The tokenomics of self-hosted LLMs

This post explores the economics of self-hosted large language models (LLMs), emphasizing the importance of understanding both operational costs and token processing efficiency. It introduces a formula for calculating cost per token and reviews strategies for reducing expenses, increasing token throughput, and optimizing model choices. The author discusses hardware and personnel costs, software expenses, and specific techniques for improving cost-effectiveness in LLM deployment.