They say it's "parallelized". Whatever that means in reality, their demos are pretty good, their prices are extremely low compared to alternatives, and it responds in ~100ms which is pretty fast for what they do. Whether it holds for longer inputs, edge cases, etc. remains to be seen, but I can imagine the use cases for that, for example you can use it directly in the sampling layer of a normal generative model, or just as a generic decision maker/controller. They can (and will, in their words) do this for images too. I don't know if it's a big deal, but it's kind of a fresh perspective.
Unless I misunderstood what they wrote, I read parallelized in the diffusion sense, akin to GemmaDiffusion and Inception Labs models. Incidentally, Mercury 2.5 is truly groundbreaking, giving it a try is highly recommended.