Cost to Extract Data from 1,000 Documents with LLM APIs
Calculate the real cost of using LLM APIs to extract structured data from documents like invoices, receipts, and forms. Compare all models with verified pricing.
Prices verified as of Aug 9, 2026 · 178 models tracked
Your workload
Token breakdown — 5K in / 500 out per document
Total tokens: —
What it costs
Cheapest
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Average
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Most expensive
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MODELPRICEWATCH.COM · 2026-08-09
Cost per documents across 178 models
cheapest 15 as bars · full table belowLoading…
Show all 178 models in a table
| Model | Provider | Input $/1M | Output $/1M | Cost for 1K documents |
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How this calculator works
Each document data extraction requires ~5,000 input tokens (the document content — invoice, receipt, form, or contract) and ~500 output tokens (the structured JSON/field data extracted). Input tokens dominate because the model must read the full document. Documents with images require multimodal models, which may have different pricing.
Formula: cost = (input_tokens × input_price_per_Mtok + output_tokens × output_price_per_Mtok) × quantity / 1,000,000
All prices are per million tokens, sourced directly from official provider pricing pages. No fabricated numbers — every model in the table links to its detail page, which cites the official pricing source.
Frequently asked questions
How much does it cost to extract data from 1,000 documents with an LLM?
It depends on the model. Extraction is input-dominated (~5,000 input / ~500 output tokens per document) because the model reads each full document. The calculator above computes the exact current cost for every model, cheapest-first, from live per-million-token pricing — the table above gives the exact per-model cost at your document volume.
Which LLM is best for document data extraction?
For text documents, the models at the top of the cost table above give the lowest cost. For scanned documents or images you need a multimodal (vision-capable) model — filter the table accordingly. Prompt caching helps when you process many similar documents.
How are data extraction token costs calculated?
Each document uses ~5,000 input tokens (document text) and ~500 output tokens (extracted data). Total cost = (input_tokens × input_price + output_tokens × output_price) × number_of_documents. Prices are per million tokens, verified from official sources.