I'm not going to open an issue on this, but you should consider expanding on the self-hosting part of the handbook and explicitly recommend llama.cpp for local self-hosted inference.
The self hosting section covers corporate use case using vLlm and sglang as well as personal desktop use using Ollama which is a wrapper over llama.cpp.
You can disagree all you want, but Ollama does not keep their llama.cpp vendored copy up to date, and also ships, via their mirror, completely random badly labeled models claiming to be the upstream real ones, often misappropriated from major community members (Unsloth, et al).
When you get a model offered by Ollama's service, you have no clue what you're getting, and normal people who have no experience aren't even aware of this.
Ollama is an unrestricted footgun because of this.
I thought the models were like HuggingFace, where anyone can upload a model and you choose which you pull. The Unsloth ones look like this to me, eg: https://ollama.com/secfa/DeepSeek-R1-UD-IQ1_S
Ollama themselves upload models to the mirror, and often mislabel them.
When R1 first came out, for example, their official copy of it was one of the distills labeled as "R1" instead of something like "R1-qwen-distill". They've done this more than once.
