How To Plan LLM Spend With Prompt Tokenizer
A practical workflow to estimate token usage, predict monthly bills, and catch expensive prompts early.
Start with real prompts, not toy examples
Take 10 to 20 prompts from production logs or staging test suites. Mixed lengths are important because a single average prompt hides long-tail cost spikes.
Paste each prompt into Prompt Tokenizer and track input tokens, expected output tokens, and total cost per request.
Use percentile budgeting
Do not budget against the average prompt only. Track p50, p90, and p99 token usage.
If your p99 is 4x p50, set guardrails in code for max output tokens and fail fast when context is too large.
- p50 controls baseline cost
- p90 controls typical peak days
- p99 controls incident-level overspend
Convert to monthly spend with confidence bands
Multiply cost per request by expected request volume. Then create low, base, and high scenarios with +/-20% traffic variation.
This gives product and finance teams a realistic range instead of a single fragile number.