API Cost Lab

Last updated: October 2026 Almost every developer hits the same moment: the first real OpenAI invoice. You expected tens of dollars. You got hundreds. And your first instinct — that something must be broken — is usually wrong. Nothing is broken. Your bill is high for predictable, fixable reasons, and they're the same reasons for nearly everyone. This is a diagnostic checklist. Work through it in order, and you'll find where your money is going. The Usual Culprits 1. Every call goes to the flagship model This is the number one cause of bill shock, by a wide margin. Somewhere in your code there's a model name, and it's the biggest one — because that's the default, that's what the quickstart used, and nobody revisited it. The problem: not every task needs the flagship. Classification, extraction, formatting, simple Q and A, summarization — these run fine on smaller, cheaper models. On OpenAI's current lineup, GPT-6.1 Sol is priced at $2.00 input / $10.00 ...

Last updated: October 2026 Every AI API bill comes down to one thing: tokens in, tokens out, multiplied by the price list. But the gap between "I understand the pricing page" and "I can predict my monthly invoice" is where most teams get surprised. This guide closes that gap. You'll learn what a token actually is, how the three prices on every rate card work, a formula for modeling any workload, and five practical ways to cut the bill — with real numbers throughout. What Is a Token? A token is the unit of text the model reads and writes. As a rough rule of thumb: 1 token ≈ 4 characters of English text 1 token ≈ 0.75 words So 100 tokens is roughly 75 words. A typical page of text (~500 words) is about 650–700 tokens. Why it matters: everything is metered in tokens, but you think in tasks, messages, and documents. The single most useful habit in API cost management is building an intuition for converting between the two. A few anchors: A short chat mes...