Tens of millions? You're thinking specifically of the proof of Navier-Stokes. According to https://github.com/openai/math/blob/main/README.md:
"On average, each result used three hours of ChatGPT Pro thinking compute with that model. Over the course of the evaluation, the model was posed approximately 4,000 problems. Aggregating the output into result families and manuscripts and requiring an appropriate level of significance led to the catalog outlined above."
I will note that this includes the Quasi Riemann Hypothesis. The model that solved NS was significantly dumber and less efficient that OpenAIs more recent math-models and you shouldn't over index on "it's expensive now". AI has advanced so quickly that your <2 month old opinion is out of date by 5+ orders of magnitude!
Question: Have you actually used AI to do research-level math? At the current time, it is not "tackle any problem you wish and you can get headline results in ~3 hours." Their method is spraying-and-praying across the entire mathematical frontier, which is something only AI demonstrators are interested in. And as far as I know, they have never elaborated on what their "average of 3 hours" metric even means (e.g. including or excluding all unsuccessful leads?).