Can you give me a practical formula to calculate LLM token budgets for a customer support chatbot handling about ten thousand queries a day
Download run
Fan-out diagram
The searches the AI actually ran for this prompt.
SEED QUERY
Can you give me a practical formula to calculate LLM token budgets for a customer support chatbot handling about ten thousand queries a day
1 real search · 1 real-search pass
LLM API token usage input output cached tokens pricing billing documentation 2026Google ↗
OBSERVEDOther / navigational
Badge and edge weight = share of passes that produced the query. Hover a query for its intent and routing format.
Query classes
Google's semantic query class for every sub-query: what kind of answer each search is after, simulated vs real.
ChatGPT real searches (1)
Classes come from the query-classifier (a local Laya model). 1 of 1 calls are low-confidence (under 50%) — hover a query in the table to see its confidence.
Searches and sources
ChatGPT1 real searches · gpt-6
LLM API token usage input output cached tokens pricing billing documentation 2026 Google ↗
- Pricing · developers.openai.com
- Prompt caching · developers.openai.com
- Understanding and counting tokens · help-lb.openai.com
- Reviewing API usage and costs · help-lb.openai.com