Learn how to set up and run your own local AI model using llama.cpp. This course walks through installing llama.cpp, downloading GGUF models, launching a local server, testing performance, and troubleshooting common GPU/CUDA issues. You’ll build a working local LLM setup that can become the foundation for private AI tools, experiments, and custom workflows. This course covers: ✅ Local LLM installation ✅ Quantization (Q4/Q5/Q8) ✅ Network connection ✅ Performance Testing

Benchmark tokens/sec, test logical output, and tune performance flags. In this free course you will: Build a repeatable test folder and scoring system Benchmark prompt processing and token generation speed with llama-bench Run 3 standardized quality tests across Q4, Q5, Q6, and Q8 Monitor VRAM in real time with nvidia-smi Tune llama-server flags for speed, quality, and stability Build model profiles and a personal preset library Prerequisite: C1.