Maximum sovereignty with llama.cpp: compile from source, GGUF model formats, quantisation levels (Q4_K_M, Q8_0), CLI inference, server mode, and performance tuning for CPU and GPU.
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llama.cpp Tutorial 2026: Run GGUF Models Locally on CPU and GPU
Complete llama.cpp tutorial for 2026. Install, compile with CUDA/Metal, run GGUF models, tune all inference flags, use the API server, speculative decoding, and benchmark your hardware.
Speculative decoding doubles local LLM inference speed with zero quality loss. How it works, how to enable it in Ollama and llama.cpp today, and which model pairs give the best speedup.
Master GGUF quantization formats for local LLMs in 2026. Q2_K, Q4_K_M, Q5_K_S, Q8_0, F16 explained with benchmarks, VRAM tables, and exact Ollama and llama.cpp commands.
