I love how people say things like "extension spaghetti", as if all other non-standard APIs have the same problem: hardware gets new features that people want to use from that API, API gains extension to use that hardware feature.

CUDA is no different, in fact, often worse. Nvidia is bad at documenting which hardware does what things, and CUDA users often have to use third party tables to figure out what hardware can't do what and disappoint customers who unwisely invested into it.

If you think that Vulkan is extension spaghetti you're clearly using it wrong. Set the API to 1.4 and many existing extensions get merged in.

They really don't, no. Vulkan: 50 lines to allocate device memory. Cuda: One single line. What kind of extensive documentation stack do you want for functionality that is trivial in Cuda? And that exact issue continues through every little step of the way to your first usable application. I know there is VMA, it is a very poor solution to a problem that shouldn't even exist, and it only poorly addresses one of 100 parts of the API where Cuda is vastly simpler than Vulkan. Cuda also doesnt force you to use queue families but you can optionally use streams. No ridiculous descriptor management and binding in cuda, just passing pointers and handles via launch arguments. No overengineered explicit syncing mechanis in cuda, everything is nicely implicitly synced until you explicitly opt in to parallel streams. etc.

Weird, since the most used open source inference engine is faster on Vulkan on platforms that offer multiple options, with the sole exception being Nvidia, due to poor Nvidia driver quality (which I am forced to assume is intentional, Nvidia wishes to maintain their moat after all).