Finetuning LLMs vs prompting, which is better? In the last couple of days, I shared various resources on finetuning LLMs. Here's some nice empirical evidence that finetuning outperforms prompting.

Caveat: I wish the authors studied the performance separately for each dataset, to get a better idea of when finetuning starts to outperform prompting as a function of the dataset size.