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Score: 39🌐 NewsMay 30, 2026

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.

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Source

https://machinelearningmastery.com/serving-multiple-users-at-once-how-continuous-batching-keeps-llm-inference-efficient/