Performance and Accuracy Research of the Large Language Models

Starting with the end of 2022, there has been a massive global interest in Artificial Intelligence and, in particular, in the technology of large language models. These reduced the resolution of many problems dailies of varying degrees of complexity at a level accessible to every individual, whether it was an academic, business or social environment. A multitude of digital products have begun to use large language models to offer new functionalities such as intelligent messaging applications trained to respond efficiently depending on the specific parameters of a company, virtual assistants for programmers (GitHub Copilot), video call summarization functionality (Zoom), interpretation and extraction rapid drawing of conclusions from massive data (Big Data). These are just a few of the many uses of these technologies. Therefore, the general objective of this paper is the comparative analysis between three large language models such as ChatGPT, Gemini, and Llama3. Each model's strengths and constraints are analyzed, offering insights into their optimal use cases. This analysis provides a comprehensive understanding of the current state of large language models powered by deep learning, capable of executing various natural language processing (NLP) tasks, guiding future developments and applications in the field of artificial intelligence (AI).