Drop one tool from your request: one GPT-5 version keeps 76% of it cached, another keeps nothing

Prompt caching is the cheapest performance win within an LLM based application. An application sends a long system prompt with each request and the model provider checks recognizes the part it had seen before (from the beginning) and it charges you a fraction of actual token cost instead of reprocessing them. An agent that uses tools where the system prompt and tool definitions can be upto several thousand tokens and barely change between turns, the discount is enormous. The advice to benefit…