TLDR Tech / Founders
Why your local LLM feels dumber than it is
Plenty of teams save money running open AI models on their own hardware, shrunk to fit. Someone on a forum tested those shrunken versions of one model and logged 44.8 terabytes of results. Same model, same question. Right answer on one graphics card, wrong answer split across two, right again across four. One common compression setting quietly broke the model's ability to call outside tools, while a slightly bigger one worked fine. A feature that flakes in production but sails through your demo may be a settings problem, not a code problem. Answers also drift deep into long documents.
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