If I understand correctly, Hugging Face is exploring approaches to tuning the output quality of a given model by tuning how long to let it run.

Normally when you run an LLM, you set your prompt and whatever tunable parameters, and the LLM software (eg. lamma.cpp) spits out tokens at whatever rate it can. If you want higher quality, you run a bigger model (though you're limited by the amount of memory you have available). If you want higher speed, you run a smaller model. Hugging Face seems to be looking at ways to make this tradeoff without switching between different models.