What you get with local LLM options: 1. Download the inference engine app from the web; 2. Download the model; 3. Configure MTP / DFlash / DSpark whatever; 4. Configure your Pi / OpenCode harness to point to this local LLM inference engine. 5. Configure tools for these harness to be effective. 6. Switching between Ollama, LM Studio, llama.cpp (DwarfStar4), oMLX, MTPLX, to see which one is fastest for your workload. 7. Again switching between different quants of the same model to see which one is less dumb.
To be honest, llama.cpp probably the closest to deliver on "just use it, don't worry about speed" if your focus is about a pure LLM inference engine.