In plain words
Frontier AI refers to models near the leading edge of what AI can do. The boundary shifts as capabilities advance, and different research or policy frameworks define it differently.
A closer look
The term often describes general-purpose models with strong abilities across tasks. It is not a permanent label: a model at the frontier today may later become ordinary.
Frontier status describes capability, not a guarantee of reliability or safety. It also does not establish AGI; even advanced models have uneven strengths and limitations.
In practice
A newly released model advances performance across coding, reasoning, and scientific tasks. Researchers may describe it as a frontier model while separately testing its limitations.
A useful distinction
Frontier AI is not a fixed architecture or a synonym for AGI. There is no single universally accepted cutoff.