Token Use Model Pricing

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Token Use Model Pricing

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Monthly cost —

Inputs

Project assumptions

Quick setup

Five inputs for a working estimate. Presets fill the rest.

AI system type Primary model Monthly active users Workflows per user / month Revenue per user / month ($)

Tokens, OCR, review rates, pricing overrides

Demand detail

Fine-tune how many calls and retries each workflow generates.

Model calls per workflow Retry overhead %

Core LLM workload

Per-call token assumptions and optimization levers.

Input tokens per call Output tokens per call Cache-hit share % Batch-processed share %

⚠ High cache hit rate and high batch share are rarely achievable together. Real-time workloads (high cache hits) can’t be batched; batch workloads typically have unique inputs and low cache hits. Stacking both may understate true cost.

Tools and extras Optional

Add the workflow pieces beyond token inference. Set any field to 0 to exclude it.

Web searches per workflow Times the AI calls a web search tool (e.g. Bing, Brave, Tavily) per run. Set to 0 if no search tool used. Search content tokens / search Tokens from search results injected into the prompt per search call. Typically 500–3,000. Embedding tokens / month Total tokens sent to an embedding model per month (for RAG / semantic search). Set to 0 if no embeddings used. OCR pages per workflow Pages processed by an OCR service (e.g. AWS Textract, Google Document AI) per workflow run. Set to 0 if no document scanning.

Team and operating costs Optional

Infrastructure and overhead costs. Set any field to 0 to exclude it — token-only pipelines can skip this section entirely.

What is fixed infra?

Infrastructure costs that stay roughly the same regardless of how many requests you handle — hosting, monitoring (e.g. Datadog, Sentry), auth services, CI/CD pipelines. This is your actual monthly bill, not a calculated estimate. Enter your own number or set to 0 if unknown.

Fixed infra / month ($) Monthly cost of hosting, monitoring, auth, CI/CD — things that don’t scale with usage. Set to 0 if unknown. Vector / storage / month ($) Pinecone, Weaviate, pgvector hosting, or similar. Set to 0 if not using a vector database. Contingency buffer % Safety margin for unexpected usage spikes. 10–20% is typical. Target gross margin % Used to calculate the minimum price you’d need to charge per user. Set to 0 to skip pricing analysis.

Pricing overrides

Model preset fills these. Override for custom plans or different architectures.

Model input $ / 1M tokens Cached input $ / 1M tokens Model output $ / 1M tokens Web search $ / 1K calls Search content $ / 1M tokens Embeddings $ / 1M tokens OCR $ / page Batch discount on core LLM %

Caching applies to cache-hit share of input tokens only. Batch discount applies to core model inference only.

Output

Cost estimate

Model preset

API / usage costs calculated from published rates × your volume estimates

API cost / month

$0

Tokens + OCR + embeddings + search

API cost per workflow

$0

Cost per request / run at expected volume

Full stack estimate includes your operating inputs — not calculated

+ Operating overhead / month

$0

Infra + storage — your estimates

Total estimate / month

$0

API cost + operating overhead

Cost per active user

$0

API + infra ÷ users (excl. contingency)

Price for target gross margin

$0

Based on variable API costs only

Yearly run-rate

$0

Monthly × 12 — flat rate, no price decay

Scenario range

P10 / P50 / P90 — volume multipliers only, rates are fixed. Distribution is right-skewed: P90 is further from median than P10.

P10 $0 lean adoption

P50 $0 median case

P90 $0 heavy usage

Profitability

Based on your revenue per user assumption.

Monthly revenue

$0

Revenue per user × active users

Monthly profit

$0

Revenue minus total monthly cost

Gross margin

—

Net profit as % of revenue

Break-even users

—

Users needed to cover costs

Workload summary

Monthly volume your architecture needs to absorb.

Workflows / month 0

Model calls / month 0

Input tokens / month 0

Output tokens / month 0

Search calls / month 0

OCR pages / month 0

Cost breakdown

Which components dominate the estimate.

What’s driving cost

Where to optimise first.

Pricing references

Sources for the editable defaults in this calculator.

OpenAI API pricing
Anthropic pricing
AWS Textract pricing

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Token Use Model Pricing © 2026 · Prices from public provider docs · Estimates only — verify before budgeting