What is LLM Distillation ?

Are large language models (LLMs) too slow and expensive to run? In this video, we break down LLM Distillation—the technique that makes AI models smaller, faster, and cheaper without sacrificing much accuracy. We'll explain how distillation transfers knowledge from a large "teacher" model to a smaller "student" model, significantly reducing compute costs while maintaining strong performance. Whether you're building AI for mobile devices, cloud applications, or real-time chatbots, understanding LLM distillation is key to scaling AI efficiently.

We'll explore real-world distilled models like DistilBERT, TinyBERT, MiniLM, and DistilGPT-2, explaining how they work and why they're widely used .

By the end of this video, you'll understand why LLM distillation is the future of efficient AI and how it's shaping the next

generation of lightweight, scalable, and cost-effective AI models. If you're interested in deploying AI on edge devices, reducing inference latency, or scaling AI for enterprise use, this video is for you! Don't forget to like, subscribe, and hit the notification bell to stay updated on the latest AI breakthroughs!