To me, the real lead of the article is buried here:

> apparently they tried the model on about 8,000 problems. So, right now it “merely” solves ~5% of the longstanding open mathematical problems that it’s asked about, the problems that whole communities have spent years on, after a single 3-hour attempt on them.

Back-of-the-envelope cost calculation:

3 hours of GPT-Pro compute per attempt / 5% success rate → 60 hours of compute per solved open math problem

At GPT-6 Astra API long-context pricing ($75/M output tokens), assuming 50 reasoning tokens/s, that's roughly $810 per solution:

60 h × 3,600 s × 50 tokens/s × $75 / 1,000,000 = $810

Of course, actual token usage is unknown. But even if off by 10x, $8100 is cheap for solving a longstanding mathematical problem.