Sam Altman describes the ideal AI model for 2026: tiny and fast, with superhuman reasoning and access to a trillion tokens of context. Rather than using models as databases, he envisions reasoning engines that call specialized tools like physics simulators to solve problems.
The framework that I like to think about. This is not something we're about to ship, but like the Platonic ideal, is a very tiny model that has superhuman reasoning capabilities. It can run ridiculously fast, and 1 trillion tokens of context and access to every tool you can possibly imagine. And so it doesn't kind of matter what the problem is. Doesn't matter whether the model has the knowledge or the data in it or not. Like the model, using these models as databases is sort of ridiculous. It's a very slow, expensive, very broken database. But the amazing thing is they can reason. And if you think of it as this reasoning engine that we can then throw, like, all of the possible context of a business or a person's life into and any tool that they need for that physics simulator or whatever else, that's quite amazing what people can do. And I think directionally, we're headed there.
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