Beyond Cost per Token: Choosing the Right AI Model Through Real Experience
While developing an intelligent reporting proof of concept, I learned that the model with the lowest token price was not necessarily the most efficient option. After testing several models within the actual application workflow, I found that a newer and more capable model delivered equivalent results in significantly less time while also using tokens more effectively. This experience reinforced the value of measuring real performance and applying engineering judgment instead of making decisions
