Show HN: Llama.cpp Tutorial 2026: Run GGUF Models Locally on CPU and GPU

This tutorial addresses the increasing demand for local large language model (LLM) deployment and optimization. The focus on `llama.cpp` and GGUF models highlights the community's preference for efficient, hardware-agnostic inference solutions. Covering compilation with CUDA/Metal, API server usage, and speculative decoding indicates a comprehensive approach to maximizing performance and utility for developers. The existence of such a detailed guide underscores the ongoing trend of democratizing LLM access and enabling cost-effective, privacy-preserving AI applications by leveraging local compute resources, reducing reliance on cloud-based inference APIs. This caters to a growing segment of developers prioritizing control and efficiency.