What changed
GitHub's AI usage report now shows each model's input, output, cache-read, and cache-write tokens alongside AI credits. The downloadable report is available to Business and Enterprise administrators and to individual users from billing settings.
Why it matters
Per-model token composition makes it easier to explain credit consumption and distinguish expensive context, generated output, and cache behavior across an organization's model mix.
What to do
Download the report, compare token composition and credits by model over time, and investigate large context or cache-write costs before changing model policies.
Caveat
Token accounting describes consumption, not whether the work was correct or valuable, and the report does not by itself attribute usage to individual development tasks.