Frontier model
One of the most capable general-purpose AI models available at a given moment, defining the current ceiling for reasoning, instruction-following, and generation quality.
In more detail
Frontier model is a relative term. It refers to the handful of models at the leading edge of capability at any point in time, the ones that push the boundary on hard reasoning, long-context understanding, and reliable instruction-following. Yesterday's frontier model becomes today's baseline as the field moves.
Frontier models are expensive to run and slower than smaller models, so the practical question is rarely whether to use the most capable model for everything. It is which steps genuinely need frontier-class reasoning and which run fine on a smaller, faster, cheaper model.
Where this shows up at Ceven
Ceven routes each step to a model sized for the job rather than sending everything to the largest one. A hard reasoning or planning step can use a frontier-class model, while a quick classification or extraction step runs on something smaller and faster. The workflow you describe in plain language runs the same way regardless of which model handles each step.