What is a Frontier Model?

The term emerged as a way to talk about the small set of models — at any given moment, things like the newest Claude, GPT, or Gemini release — whose capabilities exceed anything previously deployed, and which therefore carry both the most potential benefit and the most uncertain risk profile. Frontier models are distinguished less by a specific technical property and more by their position in time: what counts as "frontier" is a moving target, since today's frontier model becomes tomorrow's baseline as the field advances. Because frontier models are pushing into capability territory that hasn't been extensively tested in the wild, labs releasing them typically invest in more extensive safety evaluation, red-teaming, and staged rollout than they do for smaller or more established models. For a business building products on top of AI, tracking frontier model releases matters because a jump in frontier capability can unlock entirely new product possibilities — a task that was unreliable with last year's best model can become dependable with this year's — not just an incremental accuracy bump.