Real ChatGPT answer · index seedPgNKW7p3vZccompleteB2B software · AI and automation toolsinformational
What is the most practical way to track token usage and manage API costs when building internal workflows using OpenAI models?
Download run
Fan-out diagram
The searches the AI actually ran for this prompt.
SEED QUERY
What is the most practical way to track token usage and manage API costs when building internal workflows using OpenAI models?
1 real search · 1 real-search pass
OpenAI API official documentation usage token counts response usage pricing costs dashboard project budgets rate limits 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
OpenAI API official documentation usage token counts response usage pricing costs dashboard project budgets rate limits 2026 Google ↗
- Reviewing API usage and costs · help.openai.com
- Understanding and counting tokens · help.openai.com
- Counting tokens · developers.openai.com
- OpenAI API pricing · openai.com
- OpenAI Usage Dashboard · platform.openai.com
- How to use the Usage API and Cost API to monitor your OpenAI usage · developers.openai.com
- Spend limits · developers.openai.com
- Rate limits · developers.openai.com