Small models, big wins: four reasons enterprises are choosing SLMs over LLMs

In recent years, Large Language Models (LLMs) have dominated mainstream attention for their ability to generate human-like responses, and complete tasks ranging from summarizing documents to coding applications. But now, enterprises are beginning to question if these general-purpose AI models can actually support their specific business goals.

A recent McKinsey survey found almost three quarters of organizations regularly use generative AI in at least one business function, up from 65% in early 2024. Despite this rising popularity, there is still a need for greater control and understanding of how AI models work. Nearly two-thirds (62%) of business leaders cite model explainability and data management among common challenges with AI adoption. If organizations are to keep pace and bring their ambitions for AI to fruition, they need to act quickly to overcome these issues.

Small solutions for large problems

Purpose-built Small Language Models (SLMs) can offer significant ...