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Analytics reads canonical project traces from W&B rather than maintaining a separate request-event database. It helps you verify rollout and estimate the economic effect of replacing a model.

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Available views

  • request volume over time;
  • traffic share by routed model;
  • project-version distribution;
  • input and output token volume;
  • provider errors;
  • estimated input, output, and total cost;
  • comparison models that are not currently receiving traffic.
Choose a range from one hour through three months. Long ranges use wider time buckets.

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Pricing coverage

Costs are estimates. Studio uses, in order:
  1. a manual model price configured on the provider or fine-tune;
  2. W&B Inference pricing for a fine-tune’s base model;
  3. the bundled LiteLLM catalog when a matching model is known.
The page reports what percentage of calls had enough pricing information. Compare models only when their coverage is similar. Responses replayed from the exact-response cache keep their original token counts but are priced at zero, because no provider inference ran.

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Use analytics during rollout

After changing routing, verify:
  • the new model receives the intended share;
  • the old model remains at the expected residual or zero weight;
  • error rate does not increase;
  • token volume and finish behavior remain plausible;
  • estimated cost moves in the expected direction.
Quality decisions should still come from evaluations and product metrics, not cost charts alone.
The time_range query accepts relative windows such as 1h, 24h, 5d, 30d, or 12w:
See Get task analytics for the response schema.
Last modified on September 3, 2026