Rick W / Tuesday, June 9, 2026 / Categories: Artificial Intelligence Serving Multiple Users at Once: How Continuous Batching Keeps LLM Inference Efficient This article is divided into four parts; they are: • The Problem with Static Batching • Code Example of Static Batching • Continuous Batching: Dynamic Scheduling and Ragged Batching • Full Implementation The simplest way to serve multiple requests together is to use static batching, by grouping them into fixed-size batches and processing each batch together. Previous Article Build an Emergency Helpline Voice Agent with LangChain Next Article Using Scikit-LLM with Open-Source LLMs Print 3 Tags: Continuous