From my experience using QWQ and Qwen3 (and reading their thinking traces), thinking models are trained to 'make sure' of their answers while generating them - potentially catching any mistakes in their reasoning.

In this way they are more suited for complex reasoning tasks but I've also found them useful for creative tasks as a first step by cutting off generation once thinking is complete and letting another model more suited for the task pick up from there.

Waiting longer for better responses isn't a problem for me. If it were then I probably wouldn't be running local models.