Frontier model
One of the most capable AI models available at a given time, at the leading edge of what is possible.
A frontier model is an AI model at or near the highest level of capability at a given time. The term is relative: a model that was at the frontier a few years ago may now be well behind. It is usually applied to general-purpose systems built by a small number of well-funded organisations.
The label matters because these models are where new abilities, and new risks, are most likely to first appear. Regulators, researchers and safety groups therefore often single them out for extra testing, reporting or oversight, while treating smaller or older models more lightly.
There is no exact definition. Some proposals define a frontier model by the amount of compute used to train it. Others define it by what it can do, or by comparison with the best current systems. Each approach has drawbacks: a compute threshold can be gamed or become outdated, while a capability test can be hard to run before release. Reading news about AI, it helps to ask which models are meant, since the phrase is sometimes used loosely for any new, well-known system.