Small language models trade the broad capability of frontier models for speed, low cost, and the ability to run privately on a laptop, phone, or edge device. For a narrow, well-defined task a fine-tuned small model often matches or beats a much larger general one.
Open SLMs combined with quantization have made capable on-device inference mainstream, which is why they anchor much of the local-LLM ecosystem.