Android wins this one and it is not close. The reason is boring and practical: you can actually get model files onto the device. Download a GGUF in the browser, point an app at it, done. No jailbreak. No sideloading gymnastics. No begging the OS for permission to use your own hardware.
The app that makes it work is PocketPal AI. Loads GGUF models directly, chats offline once the model is on the device. As a local LLM management app on Android that is genuinely on-device and free to start, it is the first install. The honest limit is the same one every phone has: small models, typically 1B to 8B after quantization. That covers writing, summarizing, brainstorming, general chat. It does not cover beating a datacenter model at hard reasoning. Manage expectations and you will be happy.
The other Android pattern is the remote one. Heavy model at home on Ollama or LM Studio, phone as the window. A mobile admin app for your local AI stack here is less about chatting and more about control: what is loaded, restart a model, watch memory, all from your pocket. Same privacy story, bigger models, one more machine to maintain.
Either way, the model matters more than the app. Great app, wrong model, still the wrong model. Our open source LLM benchmark database search filters 200 open-weight models by size and hardware fit, so you pick one your phone can actually carry before downloading anything. Best local LLM for a phone is a different question than best local LLM for a desktop, and the database treats it that way. Setting this up for a whole team? I do private AI setup for businesses at privateaiagent.fyi. Your data never leaves.