A Practical Guide to Running Local LLMs

I’ve built some projects recently that include integrations with LLMs. Specifically, I’ve found an interest in agentic applications where the LLM has some responsibility over the control flow of the application. Integrating these features into my existing development workflow led me to explore running local LLMs in depth. Why Run an LLM Locally? When I talk about running an LLM locally, I mean that I’m running a temporary instance of a model on my development machine. This is not intended to be advice on self-hosting an AI application. Let’s be clear. It’s going to be a long time before running a local LLM will produce the type of results that you can get from querying ChatGPT or Claude. (You would need an insanely powerful homelab to produce that kind of results). If all you need is a quick chat with an LLM, a hosted service will be far more convenient than setting up a local one. So when might you want to run your own LLM? When privacy is critical When expenses are sensitive W ... Read full article.