No it isn't. We're still five or ten years away from real standards.
(Anyways it's clear that the future is smaller self-hosted LLMs, so whatever standard eventually emerges will be based on that paradigm.)
Standards are already emerging, including MCP, and to say that simply because they’ll evolve and be replaced over time means they’re not ‘real’ now is ridiculous. Look at the early internet and web as examples.
Local models, even accounting for reasonable progress and device performance improvements, will always, inherently, be behind the eight ball compared to SOTA models. While they may be sufficient for the low hanging fruit, I’d not bet against the frontier models being every bit as compelling relatively speaking.
Using weasel words like ‘real’ and ‘x is the future’ is astoundingly arrogant, and anyone claiming with confidence that they’ve got any idea where we’re heading is almost assuredly wrong.
2) For me it is not clear the future is smaller self-hosted LLMs. As of today, most useful for me is to use best models, and those are not self-hosted.
They'll be used for particular language classification and search tasks, and for that you'd want several lighter, faster, cheaper and more specialized models. Not one with an arbitrary "best" score that's based on tricking the Turing test.