> For each problem, our system sampled many candidate submissions and submitted 50 of them based on a test-time selection strategy. Submissions were selected based on performance on the IOI public test cases, model-generated test cases, and a learned scoring function. If we had instead submitted at random, we would have only scored 156 points on average, suggesting that this strategy was worth nearly 60 points under competition constraints.

Did you read the post? OpenAI clearly states that the results are cherry-picked. Just a random query will have far worse results. To get equal results you need to ask the same query dozens of time and then have enough expertise to pick the best one, which might be quite hard for a problem that you have little idea about.

Combine this with the fact that this blog post is a sales pitch with the very best test results out of probably many more benchmarks we will never see and it seems obvious that human experts are still several order of magnitudes ahead.