Evaluating AI Language Models: Performance, Cost, and New Benchmarking Tools

This chapter compares various AI language models through a scatter plot of performance scores and cost-per-token, emphasizing Google's Gemini 2.5 models. It also introduces EmojiBench, a novel evaluation system that uses emojis to rate models on multiple performance metrics, while raising concerns about the gap between benchmarking and real-world usability.