An AI lab will never volunteer the information because it opens them up to lawsuits if they are purposely degrading service and not letting users know.
They can limit how hard the model thinks for a given effort. Suddenly xhigh only thinks as hard as high did, and high shifts down to medium effort, and so on.
They can also serve quantized models. And this has the benefit of practically not showing up in benchmarks at all even if the user experience is obviously degraded.
The other major thing the labs do is silently drop the usage limits. This has become very noticeable for codex users who are suddenly burning through their weekly usage in a few hours.
Yea, if you ever run your own models on a GPU there are a whole ton of different dials you can adjust that drastically affect compute use, memory use, and output token quality, and number of tokens held in memory.
If anyone reading has a GPU it's worthwhile just messing with a smaller model for a bit to watch how the settings affect output.