
Large Language Models represent a significant advancement in the field of artificial intelligence, yet their probabilistic nature presents a unique and persistent challenge for developers aiming to build reliable, predictable applications. This review will explore the practical methods for evaluating their performance, key metrics for comparison, and the impact of these evaluations on application development. The purpose of this review










