I audited 78 API requests on my own gateway. One of them used 1,086 input tokens and returned 2 tokens. Token waste is real.

A developer audited 78 API requests on their own gateway for Chinese AI models and found that one request used 1,086 input tokens to return only 2 output tokens, highlighting significant token waste. The developer is building a Token Audit tool to catch duplicate submissions, expensive models used for trivial queries, and nighttime spikes that may indicate key leaks.

I built a small API gateway for Chinese AI models DeepSeek, etc. and decided to audit my own token usage. Nothing fancy — just 78 test requests. What I found: 76 successful calls → 13,103 tokens total avg ~172 per call 2 calls failed → invalid model name no cost, but indicates misconfiguration Worst case: 1,086 input tokens → 2 output tokens. Yes, someone pasted a massive document and got a 2-token reply. This is like using a Ferrari to deliver a pizza. If this happens at enterprise scale, the waste is astronomical. Companies are throwing money at AI APIs without knowing where it's going. What I'm building: A Token Audit tool that catches: ❌ Duplicate content submissions ❌ Expensive models used for trivial queries ❌ Nighttime spikes potential key leaks Would you use this for your team? Any feedback is appreciated. P.S. This is my own test data, not customer data. Just validating the problem.