OpenAI o3

And this is a totally reasonable trade-off if you have humans looking at all of this stuff.

But my moment was, and this is before Codex, before Cloud Code, was can you put the O3 model, which was the model I used at that point, kind of the first real agentic model.

There was O1, but O3 was really a first breakthrough.

Can you put it in some kind of loop and just have it keep looking? And it basically looped.

And the first loop was like, is there anything wrong with the coding elements, which are kind of obvious things? And it's using these kind of bioinformatics tools.

The sequencing is not the problem.

It is given your problem, What insights can you derive from that? And that was only possible as of like last summer.

Like I'd say O3 is the first example of that.

There's an image here.

Line graph, Sweebench verified software engineering comparing GPT-5 and OpenAI O3 accuracy versus output tokens.

But on their new chart, the internal model is getting the same performance as GPT-6 Astra for about 1 to 100 the tokens.

That's like four previous jumps in one.

There's an image here.

Line graph, Sweebench verified software engineering comparing GPT-5 and OpenAI O3 accuracy versus output tokens.

But on their new chart, the internal model is getting the same performance as GPT-6 Astra for about 1 to 100 the tokens.

That's like four previous jumps in one.