I'll take prompt adherence over quality any day. The machinery otherwise isn't worth it i.e the controlnets, openpose, depthmaps just to force a particular look or to achieve depth. Th solution becomes bespoke for each generation.
Had a test of it and my option is it's an improvement when it comes to following prompts and I do find the images more visually appealing.
For detail, it'd probably be better to use a full model with a small number of steps (something like KSampler Advanced node with 40 total steps, but starting at step 32-ish.) Might even try using the SDXL refiner model for that.
Turbo models are decent at low-iteration-decent-results, but not so much at adding fine details to an mostly-done image.
Had a test of it and my option is it's an improvement when it comes to following prompts and I do find the images more visually appealing.