GPT-4 is amazing, but the upside of smaller models is much lower cost. I get basically 100% accuracy on JSON modeling with GPT-4 with function calling too, but I will say that gpt-3.5-turbo with function calling is somewhat less accurate — it usually generates valid JSON in terms of JSON.parse not exploding, but not necessarily JSON following the schema I passed in (although it's surprisingly good, maybe ~90% accurate?). I use 3.5-turbo a decent amount in API calls because it's just a lot cheaper, and performs well enough even if it's not gpt-4 level.

I haven't gotten a chance to earnestly use the smaller Llama models yet in more than small prototypes (although I'm building a 4090-based system to learn more about finetuning them), but the little amount of experimenting I've done with them makes me think they need a decent amount of help with generating consistently-valid JSON matching some schema out of the box. This is a pretty neat tool to use for them, since it doesn't require finetuning runs, it just masks logits.