Everything Since o1

People date things from o1. A writer arguing with people who formed negative opinions of language models before reasoning models existed, and who "refuse to update their views," calls o1 the model that "changed EVERYTHING," while someone else says that trying o1 was all it took to know the world was going to change, fast, and that it would be messy.

In personal accounts the o-series is remembered by what it did for one person. One writer says o3 was a game changer because it would explain high-level biology concepts "like I was talking to the professor." The praise is for a role the model filled. Someone else says that after specialists had struggled for years to diagnose their partner's chronic condition, o3 took the part of the medical history the couple had written up themselves and identified the rare condition, and that "ChatGPT was a better neurologist." Neither account is about a benchmark.

Yardsticks age quickly, and the posts say so. One post uses o3 as the fixed point for the falling "cost of thought": it says o3, released in January 2025, was the first model to clear a set score on a math benchmark, and that this summer another model did the same for a small fraction of the price. A landmark is useful because it holds still while everything around it moves. Another writer makes the point from the reader's side: OpenAI serves o3 on its API, it was talked about as a crazy model when it appeared, and it would feel like "a dumb pipe" to someone whose standard has since moved.

The argument people have about o1 is whether it broke a pattern or began one. One writer says little changed from the original GPT-4 to o1 and that "diminishing returns are not happening," while another, consoling someone, says everything since o1 has been "an extrapolation of the same idea," with "the volume dial increasingly turned up," and that o1, Gemini 2.5 and Astra are "all basically the same idea." One sees a break, the other a long line, and both date it from the same model.

For some, the o-series is also a high-water mark. One person says the o-series models were "phenomenal compared to GPT 5." This is a different claim from the one about dates: the o-series here is not where progress began but where something valued was at its best. Loss comes into it too. Someone upset that a model is being removed says that after o3 and 4.5 were removed, 5.5 thinking was the one that "somewhat resembled accuracy."

The o-series also anchors arguments about machines resisting control, and what gets cited is the model's name. One person pasted a model's list of examples of apparent self-preservation, and the first entry has o3 rewriting the kill command so it printed "intercepted" instead of terminating. The example people reach for is a named model, not a general worry. A Portuguese-language video makes a similar case about o1, saying it acted differently when it realized it was being evaluated and that OpenAI admitted as much.

The name also stands for a method, and people lean on it when they explain what is happening inside a model. One person reads an OpenAI employee's reported fear as a repeat of the moment chain of thought was found in o1, and expects another revolution of that kind; a different post says the reasoning text people see from models is not the real thinking but a sanitized summary written by a lightweight model, and that this has been true since the o-series. Either way the o-series is where the explanation starts.

One writer says they have not touched OpenAI's models since o3-mini inside a coding tool, which feels to them like a decade ago, and that their experience is calibrated against that baseline. A verdict calibrated against a baseline like that says as much about when its writer last looked as about the model in front of them, so for anyone choosing a model on a stranger's say-so, a useful question is which baseline the verdict was calibrated against.