Inference with Gemma using Dataflow and vLLM- Google Developers Blog

This post introduces the integration of vLLM, an open-source library for high-throughput LLM inference, with Google Cloud Dataflow's model manager. It details how vLLM's continuous batching technique significantly improves LLM inference performance compared to traditional batching, achieving over a 23x improvement in vCPU hours for processing prompts. The post explains how Dataflow's model manager simplifies the deployment of vLLM within streaming pipelines by allowing users to control the exact number of model copies, thereby optimizing resource utilization and reducing out-of-memory issues for large models.