Prompt Compression Savings Calculator

See savings from shortening your prompts.

Quick answer

With the default inputs, $300.00/month saved — 4,000 tokens → 2,400 tokens per prompt. Enter your own numbers below to recompute instantly; the full step-by-step math is shown under the worked example.

Model

Prompt tokens (before)(tokens)

Reduction %(%)

Requests per day

Results update automatically as you type.

Result

$300.00/month saved

4,000 tokens → 2,400 tokens per prompt

Before: 4,000 tokens
After: 2,400 tokens
Saved / request: $0.00200
Saved / month: $300.00

Trimming, summarizing or compressing prompts reduces input tokens on every call. Set your current prompt size and target reduction to see the monthly savings.

How this is calculated

Savings = before tokens × reduction % × requests × input price. Trimming, summarizing or compressing the prompt reduces input tokens on every call, so a one-time editing effort pays back continuously across your volume.

Is this a good result? What to do next

The higher your volume, the more even a modest reduction is worth. But cutting too far removes context the model needs, so treat the dollar figure as the upside and always re-test accuracy after each trim.

Typical planning ranges

Savings scale with: reduction % × volume
Safe cuts: redundant instructions, filler
Risky cuts: essential context / examples

Ranges are typical planning figures to sanity-check your result, not authoritative benchmarks. Your numbers will vary with use case, volume, and vendor.

How to improve this number

Remove redundant instructions and restate rules once.
Summarize long context instead of inlining it verbatim.
Reference stored content rather than pasting it each call.

Common mistakes

Over-compressing and losing accuracy.
Not re-testing quality after cutting the prompt.

When to use a different approach

If the content is stable rather than compressible, caching may save more — use the prompt caching savings calculator. For the fixed prompt, use the system prompt cost calculator.