A standard 25 pages document (~12,500 words / 16,663 tokens) costs $0.002166 to ingest and $0.002166 to generate a comprehensive executive summary using Text Embedding 3 (Large).
Feed the entire 25 pages document into context to extract fields, entities, or answer queries.
Ingest 25 pages and generate a structured 500-token executive summary with key takeaways.
Translate or reformat the entire 25 pages document into an equivalent length output.
| Model | Provider | Ingestion (25 pages) | Cached Ingestion | Summary Cost | Context Limit |
|---|---|---|---|---|---|
| Text Embedding 3 (Large) (Current) | openai | $0.002166 | $0.000542 | $0.002166 | 8,191 |
| Text Embedding 3 (Small) | openai | $0.000333 | $0.000083 | $0.000333 | 8,191 |
| Text Embedding 004 | $0.000333 | $0.000083 | $0.000333 | 8,192 |
Assuming a standard single-spaced document with ~500 words per page, a 25 pages document contains approximately 12,500 words, which translates to roughly 16,663 tokens using Text Embedding 3 (Large)'s tokenizer. Dense PDF tables, legal boilerplate, and OCR scans may increase this by 20–30%.
Text Embedding 3 (Large) has a context window of 8,191 tokens. A 25 pages document consumes only 203.43% of its total window, easily fitting in a single prompt without requiring chunking or vector search.
Ingesting the document and outputting a concise 500-token executive summary costs $0.002166. Using 24-hour async batch API queues drops this cost to $0.001083.
If your workflow repeatedly queries or chats with this same 25 pages document, prompt caching reduces subsequent turn input costs by up to 90% (to $0.000542 per turn instead of $0.002166).