I prefer not to due to privacy concerns. Perhaps you can try yourself?

I will say that after checking, I see that the model is set to "Auto", and as mentioned, used almost 8 minutes. The prompt I used was:

    Solve the following problem from a competitive programming contest. Output only the exact code needed to get it to pass on the submission server.

   I need to tackle a problem where no web-based help is available. The task involves checking if a given tree can be the result of inserting numbers 1 to n into an empty skew heap, following the described insertion algorithm. I have to figure out the minimal and maximal permutations that produce such a tree.

A terse prompt and expecting a one-shot answer is really not how you'd get an LLM to solve complex problems.

I don't know what Deepmind and OpenAI did in this case, but to get an idea of the kind of scaffolding and prompting strategy that one might want, have a look at this paper where some floks used the normal generally available Gemini Pro 2.5 to solve 5/6 of the 2025 IMO problems: https://arxiv.org/pdf/2507.15855