Free model tokens and a free server sound like a gift, but they become a liability the moment you treat them as unlimited. The position argued here is simple: you should only build on free AI infrastructure when every request passes through a meter, a daily cap, and a fixed evaluation suite. Without those three things, a generous quota teaches you nothing except how quickly it can disappear.
Ten million tokens sounds enormous until you estimate a real workload. A single agent loop that reads a stack trace, searches a codebase, and drafts a fix can consume thousands of tokens per task, depending on how much context you stuff into the prompt. At a rough estimate of five thousand to fifty thousand tokens per task, ten million tokens is somewhere between two hundred and two thousand tasks. That is a comfortable experiment and a very small production footprint, which is exactly why the free tier should stay an experiment.
MonkeyCode is an open-source project that currently offers free model access and a free server option, and its free tier includes ten million tokens as of this writing. Disclosure: This article was prepared as part of MonkeyCode's product outreach. The combination is useful for prototyping, but only if you treat it as a lab rather than a gift. The rest of this article shows the metering workflow you should run against any free endpoint, including this one.
