Reducing input tokens
Shorter prompts send fewer input tokens to the model. PromptMeter estimates savings from reducing that input by 10%, 25%, or 50%.
Prompt savings calculator
Paste your prompt to estimate how much you could save by making it shorter. PromptMeter calculates potential savings per prompt run, per 1,000 runs, and per month.
Calculator
Paste a prompt, choose an example pricing profile, and estimate cost per prompt run, per day, and per month.
Input tokens are what you send to the AI model. Output tokens are what the model returns. API providers often price them separately.
Prices are manual for now. Example: if your provider charges $2 input and $10 output per 1M tokens, enter 2 and 10.
Energy usage is a rough estimate. Actual energy depends on model, hardware, provider, datacenter efficiency, workload, and region.
Shorter prompts send fewer input tokens to the model. PromptMeter estimates savings from reducing that input by 10%, 25%, or 50%.
Many AI providers bill input tokens separately, so reducing prompt size can lower the cost of each prompt run.
Savings are calculated only on input tokens. Expected answer tokens stay the same in this version.
The scenarios are mathematical estimates. PromptMeter does not rewrite your prompt yet, though future versions may help make prompts more efficient.
Start with repeated instructions, stable context, output length, examples, and reusable rules separated from variable input.
Removing duplicates is usually low risk. Removing examples or constraints can save more tokens but may reduce answer quality.
| Technique | Potential saving | Risk |
|---|---|---|
| Remove repeated instructions | Low to medium | Low if meaning stays clear |
| Shorten stable context | Medium to high | Medium if important context is removed |
| Reduce examples | Medium | Medium if examples guide the model |
| Control answer length | Medium to high | Low if output requirements are clear |
| Separate reusable instructions from variable input | Medium | Low to medium |
FAQ
It estimates standard input tokens, applies 10%, 25%, and 50% reductions, then calculates potential savings using your input-token price and usage volume.
No. It shows mathematical savings estimates only. You still decide how to shorten or improve the prompt.
AI providers often charge for text sent to the model. Sending fewer input tokens can reduce cost while output assumptions remain unchanged.
Remove duplicated instructions and repeated generic phrases first. They often add cost without improving the answer.