Architecture generally refers to the design of the model. In this case, the underlying model is still a transformer based llm and so is its architecture.
What's different is the method for _sampling_ from that model where it seems they have encouraged the underlying LLM to perform a variable length chain of thought "conversation" with itself as has been done with o1. In addition, they _repeat_ these chains of thought in parallel using a tree of some sort to search and rank the outputs. This apparently scales performance on benchmarks as you scale both length of the chain of thought and the number of chains of thought.
No disagreement, although the sampling + search procedure is obviously adding quite a lot to the capabilities of the system as a whole, so it really should be considered as part of the architecture. It's a bit like AlphaGo or AlphaZero - generating potential moves (cf LLM) is only a component of the overall solution architecture, and the MCTS sampling/search is equally (or more) important.
What's different is the method for _sampling_ from that model where it seems they have encouraged the underlying LLM to perform a variable length chain of thought "conversation" with itself as has been done with o1. In addition, they _repeat_ these chains of thought in parallel using a tree of some sort to search and rank the outputs. This apparently scales performance on benchmarks as you scale both length of the chain of thought and the number of chains of thought.