LLMs are notoriously non-deterministic, and even at temperature zero you still can't predict exactly where the weights will take you next.
An LLM can be made to be completely deterministic. I use them in this mode so I can reproduce test cases. Of course it requires complete control over the model, etc. but this myth that a computer program is non-deterministic needs to end.You can 100% predict where the weights “will take you” given a set of inputs.
> You can 100% predict where the weights “will take you” given a set of inputs.
Do you mean reproduce?
Sorry it's just if you are saying what your statement implying then either the model is very simple, or you've figured out something incredible
Can you provide steps to reproduce so I can see one of these deterministic LLMs running myself? API based or local models.
By "can't predict exactly where the weights will take you next" I meant with your brain. The blind chess analogy suggests you can predict, using your own thought process, the exact output of a prompt.
Could you give some examples?
You should publish, likely a Nobel price or Turing award waiting, and generational wealth at some tech giant.
Floating point matrix calculations are non-deterministic. You need to invent new hardware, that doesn't use floating point math, first. [0]
[0] https://arxiv.org/html/2506.09501