alt Hacker NewsIt won't matter. By the time it's done reasoning, it has already decided what it wants to say.
Reasoning tokens are just regular output tokens the model generates before answering. The UI just doesn't show the reasoning. Conceptually, the output is something like:
<reasoning>
Lots of text here
</reasoning>
<answer>
Part you see here. Usually much shorter.
</answer>
The reasoning part is not diferente from the part that goes in answer. It’s just that the model is trained to do some magical text generation with back and forth. But when it’s writing the answer part of it, each word is part of its context when generating the next. What that means is that the model does not compute then write, it generates text that guide the next generation in the general direction of the answer.
If you steer it in strange (for it, as in not seen before in training) text, you are now in out-of-distribution, very weak generalization capabilities territory.