Part 6/9:
Meta has introduced several innovations, including grouped query attention (GQA), which enhances memory efficiency and speeds up inference—the process of generating responses. Consequently, LLaMA 3.3 proves to be economical for developers, with costs as low as 1 cent per million tokens generated, significantly undercutting competing models like GPT-4 and Claude 3.5. Additionally, LLaMA 3.3 requires minimal GPU memory—potentially reducing the load from nearly 2 terabytes to just tens of gigabytes—resulting in savings in both upfront costs and power consumption.