Thanks, that’s actually very helpful, and it confirms what I was running into.
My confusion wasn’t about whether reverse-engineering is possible, but about the fact that the official documentation mixes multiple vision pricing regimes without clearly scoping them per model, which makes it hard to know when reverse-engineering is required vs when the documented rules apply.
The existence of hidden multipliers (like the GPT-5.2 ×1.2 you mention), undocumented resize behavior, and per-call overhead explains why the billed tokens don’t always line up with the published formulas or even the official calculator.
I’ll take a look at the hotnova script, thanks for sharing it.