Estimate meeting-summary AI cost before it adds up

Enter how many meetings you summarize with AI each month to get a Low / Likely / High monthly API cost estimate. Everything runs locally in your browser — no data is sent to any server.

  • No login
  • No credit card
  • No API calls
  • Estimate only

Configure your meeting summaries

Estimated monthly cost

This estimates the cost of summarizing a transcript you already have. It does not include audio transcription / speech-to-text cost — that is billed separately by your transcription provider.

Likely monthly cost$0.1402Estimated range: $0.0957$0.1920
Cost per meeting
Low$0.004785Likely$0.007012High$0.009600
Input tokens / meeting
Low3.5KLikely4.8KHigh6.2K
Output tokens / meeting
Low480Likely750High1.1K
Monthly input tokens
Low70KLikely97KHigh124K
Monthly output tokens
Low9.6KLikely15KHigh22K

This is an estimate, not a billing guarantee. Actual costs depend on your provider's exact tokeniser, real meeting length, and your billing tier.

Understand & trust these numbers Methodology What are AI tokens? Why bills surprise you Chatbot calculator

How this estimate works

Input — you send
  • Instruction / system prompt
  • The meeting transcript
Model

Reads the full transcript, then writes a summary.

Output — you get

A summary, and optionally an action-items/decisions list.

Transcript size scales with meeting duration and how densely people talk — a fast, overlapping discussion produces more transcript tokens per minute than a slow, sparse one.

What's not included: transcription

This calculator estimates the cost of summarizing a transcript you already have — it does not include audio transcription (speech-to-text) cost.

If your pipeline also transcribes audio to text, that step is billed separately by your transcription provider (e.g. a speech-to-text API) and is not part of this estimate.

Low / Likely / High explained

Low

Sparse-speech transcript, brief instruction prompt.

Likely

Typical speaking pace and a standard instruction prompt. Plan against this number.

High

Dense, fast-paced transcript and a detailed instruction prompt. Budget against this.

Cut your cost

1
Keep the instruction prompt tight. It repeats on every single meeting you summarize.
2
Choose "brief" when you can. Output tokens usually cost more than input tokens per token.
3
Match model to task. Routine standups rarely need a frontier-tier model.

Example monthly costs

These worked examples use the same default assumptions as the calculator above — typical speech density, a standard summary length, a standard instruction prompt, action items on — with GPT-5.4 Mini. Only the number of meetings per month changes between rows. Use the calculator above to model your own usage or a different model.

Usage levelMeetings / monthLowLikelyHigh
Light usage 5 $0.0239 $0.0351 $0.0480
Typical usage 20 $0.0957 $0.1402 $0.1920
Heavy usage 80 $0.3828 $0.5610 $0.7680

Caveats

  • These estimates use the formula characters ÷ 4 ≈ tokens, accurate to ±10–15% for plain English text.
  • Each provider uses a different tokeniser. Actual token counts may differ ±5–10% between OpenAI, Anthropic, Google, Mistral, and DeepSeek for the same content.
  • Audio transcription (speech-to-text) cost is not included. This tool only estimates the cost of the summarization call itself.
  • Prices shown are manually verified against each provider's official pricing page as of 2026-09-08. AI provider pricing changes frequently — verify at your provider's official pricing page before making budget decisions.
  • Transcript density is a rough proxy for how many tokens a minute of audio produces once transcribed — real transcripts vary with accent, cross-talk, and transcription quality.
  • The context-window warning above appears when the High scenario's combined tokens exceed 80% of the selected model's context window — a safety margin before truncation or failure risk, not a hard limit at 100%.

This is an estimate, not a billing guarantee. Always confirm against your provider's usage dashboard and official pricing before committing a budget.