The CPU is back: Rethinking the CPU-GPU split for LLM inference

Red Hat's reevaluation of the CPU-GPU split for large language model (LLM) inference highlights a significant shift in the way companies approach chatbot applications, with CPUs potentially handling a larger portion of the compute per request. This development has important implications for website owners who utilize LLM-powered chatbots, as it may lead to more efficient and cost-effective processing of AI-driven interactions. With CPUs potentially taking on more of the workload, website owners may see reduced latency and improved performance in their chatbot applications, ultimately enhancing the user experience. To prepare for this shift, website owners can take several steps: monitor their AI bot traffic to identify areas where CPU-based processing can be optimized, review their llms.txt files to ensure they are configured to take advantage of CPU-based inference, and explore Red Hat's guidance on rethinking the CPU-GPU split to inform their own LLM infrastructure decisions.