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Friends Don't Let Friends Use Ollama
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this post was submitted on 31 Oct 2026
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LocalLLaMA
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Welcome to LocalLLaMA! Here we discuss running and developing machine learning models at home. Lets explore cutting edge open source neural network technology together.
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Rule 2 - No comparing artificial intelligence/machine learning models to cryptocurrency. I.E no comparing the usefulness of models to that of NFTs, no comparing the resource usage required to train a model is anything close to maintaining a blockchain/ mining for crypto, no implying its just a fad/bubble that will leave people with nothing of value when it burst.
Rule 3 - No comparing artificial intelligence/machine learning to simple text prediction algorithms. I.E statements such as "llms are basically just simple text predictions like what your phone keyboard autocorrect uses, and they're still using the same algorithms since <over 10 years ago>.
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I started off with Ollama, but liked llama.cpp better because you can download one GGUF file the day it’s released and add it to a source controlled config.ini with parameters to make it work best on your hardware.
I didn’t get serious about local LLMs until I realized I could run Qwen 3.6 35B-A3B on my 3070 with q4 for KV cache and get over 100k context. I found Ollama’s Modelfile approach and model handling in general to be clunky and discouraging important tweaks, but llama.cpp keeps everything simple.