Nope. You have not shown how a large scale collection of neural networks irrespective of their architecture is more deterministic when compared to a 'compiler' and only repeating a known misconception of tweaking the temperature to 0 which does not bring the determinism you claim it brings with LLMs [0] [1] [2], otherwise you would not have this problem in the first place.

By even doing that, the result of the outputs are useless anyway. So this really does not help your point at all. So therefore:

> You're just using words incorrectly. Deterministic means repeatable. That's it. Predictable, verifiable, etc are tangential to deterministic.

There is nothing deteministic or predictable about an LLM even when you compare it to a compiler, unless you can guarrantee that the individual neurons through inference give a predictable output which would be useful enough for being a drop-in compiler replacement.

[0] https://152334h.github.io/blog/non-determinism-in-gpt-4/

[1] https://arxiv.org/pdf/2506.09501

[2] https://thinkingmachines.ai/blog/defeating-nondeterminism-in...