Dashboards & Analytics · 4 min · Updated 2026-06-14

Token Metrics explained

Understanding token counts, cache rates, and prompt efficiency

Key metrics

  • Input tokens — tokens sent to the model (your prompts + context)
  • Output tokens — tokens generated by the model
  • Cache-read tokens — input tokens served from cache (~90% cheaper)
  • Cache-write tokens — input tokens written to cache (~25% more expensive, but pay off quickly)

Cache hit rate

Your cache hit rate shows what percentage of input tokens were served from cache. Higher is better.

  • 0-10% — no caching in place, significant savings available
  • 10-30% — some natural caching from repeated system prompts
  • 30%+ — active caching strategy paying off

Improving your metrics

  1. Structure prompts for cache hits — put stable content (system prompts, instructions) at the beginning
  2. Reuse conversation prefixes — cache-friendly patterns save 90% on repeated context
  3. Trim conversation context — summarize prior turns instead of re-sending full history

Track your real costs

Calculators estimate. The dashboard shows what you actually spend and where you can save.