The On-Premise LLM Lottery
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Article: https://unlockedconsulting.ai/blog/on-premise-llm-lotteryRunning an LLM on your own hardware is not a four-stepchecklist. It is a search across model size, quantizationand runtime, landing on hardware that procurement alreadyfixed before anyone asked. Twenty combinations were testedhere before one of them fit.What the episode covers:
- Why the tutorials are accurate and still useless: each documents one point in the space, on one GPU that is never yours- The three axes that interact, and why a parameter count tells you nothing until it is paired with quantization and a runtime- Why twenty attempts is the size of the job rather than excessive diligence- The failure mode that arrives after the demo: a model that answers one user and falls over under concurrent requests- Why a finished search is hard to copy, and how to scope a small version of it before committing to on-premFor operations leaders and founders at 20-to-500-personcompanies, and for the CIOs, CTOs and heads of AI who needevidence for their own board or stage.Two synthetic voices, generated with NotebookLM from anarticle written and reviewed by Helkyn Coello, founder ofUnlocked Consulting.