A standard 250 pages document (~125,000 words / 160,000 tokens) costs $0.40 to ingest and $0.405 to generate a comprehensive executive summary using GPT-4o (Omni).
Feed the entire 250 pages document into context to extract fields, entities, or answer queries.
Ingest 250 pages and generate a structured 500-token executive summary with key takeaways.
Translate or reformat the entire 250 pages document into an equivalent length output.
| Model | Provider | Ingestion (250 pages) | Cached Ingestion | Summary Cost | Context Limit |
|---|---|---|---|---|---|
| GPT-4o (Omni) (Current) | openai | $0.40 | $0.20 | $0.405 | 128,000 |
| GPT-5.6 Sol | openai | $0.80 | $0.08 | $0.815 | 1,050,000 |
| GPT-5.6 Cyber | openai | $2.00 | $0.20 | $2.038 | 1,050,000 |
| GPT-5.5 Standard | openai | $0.80 | $0.08 | $0.815 | 512,000 |
| GPT-5.5 Pro | openai | $4.80 | $0.48 | $4.89 | 512,000 |
| o3-pro (Frontier Reasoning) | openai | $3.20 | $0.32 | $3.24 | 1,000,000 |
Assuming a standard single-spaced document with ~500 words per page, a 250 pages document contains approximately 125,000 words, which translates to roughly 160,000 tokens using GPT-4o (Omni)'s tokenizer. Dense PDF tables, legal boilerplate, and OCR scans may increase this by 20–30%.
GPT-4o (Omni) has a context window of 128,000 tokens. A 250 pages document consumes only 125.00% 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 $0.405. Using 24-hour async batch API queues drops this cost to $0.2025.
If your workflow repeatedly queries or chats with this same 250 pages document, prompt caching reduces subsequent turn input costs by up to 90% (to $0.20 per turn instead of $0.40).