I really hope we will get deterministic LLMs in the future. Even if it causes slightly slower response times.
Nondeterminism is what currently keeps me from working with other developers.
As I wrote in "Prompt Coding" [1], these days I am not looking for good code. I am looking for prompts that create good code. But how do you share prompts among developers when they produce different code every time? You cannot simply state "Here, I found a prompt that makes gpt-5-2025-08-07 output a solution with all the desired attributes".
Similar with images. At the moment, for most image models, you cannot outsource the task of writing prompts that create the desired images. Because most image models will not create the same image when given the same prompt and parameters.
Surely if you end up relying on a given prompt to produce the exact same code every time you should instead just check that code into source control the first time you generate it?
A deterministic LLM isn't going to behave appreciably differently from a non deterministic one if your input or context varies by even a tiny bit (pun intended) each time.
If nothing has changed, caching the result would certainly be cheaper. But if you're doing that as part of a test, it's not really running the test and it might defeat the purpose of the test.
i tried to create a makefile driven workflow based on this idea and ended up with https://github.com/khimaros/enc -- it suffers from the issues you raised
i'm hoping that it becomes more useful as models improve and become more reliable at producing working code (though determinism would be great for improving prompts).
> most image models will not create the same image when given the same prompt and parameters.
Really? If you include the seed as one of the parameters most produce pixel identical output.
E.g. "Generate deterministic images" https://cloud.google.com/vertex-ai/generative-ai/docs/image/...