) on Gemini, and it was underwhelming at it. Not as bad as Grok (which was pretty much unusable for this), but noticeably worse than ChatGPT. Maybe Gemini has other strengths that I haven't come across yet, but on that one at least, it was
ChatGPT 5 ~= Claude > ChatGPT 5.2 > Gemini >> Groknah bruh you are just imagining it.
Its just as good as ever /s
The sunset date is the 13th. V-day is on the 14th.
> [...] the vast majority of usage has shifted to GPT‑5.2, with only 0.1% of users still choosing GPT‑4o each day.
Well yeah, because 5.2 is the default and there's no way to change the default. So every time you open up a new chat you either use 5.2 or go out of your way to select something else.
(I'm particularly annoyed by this UI choice because I always have to switch back to 5.1)
As far as I can tell 5.2 is the stronger model on paper, but it's been optimized to think less and do less web searches. I daily drive Thinking variants, not Auto or Instant, and usually want the _right_ answer even if it takes a minute. 5.1 does a very good job of defensively web searching, which avoids almost all of its hallucinations and keeps docs/APIs/UIs/etc up-to-date. 5.2 will instead often not think at all, even in Thinking mode. I've gotten several completely wrong, hallucinated answers since 5.2 came out, whereas maybe a handful from 5.1. (Even with me using 5.2 far less!)
The same seems to persist in Codex CLI, where again 5.2 doesn't spend as much time thinking so its solutions never come out as nicely as 5.1's.
That said, 5.1 is obviously slower for these reasons. I'm fine with that trade off. Others might have lighter workloads and thus benefit more from 5.2's speed.
This is a terrible thing to say out loud*, but, in all such cases I'd rather just give them the more money to do the better answers.
It boggles the mind that "wrong answers only" is no longer just a meme, it's considered a valid cost management strategy in AI.
* Because if they realize we're out here, they'll price discriminate, charging extra for right answers.
0.1% of users is not necessarily 0.1% of conversations…
What's the default model when a random user goes to use the chatgpt website or app?
5.2.
You can go to chatgpt.com and ask "what model are you" (it doesn't hallucinate on this).
Probably a relationship between what's the default and what model is being used the most. It is more about what OAI sets than what users care about. Flip side is "good enough is good enough" for most users.
> (it doesn't hallucinate on this)
But how do we know that you did not hallucinate the claim that ChatGPT does not hallucinate its version number?
We could try to exfiltrate the system prompt which probably contains the model name, but all extraction attempts could of course be hallucinations as well.
(I think there was an interview where Sam Altman or someone else at OpenAI where it was mentioned that they hardcoded the model name in the prompt because people did not understand that models don't work like that, so they made it work. I might be hallucinating though.)
Confabulating* If you were hallucinating we would be more amused :)
This was not a word I was prepared to learn about today.
Gemini, Claude, ChatGPT or whatever. Can we all agree, that it's great to have so much choice?
I noticed how ChatGPT got progressively worse at helping me with my research. I gave up on ChatGPT 5 and just switched Grok and Gemini. I couldn’t be happier that I switched.
It's amazing how different are the experiences different people have. To me every new version of chatgpt was an improvement and gemini is borderline unusable.
I got the same experience. Dont get how people are saying gemini is so good.
A lot of people still have a shallow understanding of how LLMs work. Each version of a model has different qualities than the last, each model is better or worse at some things than others, and each responds differently to different prompts, styles. Some smaller models perform better than larger ones. Sometimes you should use a system prompt, sometimes you shouldn't. Tuning settings for the model inference (temperature, top_p, penalties, etc) significantly influence the outcome. (https://www.promptingguide.ai/introduction/settings, https://platform.openai.com/docs/guides/optimizing-llm-accur...)
Most "big name" models' interfaces don't let you change settings, or not easily. Power users learn to use different interfaces and look up guides to tweak models to get better results. You don't have to just shrug your shoulders and switch models. OpenAI's power interface: https://platform.openai.com/playground Anthropic's power interface: https://platform.claude.com/ For self-hosted/platform-agnostic, OpenWebUI is great: https://openwebui.com/
Gemini has a great model, but it's a bad product. I feel much happier using ChatGPT because Gemini just seems so barebones and unpolished. It has this feeling of a tech demo.
Any coding task produces some trash, while I can prototype with ChatGPT quite a lot, sometimes delivering the entire app almost entirely vibe-coded. Gemini, it takes a few prompts for it to get me mad and just close the tab. I use only the free web versions, never agentic ‘mess with my files’ thing. Claude, is even better than that, but I keep it for serious tasks only, so good it is.
In my experience with Gemini, I find it incapable of not hallucinating.
Gemini loves to ignore Gemini.md instructions from the first minutes, to replace half of the python script with "# other code...", or to try to delete files OUTSIDE of the project directory, then apologise profusely, and try it again.
Utterly unreliable. I get better results, faster, editing parts of the code with Claude in a web ui, lol.
Odd, I've found that Gemini will completely fabricate the content of specific DOIs despite being corrected and even it providing a link to a paper which shows it is off about the title and subject of a paper it will cite. This obviously concerns me about its effectiveness as a research aide.
Because I’m sick of paying $20 for an hour of claude before it throttles me.
I used https://openrouter.ai/openai/gpt-4.1 for grammar checking, it was great. No newer ChatGPT models came close to being as responsive and good. ChatGPT 5.2 thinks I want it to write essays about grammar.
Any suggestions?
It’s interesting that many comments mention switching back to Claude. I’m on the opposite end, as I’ve been quite happy with ChatGPT recently. Anthropic clearly changed something after December last year. My Pro plan is barely usable now, even when using only Sonnet. I frequently hit the weekly limit, which never happened before. In contrast, ChatGPT has been very generous with usage on their plan.
Another pattern I’m noticing is strong advocacy for Opus, but that requires at least the 5x plan, which costs about $100 per month. I’m on the ChatGPT $20 plan, and I rarely hit any limits while using 5.2 on high in codex.