How to measure and cap cloud costs for real-time llm inference in a startup using token-level autoscaling
I’ve spent the last year helping startups move from “it works on my laptop” to “it’s predictable and affordable in production” when deploying real-time LLM inference. One recurring headache is cloud costs that explode unpredictably because inference usage is measured in tokens, not requests—and tokens vary wildly. In this guide I’ll walk through how I measure token-level costs, build token-aware autoscaling, and put practical...