Price-per-Token vs. Price-per-Outcome: Why AI Cost Comparisons Are Misleading
Price-per-Token vs. Price-per-Outcome: Why the Old Way of Comparing AI Costs Is Misleading For the last few years, "how much does it cost?" has had a simple answer in AI circles: look at the price per million tokens. Compare that number across providers, pick the cheapest one, done. It's tidy, it's quotable, and it's increasingly the wrong way to evaluate what you're actually paying for. As AI shifts from single-turn chatbots to autonomous agents that complete entire workflows — resolving support tickets, qualifying leads, reviewing contracts — the token has stopped being a meaningful unit of value. What matters isn't how many tokens a system burns through. It's whether the task got done. That gap is why a growing number of AI vendors are moving toward outcome-based pricing , and why buyers who still shop by token price are often making worse decisions than they realize. What Price-per-Token Actually Measures Token pricing charges you for computa...