They can however be extremely useful for curating training data. Also things like SAM and the DINO (/grounding dino) models.

Also if they are better then you can also have a flow that’s cheap model -> marginal cases go to more complex thing (and a chain of these).

The yolo models are really shockingly good for their cost and how well they can work with not much training data as well.

>for very limited benefit

Due to how simple they are to work with they will become popular. Compare NLP before and after GPT-3. GPT-3 majorly brought down the complexity and skill needed for doing NLP tasks even if traditional NLP is much much faster. Ultimately ease of development will win out and the industry will work towards optimizing running such LLMs to make it cheap enough to run.