Yes, I think that is the general trend. Have one model tuned for reasoning that decides a plan, based on which you invoke other models as tools (see e.g. the Re

Yes, I think that is the general trend. Have one model tuned for reasoning that decides a plan, based on which you invoke other models as tools (see e.g. the ReWOO paper[0]). If I had to guess, an approach like this is what powers the recent Custom GPT/Assistant API products (based on the lag between tool invocations I would guess that they also re-prompt for plan adjustments between every set of tool calls). Do that with a small model and hot-swap LORAs, and it should be possible to build a quite powerful local assistant on consumer hardware. [0]: https://arxiv.org/abs/2305.18323 https://arxiv.org/abs/2305.18323