Small Language Model

Frontier models are built to be good at nearly everything, and every answer from one costs the computing power of a very large model. A small language model trades breadth for cost and speed. With fewer parameters, it is usually cheaper and faster per answer, the smallest can run on a laptop or phone, many fit on a company’s own servers, and it is often post-trained to do one job well.

The usual pattern is to prototype on a frontier model, measure quality with evals, then move stable, high-volume tasks to a small model that still passes them. Intercom did that with one summarization step on Chain of Thought’s episode 49. Small language model vs. frontier model covers when each wins.