LLM Context Token Cost Forecaster

Forecast how much a large language model integration will cost as you stretch the context window. Provide average prompt and completion token counts along with per-thousand pricing to surface per-call cost, monthly burn, total tokens per request, and a drift range that captures retries or longer completions.

Tokens sent in the prompt for each request after system and user messages.
Tokens returned by the model per response on average.
Provider rate charged for prompt tokens (per 1,000).
Provider rate charged for completion tokens (per 1,000).
Optional. Defaults to 50,000 requests per month if left blank.
Optional. Defaults to ±20% swing if left blank.

Token pricing may change without notice; always confirm with your API provider before budgeting.

Examples

  • 2,600 prompt tokens, 1,200 completion tokens, $0.002 prompt rate, $0.006 completion rate, 150,000 calls, 20% drift → Cost per call $0.0116; 150,000 calls → $1,740.00 per month; Drift ±20.00% → $1,392.00 to $2,088.00.
  • 1,400 prompt tokens, 700 completion tokens, $0.0025 prompt rate, $0.004 completion rate, 80,000 calls, 30% drift → Cost per call $0.0063; 80,000 calls → $504.00 per month; Drift ±30.00% → $352.80 to $655.20.

FAQ

Can I compare multiple models?

Yes. Rerun the calculator with each model's pricing and token profile, then benchmark the cost per call and drift band side-by-side.

How do I include embedding or storage costs?

Add those expenses to the monthly cost result outside the calculator, or create a separate scenario using the provider's embedding token pricing and add the totals.

What if my usage fluctuates weekly?

Input an average monthly call volume and increase the token drift percentage so the upper end of the range captures peak traffic.

Can I model truncation or response throttling?

Yes. Reduce the completion token average to reflect enforced caps, then rerun the calculation to see the savings versus letting completions run long.

Additional Information

  • Token counts convert directly to spend using provider per-1,000 token pricing; cost per call is rounded to four decimals for accuracy on sub-cent requests.
  • Monthly call volume defaults to 50,000 if blank, helping you model pilots without researching exact volumes.
  • Drift percentage models request inflation from prompt chaining, retries, or longer completions and calculates both downside and upside spend scenarios.
  • Tokens per request output adds prompt and completion counts so you can compare against model context limits.

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