Run AI Models on Your PC: Best Quantization Levels (Q2, Q3, Q4) Explained!

Run AI Models Locally: Quantization Explained (Q2, Q3, Q4, Q5) Want to run large language models (LLMs) like Phi-4 on your PC or laptop? In this video, I’ll break down quantization—the secret to making massive AI models smaller, faster, and easier to run locally. Learn the differences between Q2, Q3, Q4, and Q5 quantization, how to choose the right level for your hardware, and why quantization is a game-changer for running LLMs on consumer-grade devices. 🔍 What You’ll Learn: What is quantization, and how does it work? Key differences between Q2, Q3, Q4, and Q5 quantization. How to choose the best quantization level for your needs. Trade-offs between file size, accuracy, and speed. Practical examples using Phi-4 and other popular models. 💻 Who Is This For? AI enthusiasts who want to run LLMs locally. Developers looking to optimize AI models for edge devices. Anyone curious about how quantization works and why it matters. 📂 Resources Mentioned in the Video: GPT4All Phi-4 LMStudio Hugging Face Models 👍 If you found this video helpful, don’t forget to: Like and subscribe for more AI tutorials and guides! Share this video with anyone interested in running AI models locally. Leave a comment below if you have questions or suggestions for future videos. My Current Computer CPU: AMD 7800X3D GPU: AMD 7900XTX RAM: 64 GB of DDR5 6000MHZ