I put OpenAI’s gpt-5-nano and gpt-5.1 head-to-head on my psy-ops article scorer to see what you really get for the extra spend. Along the way I ran into pricing surprises, wild variance, and a reminder that ChatGPT’s shiny new memory feature can quietly bend your evals if you’re not careful. A post on LinkedIn a few days back suggested using Small Language Models (SLMs) as opposed to LLMs for repetitive tasks. This seemed like a great idea in some regards for me, but I was curious about how it would apply to apps that were intended to perform lanugage analysis. Luckily, I have the psy-ops app up and running. Also? At the moment, it is using a close-to-an-SLM model, gpt-5-nano due to pricing decisions. I used it as a test vehicle to look at the difference betwween gpt-5 nano and full featured gpt-5.1. The testing framework I used: Starting from this article, I first did three separate anayses with gpt-5-nano, and then three others with gpt-5.1. I then used gpt-5.1...