DEV CommunityMonday · July 27, 2026FREE

I Was Measuring LLM Latency Wrong

The article, published on DEV Community, critiques typical approaches to measuring LLM latency. The author explains that many developers measure total response time from request to completion, which conflates two distinct phases: time to first token (TTFT) and subsequent token generation rate. They argue that TTFT is often dominated by network latency and model loading, while inter-token latency reflects the model's inference speed. The author provides code snippets using Python's `time` module to measure each phase separately, demonstrating how naive timing can hide performance issues. For example, a model with fast TTFT but slow token generation might appear acceptable in short outputs but degrade for longer responses. The article includes a concrete example using a hypothetical LLM API, showing that optimizing for total time without decomposition can lead to misguided engineering efforts. The author concludes by recommending that developers always measure TTFT and tokens per second independently to identify true bottlenecks. The post is part of a themed challenge on DEV, styled with retro CSS, but the technical content is straightforward and practical.