Later, I went on to add multiple tools, toggling some off and even talking about embedding into a website.

Self-hosting large language models (LLMs) provides significant benefits: data privacy, cost savings, offline access, and customization that is often impossible with cloud APIs. In 2025, a wide variety of free and open-source platforms make this more accessible than ever, whether you're running a small 7B model on a MacBook or deploying a 70B model on a rack-mounted GPU server. This guide compares the top self-hosted LLM tools across performance, ease of use, scalability, hardware needs, and extensibility. This guide does not attempt to compare the various front-end user interfaces (UIs) such as Open WebUI and LibreChat, but does reference them, indicating that some LLMs may lack a friendly UI and you may want to consider installing one. For a comparison of UIs, read our Self Hosted AI UI Guide in June 2025. What is the best way to serve LLMs? The answer really depends on your technical abilities and scaling needs. ✅ TLDR - Best for Beginners: GPT4All or Jan - Best for Technical Mac and Linux Users: Ollama - Best for Enterprise or Scale: vLLM Read the full break-down here: https://heyferrante.com/self-hosting-llms-in-june-2025