Inference cost calculator
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The dominant cost of an AI app is the LLM calls — and almost nobody can estimate it. Pick what you're building, tune the assumptions, and compare 29 models across OpenAI, Anthropic, Google, xAI, Mistral, OpenRouter and Workers AI.
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What are you building?
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Daily active users
Usage assumptions (all editable)
Agent steps count as calls, not runs.
System prompt + history + retrieved context. ~4 chars ≈ 1 token.
Output tokens cost 4–6× more than input on most models.
Share of input tokens billed at the provider's cached rate (~90% cheaper).
publishes no cached-input discount, so the cache rate is ignored for it.
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Estimated monthly inference bill ·
/mo
per user / month
per LLM call
Fresh input Cached input Output
calls · input tokens · output tokens per month
Suggested for these assumptions
at scale
| Daily active users | Monthly bill | Per user |
|---|---|---|
| ← you |
Every model, same assumptions
Sorted by monthly bill. Click a row to select that model.
| Model | Provider | Tier | $/mo | $/user | vs selected |
|---|---|---|---|---|---|
| open |