Flutter Tutorial Shows How to Run LLMs Locally on Device Without APIs

A new tutorial published on DEV Community walks Flutter developers through running large language models directly on a user's device, eliminating the need for cloud APIs or internet connectivity. The guide uses the open-source NobodyWho library, which wraps llama.cpp and provides Dart bindings for loading and running models in GGUF format on both iOS and Android. On-device inference offers key advantages including offline functionality, user data privacy, lower latency, and no cloud infrastructure costs, though models are smaller and less capable than cloud-hosted alternatives. The tutorial covers a range of features from basic chat interactions to multimodal input, speech-to-text, voice activity detection, tool calling, and retrieval-augmented generation. Models can be sourced directly from Hugging Face, cached automatically on first use, and reused in subsequent app launches without additional downloads.