In this episode, we introduce vLLM, an open-source library designed to dramatically improve the speed and efficiency of large language model (LLM) inference. We break down how vLLM uses techniques like PagedAttention to optimize memory usage, increase throughput, and reduce latency—making it ideal for serving LLMs in production environments. Whether you're building AI-powered applications or scaling agentic systems, this episode explains why vLLM is becoming a go-to solution for cost-effective, high-performance model deployment.