Continuous Batching Explained Why Static Batching Breaks Llm Inference

Summary

How can a single GPU serve 50 users at virtually the same speed as one? In this video, we Generating one token from a large language model means streaming every weight of the model out of memory, around 140 GB for ... In this video, we dive deep into Why do expensive GPUs waste so much capacity while serving large language models? The problem is Getting a model to run and getting it to handle a hundred users are different problems. Without touching the weights or changing a ... In this video, we deep dive into Ever wondered how AI companies serve thousands of When a GPU runs a language model, it spends most of its time waiting for memory, not doing math. This video Open-source LLMs are great for conversational applications, but they can be difficult to scale in production and deliver latency ...