Interesting how do you know if it does a good job at these tasks? It seems that thinking in LLM's has been one of the things that has been so important to making sure it's a good response.
When the use case allows room for an acceptable amount of incorrect decisions because there's a manual flow those cases can be routed to still anyways.
It doesn't. Decision models are not more accurate than small models with no thinking. If your classification task is accuracy sensitive, you still need to stick with one of the big frontier models.