Something a lot of model providers don't talk about: any time an engine uses speculative decoding the throughput will depend on how much your output token distribution matches what the draft model was trained on.

The DFlash2 draft model we're using was trained on a lot of code, so if you use it in a coding agent you'll probably notice it run a lot faster (we've seen it break 300 tok/s).

Hey Daniel! It's a bit hidden, but at the bottom of the billing page there's a "Credits" section which should show usage of any active credits and the balance remaining. The usage/billing metrics are batched/handled async so it might take a minute or so for usage to be reflected. Let us know if it feels off.