Prompt Compression Calculator
Calculate the token and cost savings from compressing a prompt, comparing the original and compressed token counts at a given price.
Last reviewed by the Radiatus Cloud team
Calculate token and cost savings from compressing a prompt.
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Calculate prompt compression savings
Prompt compression reduces the number of tokens a prompt uses, through summarising context, removing redundancy or using more concise instructions, which lowers both cost and latency. This calculator quantifies the benefit by comparing the original and compressed token counts, showing the reduction percentage, the compression ratio, and the total tokens and money saved across a volume of requests. Cutting a four-thousand-token prompt to sixteen hundred is a sixty percent reduction.
Because cost scales with tokens, the savings multiply quickly across many requests.
Why compress prompts
For applications that send large, repetitive context on every request, compression can substantially cut the bill and speed up responses, since fewer input tokens mean less processing. Techniques range from simple trimming and deduplication to automated prompt-compression methods that preserve meaning while removing filler. The compression ratio gives a clear sense of how aggressively a prompt has been shortened.
Compression must preserve the information the model needs, so there is a balance between saving tokens and maintaining output quality. All calculation happens locally in your browser.
Notes on these estimates
Because the prompt compression calculator runs entirely in your browser, nothing you enter is uploaded, so you can use it with private data safely. The figures are estimates based on the values you provide and common rules of thumb, so treat them as planning guidance rather than exact measurements, and run the tool as often as you need for free.
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Frequently Asked Questions
How is the saving calculated?
It is the difference between the original and compressed token counts, multiplied by the number of requests and the price per token.
What is the compression ratio?
It is the original token count divided by the compressed count, so a four-to-one ratio means the prompt is a quarter of its original size.
Does compression affect quality?
It can if important information is removed. Good compression preserves the content the model needs while cutting redundancy and filler.
Where does compression help most?
In applications that repeatedly send large, repetitive context, where reducing input tokens cuts both cost and latency across many requests.
Privacy & Security
Everything runs in your browser; nothing is uploaded.
How to Use
Enter the original and compressed token counts and the price.
Disclaimer: This tool is provided "as is" without warranty of any kind. Results are for educational and utility purposes.
Related Tools
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