> Did you try asking Gemini what model to use and how to configure/set it up?

That would besuboptimal, as Gemini has too old knowledge cutoff. I am long past the need for such an advice anyway, as I've been using local models since mid 2024.

Gemini will search the web for most things (at least if you are using it via the web search interface), it isn’t limited to the knowledge it was trained on. Actually, I’m a bit mortified that not everyone knows this. If you ask Gemini (from the search interface) about a current event that happened yesterday, they will use search to pull in context and work with that. Also about model that was released yesterday, it can do that.

It’s only a very low level model access where search isn’t used. Local models also need to be configured to use search, and I haven't had a use case to do that yet.

Gemini seems to call this “grounding with google search”. If you have Gemini installed in your enterprise, it will also search internal data sources for context.

> Gemini will search the web for most things (at least if you are using it via the web search interface), it isn’t limited to the knowledge it was trained on.

If decides to do so, and even then baked in knowledge would influence the result.

In any case I do not need Gemini or any other LLMs to figure out setting for my llama.cpp, thank you very much.

It has always searched the web for me, and it can give me pretty good guidance about a model released in the last week. All models ATM are trying to reduce dependence on internal knowledge mostly through RAG. Anyways, this part of LLMs has gotten much better in the last 6 months.

If you are able to figure out the right settings for a model Thats was released last week, then great for you! But it sounds like you just don’t trust LLMs to use current knowledge, and have some misconception about how they satisfy recent knowledge requests.