Earlier quoted context omitted.
It could be that the prompt is accidentally (or purposefully) more optimised for Kimi K2, or that Kimi K2 is better trained on this particular data. LLM's need "prompt engineers" for a reason to get the most out of a particular model.
How much engineering do prompt engineers do? Is it engineering when you add "photorealistic. correct number of fingers and teeth. High quality." to the end of a prompt? we should call them "prompt witch doctors" or maybe "prompt alchemists".
Some of it is engineering-like, but I've also picked up a sixth sense when modifying prompts about what parts are affecting the behavior I want to modify for certain models, and that feels very witch doctory!
The more engineering-like part is essentially trying to RE a black box model's post-training, but that goes over some people's heads so I'm happy to help keep the "it's just voodoo and guessing" narrative going instead :)