Are reasoning models -basically- generating their own context? as in, if a user were to feed prompt + those reasoning tokens as a prompt to a non-reasoning model, would the effect be functionally similar?
Yes, more or less. Just like any LLM "generates its own context", during inference it doesn't care where the previous tokens came from. Inference doesn't have to change much, it's the training process that's different.
thank you, that makes sense. Now it's time to really read the article to understand if the difference is the training data or the network topology to be different (although I lean towards the latter).
I am sure this is improperly worded, I apologise.