Grok: Searching X for "From:Elonmusk (Israel or Palestine or Hamas or Gaza)"

> It’s worth noting that LLMs are non-deterministic,

This is probably better phrased as "LLMs may not provide consistent answers due to changing data and built-in randomness."

Barring rare(?) GPU race conditions, LLMs produce the same output given the same inputs.

> Barring rare(?) GPU race conditions, LLMs produce the same output given the same inputs.

Are these LLMs in the room with us?

Not a single LLM available as a SaaS is deterministic.

As for other models: I've only run ollama locally, and it, too, provided different answers for the same question five minutes apart

Edit/update: not a single LLM available as a SaaS's output is deterministic, especially when used from a UI. Pointing out that you could probably run a tightly controlled model in a tightly controlled environment to achieve deterministic output is very extremely irrelevant when describing output of grok in situations when the user has no control over it

The models themselves are mathematically deterministic. We add randomness during the sampling phase, which you can turn off when running the models locally.

The SaaS APIs are sometimes nondeterministic due to caching strategies and load balancing between experts on MoE models. However, if you took that model and executed it in single user environment, it could also be done deterministically.