My guess: because they waited to make their offerings public when they somewhat matured their behind the scenes implementations and architectures. So now a few

My guess: because they waited to make their offerings public when they somewhat matured their behind the scenes implementations and architectures. So now a few releases after that, during which they bumped specs and made smaller changes to the architectures, there's not much room to easily grow. More training data availability and quality is also a limiting factor to improvement (speed and resource needs can be improved more easily than that).