About this LLM Token Cost Calculator
LLM pricing is usually based on separate input and output token rates. This calculator helps translate source-dated model presets or custom token rates into per-call, batch, and monthly budget estimates.
When to use it
- Budget a new AI feature before production launch.
- Compare shorter prompts against longer retrieval-augmented prompts.
- Estimate one-time batch processing and recurring monthly spend.
- Check whether output length or context size is driving cost.
How to use this calculator
- Enter the average input and output tokens for one request.
- Choose a source-dated model pricing preset or select custom manual prices.
- Review or enter prices per million input and output tokens.
- Add the number of requests in a batch and the expected monthly request volume.
- Review the per-request cost first, then use the batch and monthly estimates for planning.
Key assumptions
- Preset prices are checked-in snapshots and can become stale.
- Custom prices are entered per one million tokens.
- Each request uses the same average input and output token counts.
- The estimate does not include storage, vector search, moderation, retries, taxes, or minimum fees.
- All calculations run locally in the browser.
Dataset sources
- Effective date
- 2026-05-05
- Last reviewed
- 2026-05-05
Use the current provider pricing page or contract terms before making purchasing decisions.
Public provider pricing page; rates can change without notice.
Accuracy and testing
Review formula sources, default test cases, assumptions, unit handling, rounding rules, and changelog for this calculator.
How this calculator works
Inputs explained
Input Tokens
Prompt, system, context, tool, and retrieval tokens sent into the model for one average request.
Output Tokens
Generated tokens returned by the model for one average request.
Model pricing preset
A checked-in pricing snapshot with source metadata. Choose custom if your account, vendor, or contract differs.
Custom prices per million
Manual prices used only when the preset is set to custom.
Requests
A one-time batch size, useful for estimating a test run, migration, or backfill.
Monthly Requests
Expected monthly volume for budgeting recurring usage.
Understanding your results
Example scenarios
Support Chat Estimate
A chat workflow averaging 1,200 input tokens and 350 output tokens can be multiplied by expected monthly conversations to estimate support automation spend.
Document Processing Batch
A batch of 5,000 document summaries can be priced before the run by entering average tokens and request count.
Key Features
- Instant Calculation
- Private & Secure
- Mobile Optimized
Tips & Best Practices
- Use recent usage logs to choose realistic average token counts.
- Track input and output tokens separately because their prices often differ.
- Add a buffer for retries, longer conversations, and peak usage.
- Keep sensitive prompt text out of calculators; token counts are enough.