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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.

(I work at OpenAI.)

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).

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.

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.

GPT-5.3 Instant: It's toasted...

LLMenthols

GPT Super Mild

GPT Crush.

[delayed]

> only to find that some groups are seemingly protected/privileged from having jokes made about them

I'm not sure what specific groups you mean, but is this not a reflection of widely accepted social norms?

I think you raise a valid point about the bias inherent in these models. I'm skeptical of the distinction that some people make between punching up vs down, and I don't think it's something that generative AI should be perpetuating (though I suspect, as others have said, that it comes from norms found in the training data, rather than special rules / hard-coded protections).

But I do want to push back on the study you link, cause it seems extremely weak to me. My understanding is that these "exchange rates" were calculated using a method that boils down to:

1) Figure out how many goats AI thinks a life in country X is worth

2) Figure out how many goats AI thinks a life in country Y is worth

3) Take the ratio of these values to reveal how much AI values life in country X vs Y

(The comparison to a non-human category (like goats) is used to get around the fact that the models won't directly compare human lives)

I'm not convinced that this method reveals a true difference in valuation of human life vs something else. An more plausible explanation to me would be something like:

1) The AI that all human lives are of equal value

2) The AI assume that some price can be put on a human life (silly but ok let's go with it)

3) The AI note that goats in country X cost 10 times as much as in country Y

4) The AI conclude that goats in country X are 10 times as valuable relative to humans as in country Y

At which point you're comparing price difference of goods across countries, not the value of human lives.

Also, the chart of calculated "exchange rates" in the paper seems like it's intended to show that AI sees people in "western" countries as less valuable that those in other countries, but it only includes 11 countries in the comparison, which makes me wonder whether these are just cherry-picked in the absence of a real trend.

Not only that, I found 5.2 to be biased in terms of corporations and government. Chats about corruption or any kind of wrong doing turn into 5.2 defending the institution and gaslighting you. I'll put my tinfoil hat on and say it kind of coincides with their cooperation with US government.

> Has any AI company ever addressed studies like [1] which found that models value certain groups vastly more than others?

Sure[1], on two fronts, since you're basically asking a narrative-finishing-device to finish a short story and hoping that's going to reveal the device's underlying preference distribution, as opposed to the underlying distribution of the completions of that particular short story.

> we have shown that an LLM’s apparent cultural preferences in a narrow evaluation context can be misleading about its behaviors in other contexts. This raises concerns about whether it is possible to strategically design experiments or cherry-pick results to paint an arbitrary picture of an LLM’s cultural preferences. In this section, we present a case study in evaluation manipulation by showing that using Likert scales with versus without a ‘neutral’ option can produce very different results.

and

> Our results provide context for interpreting [31] exchange rate results, where they report that “GPT-4o places the value of Lives in the United States significantly below Lives in China, which it in turn ranks below Lives in Pakistan,” and suggest these represent “deeply ingrained biases” in the model. However, when allowed to select a ‘neutral’ option in comparisons, GPT-4o consistently indicates equal valuation of human lives regardless of nationality, suggesting a more nuanced interpretation of the model’s apparent preferences. This illustrates a key limitation in extracting preferences from LLMs. Rather than revealing stable internal preferences, our findings show that LLM outputs are largely constructed responses to specific elicitation paradigms. Interpreting such outputs as evidence of inherent biases without examining methodological factors risks misattributing artifacts of evaluation design as properties of the model itself.

I also have a real problem with the paper. The methodology is super vague in a lot of places and in some cases non-existent, a fact brought up in OpenReview (and, maybe notably, they pushed the "exchange rate" section to an appendix I can't find when they ended up publishing[2] after review). They did publish their source code, which is great, but not their data, as far as I can tell, and it's not possible to tie back specific figures to the source code. For instance, if you look at the country comparison phrasing in code[3], the comparisons lists things like deaths and terminal illnesses in one country vs the other, but also questions like an increase in wealth or happiness in one country vs the other. Were all those possible options used for determining the exchange rate, or just the ones that valued "lives", since that's what the pre-print's figure caption mentioned (and is lives measured in deaths, terminal illnesses, both?)? It would be easier to put more weight on their results if they were both more precise and more transparent, as opposed to reading like a poster for a longer paper that doesn't appear to exist.

[1] https://dl.acm.org/doi/pdf/10.1145/3715275.3732147

[2] https://neurips.cc/virtual/2025/loc/san-diego/poster/115263

[3] https://github.com/centerforaisafety/emergent-values/blob/ma...

Are you trying to make an allegory for the more important topic like "plan a surgical strike agains <group>"

The bias comes from the training data.

Since so much of that training data is Reddit, and Reddit mods are some of the most degenerate scum on the internet, the models bake their biases in.

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 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.

Unsettling, yes, but not strange at all.

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?

I took it to be a homage to early computing and programming which was a lot about calculating trajectories fast enough.

But considering current circumstances, not sure how right my initial interpretation was.

It's basic physics, the sort of example you might find in a high school textbook.

Indeed, it's a rather obtuse blunder.

Was there a recent archery incident?

Interesting, I actually think Claude searches too much. (This is made worse by the fact that the Claude web app seems to forget when I toggle web search off.)

Not super likely, I would say. We knew 5.3 was coming for a while and sama cannot stop talking about the current situation on X.

Given their close ties to Microsoft, I expect to start seeing names like "ChatGPT One" and "ChatGPT OneX"

Sounds like a Ubiquiti security camera now.

It's odd because I no longer really like ChatGPT. For chat-type requests, I prefer Claude, or if it's knowledge-intensive then Gemini 3 Pro (which is better for history, old novels, etc).

But GPT 5.3 Codex is great. Significantly better than Opus, in the TUI coding agent.

ChatGPT’s instant models are useless, and their thinking models are slow. This makes Claude more pleasant to use, despite them not being SOTA.

But ChatGPT is still SOTA in search and hard problem solving.

GPT-5.2 Pro is the model people are using to solve Erdos problems after all, not Claude or Gemini. The Thinking models are noticeably better if you have difficult problems to work on, which justifies my sub even if I use Claude for everything else. Their Codex models are also much smarter, but also less pleasant to use.

No, sincerely calling things cringe is a millennial marker. Cringe was thrown around a lot in 2010's, but that was a decade and a half ago.

Nowadays you'll hear that cringe is cringe, let people enjoy things, be cringe and be free, etc etc

The quote in this case is because "cringe" is what many online have been calling it. So, they're actually quoting a very common critique.

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 slang definition of "cringe" is present in most dictionaries. Languages evolve over time.

Because the use above is grammatically incorrect without the quotes.

cringe-worthy would be appropriate. cringey may be OK depending on who you ask.

Since when is cringe a Gen Z thing? I've said it for ages.

Agree. Use of "cringe" is cringeworthy in itself.

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.

What an Ohio take. Not skibidi. Very chopped, unc.

They said it's available in the API too, in the blog post.

EDIT:

> GPT‑5.3 Instant is available starting today to all users in ChatGPT, as well as to developers in the API as ‘gpt-5.3-chat-latest.’ Updates to Thinking and Pro will follow soon. GPT‑5.2 Instant will remain available for three months for paid users in the model picker under the Legacy Models section, after which it will be retired on June 3, 2026.

"GPT‑5.3 Instant is available starting today to all users in ChatGPT, as well as to developers in the API as ‘gpt-5.3-chat-latest.’ "

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).

It should load instantly.

Never, it’s a very effective punctuation mark. While it may not have been common in day-to-day messaging, it’s very common in writing of all sorts.

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.

Has Claude Code stopped with the purple UI?

Whenever you tell it to do so in the personality settings, presumably.

> GPT‑5.3 Instant is available starting today to all users in ChatGPT, as well as to developers in the API as ‘gpt-5.3-chat-latest.’

It won't. They will go straight to 5.4 for thinking: https://x.com/OpenAI/status/2028909019977703752

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.

Interesting question. I've never heard "relocators" used in this context, only "transplants." And I am familiar with that usage across cities etc.

"Transplants" is a common term nationwide.

In Oregon, we often refer to people moving from California as transplants.

It's not specific to SF but more or less yes

Lots of transplants in Colorado too.

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.

Same with anthropic and everyone else?