Frontier model

Frontier models sit at the top of the capability curve: the newest flagship models from the major labs, the ones that handle the hardest reasoning, coding, and analysis tasks best. The frontier moves constantly, so which models count changes with each release cycle.

For builders, frontier is a pricing and capability tier, not a default. These models cost substantially more per token than mid-tier and small models and are often slower. They are the right choice for difficult, high-value work such as complex analysis, nuanced writing, tricky extraction from messy documents, and decisions with many constraints, and for prototyping, when you want to know whether a feature is possible at all.

The common mistake is using a frontier model everywhere because it was what you prototyped with. High-volume, simpler work like classification, routing, and short extraction often runs just as well on a model far cheaper and faster. Prove a feature on a frontier model, then test smaller ones against the same eval set and move down where quality holds.

Routing and cascades let you have both: send most requests to a cheaper model and escalate only the hard ones.