5 Technical Logs Found
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.
With 52 million monthly downloads and 135,000 local models on HuggingFace, Ollama and local AI inference have officially moved from niche hobby to enterprise necessity in 2026.
TurboQuant eliminates KV cache memory overhead with zero accuracy loss. Complete guide: what TurboQuant is, how PolarQuant and QJL work, and how to use TurboQuant with Ollama, GGUF, and llama.cpp today — including the best current quantisation commands while TQ models are in development.
