Small Language Models are compact AI models trained for specific tasks or domains. They are faster, more cost-effective, and easier to control than large general-purpose models.
When the task is well-defined and the domain is bounded, a small model often matches the performance of a much larger one while running at a fraction of the cost and latency. SLMs are particularly valuable for on-device deployment, edge AI, and use cases where privacy or speed requirements make sending data to a large cloud-hosted model impractical.
