Local LLM Deployment: Ollama & llama.cpp Practice Tests

This practice test series is designed to help you build genuine, working confidence in deploying large language models on your own hardware — using Ollama and llama.cpp — instead of relying on cloud APIs.

Across 6 tests and 600 carefully written multiple-choice questions, you'll work through the full arc of local LLM deployment:

Local LLM Fundamentals & Setup covers the core tradeoffs of local vs. cloud deployment, hardware requirements, the GGUF file format, and getting your first model running.

Ollama Core Usage goes deep on the Ollama CLI, Modelfiles, the REST API, model management, and everyday workflows.

llama.cpp Fundamentals covers building from source, key CLI flags, the llama-server API, GBNF grammars, and how llama.cpp compares to higher-level tools like Ollama.

Quantization & Performance Optimization is where you learn to actually tune your setup — choosing the right quantization level, GPU offloading, threading, batching, and benchmarking methodology.

Building Applications on Local LLMs covers API integration, streaming, RAG, tool/function calling, structured output, and the application-level engineering that turns a model into a real product.

Production & Advanced Deployment covers containerization, security, monitoring, scaling, versioning, disaster recovery, and the mindset shift from "it works when I tested it" to something genuinely reliable.

Every single question — right and wrong answers alike — comes with its own explanation, so you understand the reasoning behind each option, not just which one is correct. This is a hands-on, practical course built for developers and hobbyists who want to actually run and ship something on local models, not just read about the theory.