if you’re interested in running your own models for any reason, you really should build your own evaluation dataset for the scenarios you care about.

at this point, all the public benchmarks are such a mess. Do you really care if the model you select has the highest MMLU? Or, do you care only that it’s the best-performing model for the scenarios you actually need?

To be fair, it’s pretty clear that openai update their models with every kind of test people throw at them as well.

It’s inevitable people will game the system when it’s so easy, and the payoff can be huge. Not so long ago people could still get huge VC checks for showing off GitHub stars or benchmark numbers.

The problem isn’t the training data, it’s the benchmarks.