Great breakdown! Usage-based billing is here to stay. The question is how to make it work for you, not against you.
A few tips to keep your AI coding costs under control:
Track everything. You need to know exactly how many tokens you're using, which model, and what it costs. No surprise bills.
Model tiering. Don't run every task on the most expensive model. Routine edits work fine on cheaper models.
Use a gateway. Instead of paying per-provider subscriptions, use a single gateway that lets you switch models easily.
We use JZS Token as our API gateway. One endpoint, 40+ models, pay as you go. Credits never expire, so you don't have to worry about "using it or losing it" every month.
The big win: you can switch models based on the task. Use a cheap model for 80% of routine work, and only use the expensive frontier model for hard reasoning.
Nice guide. This is really helpful for understanding how usage-based billing actually works.
Model tiering is the one that actually moves the needle — routing routine edits to a cheaper model instead of always hitting the frontier one is where most of the savings are. One thing worth checking before reaching for a separate gateway: GitHub's own Copilot billing dashboard already shows projected usage and lets you set a hard budget cap on overage, so you get most of the "track everything" benefit built in.
Great breakdown! Usage-based billing is here to stay. The question is how to make it work for you, not against you.
A few tips to keep your AI coding costs under control:
We use JZS Token as our API gateway. One endpoint, 40+ models, pay as you go. Credits never expire, so you don't have to worry about "using it or losing it" every month.
The big win: you can switch models based on the task. Use a cheap model for 80% of routine work, and only use the expensive frontier model for hard reasoning.
Nice guide. This is really helpful for understanding how usage-based billing actually works.