Embedding Local LLMs in Your Mobile App
Practical integration of on-device LLM inference in production mobile apps using KMP bindings to llama.cpp, covering GGUF model selection, Q4_K_M vs Q5_K_S quantization impact on output quality, Me...
Source: DEV Community
Practical integration of on-device LLM inference in production mobile apps using KMP bindings to llama.cpp, covering GGUF model selection, Q4_K_M vs Q5_K_S quantization impact on output quality, Metal/NNAPI GPU delegation, memory-mapped model loading to stay under iOS dirty memory limits, and a Kotlin coroutine-based streaming token pipeline that renders incrementally without dropping frames
