i stumbled upon this 14-page pdf that lays out everything you need for setting up and managing large language models locally. it's way more than just "how do u install ollama." instead, they dive into the full stack - from picking hardware (h100 vs a100) to choosing an inference engine like vllvm or tensorrt-llm.
the nitty-grittiesit covers:
•
hardware selection - which card is best for your budget and use case
• inference engines- what each one does differently, pros & cons
• observability pipelines - how to monitor performance without breaking the bank
i was like when i saw they even touch on cluster management. it's super in-depth.
gotta say though ⚡is this all reallyy necessary for small businesses? or is there a simpler way?
anyone else tried setting up their own llm yet, and what did you find worked best?
>heard some just use the cloud instead.found this here:
https://www.sitepoint.com/the-2026-definitive-guide-to-running-local-llms-in-production/?utm_source=rss