The token overhead of tool/function definitions on every call.
Tool definitions ride along as input tokens on each request. Ten verbose tools can add a thousand tokens per call you pay for constantly. Cache them — see the prompt caching calculator.
The Function Calling Cost Calculator estimates the monthly API spend added by the tool definitions you send with each request. Every call that includes function-calling schemas carries those tool-definition tokens on top of your other input tokens, and you pay for them on every single request. Using your inputs — calls per month, tool-definition tokens per call, other input tokens per call, output tokens per call, and the input and output prices per million tokens — it multiplies input tokens by the input rate and output tokens by the output rate, then scales by call volume to show total cost and, in particular, how much the tool-definition overhead alone contributes.
The key trade-off to watch is that tool definitions are fixed overhead paid on every call, so their cost grows directly with request volume even when the model never invokes a tool. Trimming unused functions, shortening descriptions, or splitting large tool sets so each request only carries the schemas it needs can cut this recurring charge. Model the difference here before committing: at high call volumes, a few hundred extra definition tokens per request can quietly dominate your bill.
Yes. The JSON schema for your tools is sent as input tokens on every request, whether or not a tool is used. With many tools or verbose descriptions, that overhead is significant across high volume.
Expose only the tools a call might need, keep descriptions terse, and cache the static tool block with prompt caching so you aren't billed full price to resend it each time.