I assumed that but everything I have seen as I dug deeper has been that at some level that is what is happening. If it is ‘reasoning’, it’s generating a ‘reasoning chain’ next token by next token and using that to influence the final output tokens. The reasoning chain is discarded and since the actual output is a continuation of the reasoning chain it may conceptually be described as allowing the model to ‘rethink’ things, but even as the generation of a ‘reasoning chain’ has results that more closely resemble reasoning, it is still a scenario where it’s building it one token at a time and we get to see meaning as an emergent property, rather than trying to find words to build to a more abstract concept like humans do. It just gets to throw away the intermediate work and the extra tokens manage to improve the ‘accuracy’ of the preserved final output.