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share your settings and system specs please, I haven't seen anything come out of a local LLM that was useful.

if you don't, since you're using a throwaway handle, I'll just assume you're paid to post. it is a little odd that you'd use a throwaway just to post LLM hype.

is that you, Sam?




Happy to post mine (which is also not behind throwaway handle).

Machine: 2021 Macbook Pro with M1 Max 32GB

LLMs I usually use: Qwen 2.5 Coder 7B for coding and the latest Mistral or Gemma in the 4B-7B range for most other stuff

For interactive work I still use mostly Cursor with Claude, but for scripted workflows with higher privacy requirements (and where I don't want to be hit with a huge bill due to a rogue script), I also regularly use those models.

If you are interested in running stuff locally take a look at /r/LocalLLaMA [0] which usually gives good insights into what's currently viable for what use cases for running locally. A good chunk of the power-users there are using dedicated machines for it, but a good portion are in the same boat as me and trying to run whatever can be fit on their existing local machine, where I would estimate the coding capbilities to lag ~6-9 months in comparison to the SOTA big models (which is still pretty great).

[0]: https://www.reddit.com/r/LocalLLaMA


Not sam. I am running it with ollama on a server on my lan with two 7900XT. I get about 50-60 tokens per second on phi4-mini with full precision, it only loads on a single card.

The few requests I tried were correct, I think that phi4 the 14 b parameters model produced better code though. I don't recall what it was, it was rather simple stuff though.

QwQ seems to produce okay code as well, but with only 40GB of vram I can only use about 8k context with 8bit quantization.


It is a 6 year old throwaway.

In practice it only means it is meant to be anonymous and possible to throwaway.

Or it was meant for throwaway but they kept using it.


It was meant to be a throwaway but I kept it.


> I haven't seen anything come out of a local LLM that was useful.

By far the most useful use case for me, is when I want to do something in a repl or the shell, I only vaguely remember how the library or command I am about to use works and just ask it to write the command for me instead of reading through the manual or docs.




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