Both LLM’s and SLMs are advanced AI systems that have undergone extensive training using massive volumes of text data, making them capable of understanding existing content and producing new, original content. However, there are differences between these models in relation to their size, performance and efficiency.
LLMs as the name indicates it, are bigger, which means more computational requirements and processing power is needed. Making SLMs faster and cheaper to run in comparison.
LLMs are trained using diverse data and optimised for multiple tasks, in contrast, SLMs are optimised for single tasks using domain-specific data.
While LLMs may perform better across multiple general scenarios, the use of SLMs will increase the performance and efficiency for domain-specific tasks, e.g., monitoring regulatory compliance, or answering complex questions from patents.