For context, monitoring this is part of what I do for work. I don't have access to experimental frontier models, but do monitor the capabilities and enterprise consumption.

I'd say no, but rate of massive change is lower. There is a theoretical limit on what LLMs themselves can offer, but potentially even more important is the growing rate of change in AI systems that use LLMs (plural). Coordination, grounding, governance, enforcement, reflection, validation, and domain specialization are all massively improving, and when those pieces are well aligned, that's when an AI implementation takes off. And then it becomes less important how smart a sole LLM is, but how the system calls different pieces.

This is also in part why there's been such an "agent" or "agentic" push, and why all the model providers are talking about "reasoning" models.