This story was originally published on HackerNoon at: https://hackernoon.com/why-cost-per-token-is-the-wrong-ai-metric.
Cost per token is a misleading AI metric. Learn why total cost per successful task determines the cheapest model and how to optimize LLM routing.
Check more stories related to machine-learning at: https://hackernoon.com/c/machine-learning.
You can also check exclusive content about #ai, #machine-learning, #software-engineering, #claude-ai, #enterprise-ai, #large-language-models, #ai-agents, #hackernoon-top-story, and more.
This story was written by: @samirsawarkar. Learn more about this writer by checking @samirsawarkar's about page,
and for more stories, please visit hackernoon.com.
Cost per token is only the visible cost of AI. The real metric is cost per successful task, which includes human rework. A more expensive frontier model can be cheaper overall if it significantly reduces failures. This article introduces a simple equation to decide when paying more for a model actually saves money.