So here's what happened: i Spent Weeks Comparing AI API Prices — Here's What I Found
Last month my co-founder looked at our AWS bill and said something I'll never forget: "We're paying more for tokens than for the servers running them." That kicked off a three-week obsession of mine that turned into this post.
I've been building on top of LLM APIs for over three years now, and one thing has always bugged me — the way most providers treat their customers like hostages. Proprietary, closed source, walled garden pricing. You build your product, you commit to a vendor, and suddenly your roadmap bends to whatever they decide to charge next quarter. It feels gross.
So I pulled every price I could find, normalized them, sorted them, and stared at the results until patterns emerged. What I found honestly shocked me. The cheapest viable models aren't from the names you see splashed across conference keynotes. They're mostly Apache 2.0 and MIT licensed models that you could, in theory, self-host if you really wanted to. They're routed through Global API, which acts as a single endpoint for basically every major Chinese open-source model family.
Below is everything I learned. All numbers are pulled from Global API's pricing endpoint, verified May 2026. If you find a discrepancy, ping me — I update this every few months.
