It’s not surprising that there could be a very slight quality drop off for making the model return its answer in a constrained way. You’re essentially forcing the model to express the actual answer it wants to express in a constrained language.

However I would say two things: 1. I doubt this quality drop couldn’t be mitigated by first letting the model answer in its regular language and then doing a second constrained step to convert that into structured outputs. 2. For the smaller models I have seen instances where the constrained sampling of structured outputs actually HELPS with output quality. If you can sufficiently encode information in the structure of the output it can help the model. It can effectively let you encode simple branching mechanisms to execute at sample time