Supervised finetuning is only a seed for RL, nothing more. Models that receive supervised finetuning before RL perform better than those that don't, but it is not strictly speaking necessary. Crucially, SFT does not improve the model's reliability.
I think you’re referring to the Deepseek-R1 branch of reasoning models, where a small amount of SFT reasoning traces is used as a seed. But for non-“reasoning” models, SFT is very important and definitely imparts enhanced capabilities and reliability.
