AI Guides & Tutorials
Practical guides for running AI models locally. From first install to advanced optimization.
How to Run AI Models Locally: A Complete Beginner's Guide
Everything you need to know to get started running LLMs, image generators, and speech models on your own computer using Ollama, LM Studio, or GPT4All.
Quantization Explained: Q4, Q5, Q8, and FP16 Compared
Understand how quantization reduces model size and VRAM usage. Learn the quality tradeoffs between Q4_K_M, Q5_K_M, Q8_0, and FP16 to pick the right variant for your hardware.
Ollama vs LM Studio vs GPT4All: Which Should You Use?
A detailed comparison of the three most popular tools for running AI models locally. Covers ease of use, performance, features, and which tool fits different user types.
GGUF vs GPTQ vs AWQ: Model Format Comparison Guide
Understand the differences between GGUF, GPTQ, and AWQ quantization formats. Learn which format works best for your hardware, tools, and use case.
Running AI on Apple Silicon: The Complete M1/M2/M3/M4 Guide
Everything you need to know about running AI models on Mac. Covers unified memory, Metal acceleration, MLX framework, and which models run best on each Apple Silicon chip.
Uncensored and Abliterated Models: What They Are and How to Use Them
An honest guide to uncensored AI models. What abliteration means, why these models exist, how they differ from standard instruct models, and how to run them responsibly.
Best GPU for AI by Budget: 2026 Buying Guide
Find the right GPU for local AI at every price point. Covers budget ($200), mid-range ($400-$600), high-end ($800-$1200), and enthusiast ($1500+) tiers with specific model recommendations.
VRAM Explained: How Much Do You Need for AI Models?
Understand VRAM, how AI models use it, and exactly how much you need for different model sizes. Includes a practical VRAM calculator and tips for maximizing your available memory.