Tokenflood is a tool designed for load testing instruction-tuned large language models (LLMs). It allows users to define various parameters like prompt lengths and request rates without needing specific prompt data, making it easier to assess latency and performance across different providers and configurations. Users should be cautious of potential costs when using pay-per-token services.

The article explains how prompt caching works in large language models (LLMs) like those from OpenAI and Anthropic. It details the process of tokenization and embedding, illustrating how caching reduces costs and latency. The author shares insights from personal testing and dives into the mechanics behind LLM operations.