Kevin Weil

The other part of it is we're building a lot of new capabilities as we go.

And if we took the time

to only, you know, we just had like one model and we just had to build everything into one model, we'd end up moving a lot more slowly.

And, you know, things would be simpler for sure, but we'd end up moving a lot more slowly because sometimes it's easier to build a new model with a certain set of capabilities that's great at certain things, not as good at other things.

And so together you have sort of a collection of models that can do lots of things.

Each individual model has its strengths and weaknesses.

And so basically, we've optimized for going faster and getting more capabilities in people's hands at the expense of a bit of confusion.

And then over time, as we sort of gain more control over some of the new functionality, we understand it better.

We build it back into the core model.

So you have models like GPT-4 that can do a lot of things well.

And this is what we're trying to do with our forthcoming GPT-5 is take a lot of the things that we've learned and build more of the capabilities into a single model so that it's easier for people to reason about.

It's like, what model do I use?

Just use GPT-5.

And, you know, in a perfect world, it knows how hard the question you ask it is.

And so it knows whether it should give you an answer like this or whether it should think for a while.

And, you know, that's what we're shooting for.

Yeah, and look, what I don't want to do is overpromise and say, oh, in the future, we'll only ever have one model and it's going to all be simple.

Because we're also, you know, say we launch GPT-5, we're then going to have a bunch of new capabilities beyond that that we're trying to build and experiment with.

And we're going to want to get those out to people and deploy iteratively and so on.

So I expect you always have this sort of phenomenon of there are new models, and you've got sort of your workhorse models, and then you've got some of the new ones that have certain frontier capabilities that we're experimenting with and learning with together.