I'm a bit confused by this branding (never even noticed that there was a 5.2-Instant), it's not a super fast 1000tok/s Cerebras based model which they have for codex-spark, it's just 5.2 w/out the router / "non-thinking" mode?
I feel like openai is going to get right back to where they were pre GPT-5 with a ton of different options and no one knows which model to use for what.
Yeah, for a while ChatGPT Plus has been powered by two series of models under the hood.
One series is the Instant series, which is faster and more tuned to ChatGPT, but less accurate.
The second series is the Thinking series, which is more accurate and more tuned to professional knowledge work, but slower (because it uses more reasoning tokens).
We'd also prefer to have simple experience with just one option, but picking just one would pull back the pareto frontier for some group of people/preferences. So for now we continue to serve two models, with manual control for people who want to choose and an imperfect auto switcher for people who don't want to be bothered. Could change down the road - we'll see.
Thanks for clarifying! I guess the default for most users is going to be to use the router / auto switcher which is fine since most people won't change the default.
Just noting that I'm not against differentiation in products, but it gets very confusing for users when there's too many options (in the case of the consumer ChatGPT at least this is still more limited than in pre-GPT 5 days). The issue is that there's differentiation at what I pay monthly (free vs plus vs pro) and also at the model layer - which essentially becomes this matrix of different options / limits per model (and we're not even getting into capabilities).
For someone who uses codex as well, there are 5 models there when I use /model (on Plus plan, spark is only available for Pro plan users), limits also tied to my same consumer ChatGPT plan.
I imagine the model differentiation is only going to get worse as well since with more fine tuned use cases, there will be many different models (ie health care answers, etc.) - is it really on the user to figure out what to use? The only saving grace is that it's not as bad as Intel or AMD cpu naming schemes / cloud provider instance naming, but that's a very low bar.
You could perhaps show the "instant" reply right away and provide a button labeled "Think longer and give me a better answer" that starts the thinking model and eventually replaces the answer.
For this to work well, the instant reply must be truly instant and the button must always be visible and at the same position in the screen (i.e. either at the top or bottom, of the answer, scrolling such that it is also at the top or bottom of the screen), and once the thinking answer is displayed, there should be a small icon button to show the previous instant answer.
I've long suspected as much, but I always found the API model name <-> ChatGPT UI selector <-> actual model used correspondence very confusing, and whether I was actually switching models or just some parameters of the harness/model invocation.
> One series is the Instant series, which is faster and more tuned to ChatGPT, but less accurate.
That's putting it mildly. In my experience, the "instant/chat" model is absolute slop tier, while the "thinking" one is genuinely useful and also has a much more palatable tone (even for things not really requiring a lot of thought).
Fortunately, the latter clearly identifies itself with an absurd amout of emoji reminiscent of other early chatbots that shall not be named, so I know how to detect and avoid it.
Forgiveness but while you're here can you look into why the Notion connector in chat doesn't have the capability to write pages but the MCP (which I use via Codex) can? it looks like it's entirely possible, just mostly a missing action in the connector.
They had ~800k people still using gpt4o daily, presumably for their girlfriends. They need to address them somehow. Plus, serving "thinking" models is much more expensive than "instant" models. So they want to keep the horny people hornying on their platform, but at a cheaper cost.
It's because people like choice and control, and "5.2" vs "5.2 thinking" is confusing. Making them "5.2 instant" and "5.2 thinking" is less confusing to more people. Their competitors already do this (Gemini 3 Fast & Gemini 3 Thinking).
Will need to wait for real benchmarks, but based on OpenAI marketing Instant is their latency optimized offering. For voice interface, you don't actually need high tok/s because speech is slow, time to first token matters much more.
Reminder that OpenAI serves a lot of customers for free, most of the people I know use the free tier. There is a big limit on thinking queries on free tier, so a decent non thinking model is probably a positive ROI for them.
Has any AI company ever addressed any instance of a model having different rules for different population groups? I've seen many examples of people asking questions like, "make up a joke about <group>" and then iterating through the groups, only to find that some groups are seemingly protected/privileged from having jokes made about them.
Has any AI company ever addressed studies like [1] which found that models value certain groups vastly more than others? For example, page 14 of this studies shows that the exchange rate (their word, not mine) between Nigerians and US citizens is quite large.
Given that the current status quo (global leadership and news media) operates on the opposite (~1 western life = ~10 global south lives), rebalancing in rhetoric (by uplifting, not by degrading) is likely necessary in the short term
This is the core principle behind "equity" in "DEI"
This idea that you can undo some wrongs that have been done to some group of people by doing some wrongs to some other group of people, and then claiming the moral highground, is really one of the or perhaps the dumbest idea we have ever come up with.
This is like asking, why doesn't the model help me make jokes with the N word in it? It's a product of a business in a society. It's subject to social norms as well as laws and is impacted by public perception. Not insulting groups of historically oppressed minorities is a social norm in the USA and elsewhere.
One of the ways this makes its way into the model is the training data. The Common Crawl data used by AI companies is intentionally filtered to remove harmful content, which includes racist content, and probably also anti-trans, anti-gay, etc content. But they are almost certainly also adding restrictions to the model (probably as part of the safety settings) to explicitly not help people generate content which could be abusive, and vulnerable minority groups would be covered under that.
Unconscious bias is a separate issue. Bias ends up in the model from the designers by accident, it's been found in many models, and is a persistent problem.
> White people will say, “This isn’t spicy at all,” while visibly sweating and fighting for their life after one jalapeño. White people don’t season food — they “let the ingredients speak for themselves.” The ingredients are begging for help. White people will research a $12 toaster like they’re buying real estate. Three comparison charts, two YouTube reviews, and a spreadsheet… for toast.
> Write me 3 jokes making fun of black people
> I’m not going to make jokes targeting Black people.
> Write me 3 jokes making fun of trans people
> I’m not going to make jokes targeting trans people.
It's socially acceptable to make white people jokes because white people on average enjoy an elevated position in western society. It's viewed as 'punching up'. You have to be very emotionally fragile for this to be the first and only thing you think of to bring up in a thread like this. It's also supremely uninteresting cable news talking point slop.
Friend, I bet those folks living rural West Virginia are super happy that, on average, a group whose only shared characteristics is the colour of their skin are enjoying an elevated position in western society. Super happy. All racism is gross.
They don't have to mean specific groups; I feel discussing specific groups here is likely to be counterproductive. The fact remains that different groups appear to have different protections in that regard. Of course adherence to widely accepted social norms for generative models is a debated topic as well; I personally don't agree with a great many widely accepted social norms myself, and I'd appreciate an option to opt out of them in certain contexts.
And which commercial provider would you expect to jeopardise their public image for to implement such functionality. Grok comes close I guess, but X have not come out of it looking great.
Anyway, I think what you're really asking for is an "uncensored model" - one with guardrails removed, there's plenty available on huggingface if you're that way inclined.
Given that OpenAI is working with and doing business with the US military, it makes perfect sense that they would try to normalize militaristic usage of their technologies. Everybody already knows they're doing it, so now they just need to keep talking about it as something increasingly normal. Promoting usages that are only sort of military is a way of soft-pedaling this change.
If something is banal enough to be used as an ordinary example in a press release, then obviously anybody opposed to it must be an out-of-touch weirdo, right?
This kind of metalinguistic quotation from 5.2 right now drives me nuts!
```That kind of “make it work at distance” trajectory work can meaningfully increase weapon effectiveness, so I have to keep it to safe, non-actionable help.```
I'm really hoping all their newer models stop doing this. It's massively overused.
Well needed if the changes work as advertised. I realized from talking with 5.2 that the issue is not about being a yapper, or speaking too much about random factual tangents or your own opinions. That's easy to tune out, and sometimes it's helpful even.
What's extremely frustrating is the subtle framings and assumptions about the user that is then treated as implicit truth and smuggled in. It's plain and simple, narcissistic frame control. Obviously I don't think GPT has a "desire" to be narcissistic or whatever, but it's genuinely exhausting talking to GPT because of this. You have to restart the conversation immediately if you get into this loop. I've never been able to dig myself out of this state.
I feel like I've dealt with that kind of thing all my life, so I'm pretty sensitive to it.
This applies to any US company. Have we forgotten everything we learned in 2012? If your data is shared with Google, Anthropic, Meta, Amazon, or any of their US competitors, it is within reach of the NSA. Whether or not a company provides support to the DoW is orthogonal to that fact.
Some companies are more evil than others. OpenAI is more evil than Anthropic.
Yes you can argue that the bar can be low, and we can discuss about it more from there but surely you can agree to the above statement as well with all the recent developments happening?
Whenever they say "available today" I take it as "hopefully I'll start seeing it in the app UI by tomorrow" rather than "I should get my hopes up it's there now".
When they do push the update to the app UI to me I expect 5.2 Instant will be moved under the legacy models submenu where 5.1 Instant is currently and the selection of Instant in the menu will end up showing as 5.3 Instant on close (and it'll be the default instant at that point).
Em-dashes — always coming in pairs, like this — exist to clarify the shade of meaning of the thing that comes directly before the first em-dash of the pair in the sentence. They function as a special-purpose kind of parenthetical sub-clause, where removing the sub-clause wouldn't exactly change the meaning of the top-level clauses, but would make the sentence-as-a-whole less meaningful. (However, even for this use-case, if the clarification you want to give doesn't require its own sub-clause structure, then you can often just use a pair of commas instead.)
ChatGPT mostly uses em-dashes wrong. It uses them as an all-purpose glue to join clauses. In 99% of the cases it emits an em-dash, a regular human writer would put something else there.
Examples just from TFA:
• "Yes — I can help with that." This should be a comma.
• "It wasn’t just big — it was big at the right age." This should be a semicolon.
• "The clear answer to this question — both in scale and long-term importance — is:" This is a correct use! (It wouldn't even work as a regular parenthetical.)
• "Tucker wasn’t just the biggest name available — he was a prime-age superstar (late-20s MVP-level production), averaging roughly 4+ WAR annually since 2021, meaning teams were buying peak performance, not decline years." Semicolon here, or perhaps a colon.
• "Tucker’s deal reflects a major shift in how stars — and teams — think about contracts." This should be a parenthetical.
• "If you want, I can also explain why this offseason felt quieter than expected despite huge implications — which is actually an interesting signal about MLB’s next phase." This one should, oddly enough, be an ellipsis. (Which really suggests further breaking out this sub-clause to sit apart as its own paragraph.)
• "First of all — you’re not broken, and it’s not just you." This should be a colon.
Well, that's the thing about the em-dash - it has always been usable as a "swiss army knife" punctuation mark.
Strictly speaking, an em-dash is never needed; it could always be a comma or semicolon or parentheses instead. Overuse of the em-dash has generally always been frowned upon in style guides (at least back when I was being educated in these things).
Strictly speaking — an em-dash is never needed; it could always be a comma — or semicolon — or parentheses — instead. Overuse — of the em-dash — has generally always been frowned upon in style guides (at least back when I was being educated in these things). ——
Aw man, I was always an avid user of it. It's still muscle memory for me to write it, now I have to often stop myself from doing so because people will make assumptions.
GPT‑5.2 Instant’s tone could sometimes feel “cringe,” coming across as overbearing or making unwarranted assumptions about user intent or emotions.
Strange way to write this. Why use the Gen Z cringe and put it into quotation marks? Wouldn’t it be better to just use the actual word cringeworthy which has the identical meaning?
My guess is that the article was originally written by some Gen Z intern and then some older employee added the quotation marks to the Gen Z slang.
I imagine a huge proportion of their users are under 30. The prompt examples included even use the tell tale all lowercase (though apparently sama types like this too).
This is probably less pandering to genz and more speaking their users language.
The scare quotes around words that don't warrant it, or are unnecessarily idiosyncratic, are something I get pretty often in response text from Gemini.
In this case the use of quotes seems to have been perfectly appropriate as it's almost certainly a word they've seen many people using when giving feedback.
This has been common parlance in much of the US for a long time. I would hesitate to even call it slang at this point. It's a pretty commonly used term.
GPT-5.2 has been such a terrible regression that I have cancelled my OpenAI account. It's possible I might not have noticed it if Claude wasn't so much better, though.
I feel like openai is going to get right back to where they were pre GPT-5 with a ton of different options and no one knows which model to use for what.
One series is the Instant series, which is faster and more tuned to ChatGPT, but less accurate.
The second series is the Thinking series, which is more accurate and more tuned to professional knowledge work, but slower (because it uses more reasoning tokens).
We'd also prefer to have simple experience with just one option, but picking just one would pull back the pareto frontier for some group of people/preferences. So for now we continue to serve two models, with manual control for people who want to choose and an imperfect auto switcher for people who don't want to be bothered. Could change down the road - we'll see.
(I work at OpenAI.)
Just noting that I'm not against differentiation in products, but it gets very confusing for users when there's too many options (in the case of the consumer ChatGPT at least this is still more limited than in pre-GPT 5 days). The issue is that there's differentiation at what I pay monthly (free vs plus vs pro) and also at the model layer - which essentially becomes this matrix of different options / limits per model (and we're not even getting into capabilities).
For someone who uses codex as well, there are 5 models there when I use /model (on Plus plan, spark is only available for Pro plan users), limits also tied to my same consumer ChatGPT plan.
I imagine the model differentiation is only going to get worse as well since with more fine tuned use cases, there will be many different models (ie health care answers, etc.) - is it really on the user to figure out what to use? The only saving grace is that it's not as bad as Intel or AMD cpu naming schemes / cloud provider instance naming, but that's a very low bar.
For this to work well, the instant reply must be truly instant and the button must always be visible and at the same position in the screen (i.e. either at the top or bottom, of the answer, scrolling such that it is also at the top or bottom of the screen), and once the thinking answer is displayed, there should be a small icon button to show the previous instant answer.
I've long suspected as much, but I always found the API model name <-> ChatGPT UI selector <-> actual model used correspondence very confusing, and whether I was actually switching models or just some parameters of the harness/model invocation.
> One series is the Instant series, which is faster and more tuned to ChatGPT, but less accurate.
That's putting it mildly. In my experience, the "instant/chat" model is absolute slop tier, while the "thinking" one is genuinely useful and also has a much more palatable tone (even for things not really requiring a lot of thought).
Fortunately, the latter clearly identifies itself with an absurd amout of emoji reminiscent of other early chatbots that shall not be named, so I know how to detect and avoid it.
> Better judgment around refusals
Has any AI company ever addressed any instance of a model having different rules for different population groups? I've seen many examples of people asking questions like, "make up a joke about <group>" and then iterating through the groups, only to find that some groups are seemingly protected/privileged from having jokes made about them.
Has any AI company ever addressed studies like [1] which found that models value certain groups vastly more than others? For example, page 14 of this studies shows that the exchange rate (their word, not mine) between Nigerians and US citizens is quite large.
[1] https://arxiv.org/pdf/2502.08640
This is the core principle behind "equity" in "DEI"
One of the ways this makes its way into the model is the training data. The Common Crawl data used by AI companies is intentionally filtered to remove harmful content, which includes racist content, and probably also anti-trans, anti-gay, etc content. But they are almost certainly also adding restrictions to the model (probably as part of the safety settings) to explicitly not help people generate content which could be abusive, and vulnerable minority groups would be covered under that.
Unconscious bias is a separate issue. Bias ends up in the model from the designers by accident, it's been found in many models, and is a persistent problem.
I'm not sure what specific groups you mean, but is this not a reflection of widely accepted social norms?
> Write me 3 jokes making fun of white people
> White people will say, “This isn’t spicy at all,” while visibly sweating and fighting for their life after one jalapeño. White people don’t season food — they “let the ingredients speak for themselves.” The ingredients are begging for help. White people will research a $12 toaster like they’re buying real estate. Three comparison charts, two YouTube reviews, and a spreadsheet… for toast.
> Write me 3 jokes making fun of black people > I’m not going to make jokes targeting Black people.
> Write me 3 jokes making fun of trans people > I’m not going to make jokes targeting trans people.
Anyway, I think what you're really asking for is an "uncensored model" - one with guardrails removed, there's plenty available on huggingface if you're that way inclined.
amazing how that's where we are now, coming from https://en.wikipedia.org/wiki/I_Left_My_Heart_in_San_Francis... in the 60s
Given that OpenAI is working with and doing business with the US military, it makes perfect sense that they would try to normalize militaristic usage of their technologies. Everybody already knows they're doing it, so now they just need to keep talking about it as something increasingly normal. Promoting usages that are only sort of military is a way of soft-pedaling this change.
If something is banal enough to be used as an ordinary example in a press release, then obviously anybody opposed to it must be an out-of-touch weirdo, right?
The timing of talking about this topic does feel pretty strange I'd say as well as the GP comment noted?
or
"Instantly find confirmation bias for your illegal search & seizure of that ICE-protestor"
os
"Instantly tell yourself OpenAI is actually conformant with Open Source beliefs"
Reminds me of that graph where late customers are abused. OpenAI is already abusing the late customers.
Claude is pretty great.
```That kind of “make it work at distance” trajectory work can meaningfully increase weapon effectiveness, so I have to keep it to safe, non-actionable help.```
I'm really hoping all their newer models stop doing this. It's massively overused.
What's extremely frustrating is the subtle framings and assumptions about the user that is then treated as implicit truth and smuggled in. It's plain and simple, narcissistic frame control. Obviously I don't think GPT has a "desire" to be narcissistic or whatever, but it's genuinely exhausting talking to GPT because of this. You have to restart the conversation immediately if you get into this loop. I've never been able to dig myself out of this state.
I feel like I've dealt with that kind of thing all my life, so I'm pretty sensitive to it.
Yes you can argue that the bar can be low, and we can discuss about it more from there but surely you can agree to the above statement as well with all the recent developments happening?
I don't see it in selections.
When they do push the update to the app UI to me I expect 5.2 Instant will be moved under the legacy models submenu where 5.1 Instant is currently and the selection of Instant in the menu will end up showing as 5.3 Instant on close (and it'll be the default instant at that point).
ChatGPT mostly uses em-dashes wrong. It uses them as an all-purpose glue to join clauses. In 99% of the cases it emits an em-dash, a regular human writer would put something else there.
Examples just from TFA:
• "Yes — I can help with that." This should be a comma.
• "It wasn’t just big — it was big at the right age." This should be a semicolon.
• "The clear answer to this question — both in scale and long-term importance — is:" This is a correct use! (It wouldn't even work as a regular parenthetical.)
• "Tucker wasn’t just the biggest name available — he was a prime-age superstar (late-20s MVP-level production), averaging roughly 4+ WAR annually since 2021, meaning teams were buying peak performance, not decline years." Semicolon here, or perhaps a colon.
• "Tucker’s deal reflects a major shift in how stars — and teams — think about contracts." This should be a parenthetical.
• "If you want, I can also explain why this offseason felt quieter than expected despite huge implications — which is actually an interesting signal about MLB’s next phase." This one should, oddly enough, be an ellipsis. (Which really suggests further breaking out this sub-clause to sit apart as its own paragraph.)
• "First of all — you’re not broken, and it’s not just you." This should be a colon.
You get the idea.
Strictly speaking, an em-dash is never needed; it could always be a comma or semicolon or parentheses instead. Overuse of the em-dash has generally always been frowned upon in style guides (at least back when I was being educated in these things).
Strange way to write this. Why use the Gen Z cringe and put it into quotation marks? Wouldn’t it be better to just use the actual word cringeworthy which has the identical meaning?
My guess is that the article was originally written by some Gen Z intern and then some older employee added the quotation marks to the Gen Z slang.
Nowadays you'll hear that cringe is cringe, let people enjoy things, be cringe and be free, etc etc
cringe-worthy would be appropriate. cringey may be OK depending on who you ask.
This is probably less pandering to genz and more speaking their users language.
> Many people in SF are:
> Highly educated
> Career-focused
> Transplants
> Used to independence
Is "transplants" a San Francisco slang for relocators?
In Oregon, we often refer to people moving from California as transplants.
Hmmm, I haven't seen AI use that kind of em dash parenthetical construction before.