The rapid growth of large language models (LLMs) has brought significant advancements across various sectors, but it has also presented considerable challenges. Models such as Llama 3 have made impressive strides in natural language understanding and generation, yet their size and computational requirements have often limited their practicality. High energy costs, lengthy training times, and the need for expensive hardware are barriers to accessibility for many organizations and researchers. These challenges not only impact the environment but also widen the gap between tech giants and smaller entities trying to leverage AI capabilities. Meta AI’s Quantized Llama 3.2 Models (1B and