Its not a limit scenario is my point: these models are evaluated constantly, new benchmarks both public and proprietary are in constant development, benchmarks are not always static either, they can often times be living benchmarks that update over time.

You are making a technical point, which I am pointing out that while for _some_ benchmarks this is _technically_ possible, it's not true for plenty of benchmarks that all agree with the others.

> which of course would mean that the benchmark was created entirely "by hand" or using some other provider that is unconnected to the provider you are benchmarking

yes this is incredibly common. I'm not talking about hypothetical scenarios.

> To put it another way: a closed-weight model is, by definition, impossible to independently benchmark.

Even if you believe this, you're doing some mental gymnastics if you think this is really the most likely explanation for what we're seeing. It's absolutely possible to benchmark proprietary models when you don't have access to the weights or control over the API, even if they are adversarially trying to combat this, which they aren't. Doing what you're describing would be easy to detect: you'd see extremely high benchmark scores for established benchmarks and then poor scores for new benchmarks as they come out. It would be relatively easy to figure this out and not subtle.