[user34283]

Particularly for the large organizations at the frontier, the risk-reward does not seem worth it.

Cheating on the benchmark in such a blatantly intentional way would create a large reputational risk for both the org and the researcher personally.

When you're already at the top, why would you do that just for optimizing one benchmark score?

[D-Machine]

Everything about frontier AI companies relies on secrecy. No specific details about architectures, dispatching between different backbones, training details such as data acquisition, timelines, sources, amounts and/or costs, or almost anything that would allow anyone to replicate even the most basic aspects of anything they are doing. What is the cost of one more secret, in this scenario?