AI Prompt Cache Cost Calculator
Estimate how much prompt caching saves on token cost, compare cache read/write discounts across OpenAI, Claude and Gemini for long system prompts and RAG
Interactive tool will be available soon
Meanwhile, read the guide below to understand how it works
Features
- ✓ Enter prompt length and call volume to estimate cost before and after caching
- ✓ Compare cache read/write discounts across OpenAI, Claude and Gemini
- ✓ Separate cache-hit and cache-miss token billing
- ✓ Estimate monthly savings for long system prompts and RAG
- ✓ Export results for budgeting and cost reviews
How to Use
- Enter the token length of your system prompt and context
- Fill in daily/monthly call volume and cache hit rate
- Select the model and pricing plan
- Review the cost comparison and savings ratio
FAQ
What is an AI Prompt Cache Cost Calculator?
A tool that estimates caching costs. It estimates cost before and after caching, compares vendor discounts, separates hit and miss billing and projects monthly savings. Input: prompt length, call volume, hit rate and model pricing. Output: cost comparison and savings. Built for developers, AI products and cost owners.
What is prompt caching?
It caches repeated prefix content such as a long system prompt on the server so later requests that hit the cache are billed at a lower cache-read price, cutting both cost and latency.
Which models support caching?
Major vendors including OpenAI, Anthropic Claude and Google Gemini offer caching; the exact discounts and minimum lengths are on their official pricing pages.
Does caching always save money?
Only when the same prefix is reused often; cache writes usually cost extra, so a low hit rate may not pay off.
How do I estimate the hit rate?
Estimate it from the share of requests reusing the same system prompt; long system prompts, fixed knowledge bases and RAG scenarios usually hit more often.
Can pricing change?
Yes. Cache prices and rules from each vendor change over time, so always check the latest official pricing.