A standard 10 pages document (~5,000 words / 6,665 tokens) costs $0.000866 to ingest and $0.000866 to generate a comprehensive executive summary using Text Embedding 3 (Large).
Feed the entire 10 pages document into context to extract fields, entities, or answer queries.
Ingest 10 pages and generate a structured 500-token executive summary with key takeaways.
Translate or reformat the entire 10 pages document into an equivalent length output.
| Model | Provider | Ingestion (10 pages) | Cached Ingestion | Summary Cost | Context Limit |
|---|---|---|---|---|---|
| Text Embedding 3 (Large) (Current) | openai | $0.000866 | $0.000217 | $0.000866 | 8,191 |
| Text Embedding 3 (Small) | openai | $0.000133 | $0.000033 | $0.000133 | 8,191 |
| Text Embedding 004 | $0.000133 | $0.000033 | $0.000133 | 8,192 |
Assuming a standard single-spaced document with ~500 words per page, a 10 pages document contains approximately 5,000 words, which translates to roughly 6,665 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 10 pages document consumes only 81.37% 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 $0.000866. Using 24-hour async batch API queues drops this cost to $0.000433.
If your workflow repeatedly queries or chats with this same 10 pages document, prompt caching reduces subsequent turn input costs by up to 90% (to $0.000217 per turn instead of $0.000866).