Rather than relying on the user to request deliberation, these models generate an extended internal chain of thought, consume it as context, then answer. Those reasoning tokens are usually discarded and rarely shown.
They post their largest gains where answers can be automatically verified — mathematics, code, formal logic — because that is where the training signal exists.