A standard 10 pages document (~5,000 words / 6,665 tokens) costs $0.002799 to ingest and $0.004299 to generate a comprehensive executive summary using Qwen3.8 27B (OpenRouter).
Quick answer
A 10 pages document is modeled as 5,000 words or 6,665 tokens. With Qwen3.8 27B (OpenRouter), ingestion costs $0.002799; a 500-token executive summary brings the modeled total to $0.004299.
Method & trust
The page uses approximately 500 words per page, estimates tokens with the selected model tokenizer, and prices input plus a 500-token summary at the model's listed rates. OCR, tables, and formatting can increase the actual count.
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 |
|---|---|---|---|---|---|
| Qwen3.8 27B (OpenRouter) (Current) | qwen | $0.002799 | $0.0007 | $0.004299 | 1,000,000 |
| GPT-5.6 Terra | openai | $0.0128 | $0.00128 | $0.0188 | 1,050,000 |
| GPT-5.4 Workhorse | openai | $0.016 | $0.0016 | $0.0235 | 256,000 |
| o3-mini | openai | $0.00704 | $0.00352 | $0.00924 | 200,000 |
| o4-mini | openai | $0.00704 | $0.00176 | $0.00924 | 256,000 |
| o1-mini | openai | $0.00704 | $0.00352 | $0.00924 | 128,000 |
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 Qwen3.8 27B (OpenRouter)'s tokenizer. Dense PDF tables, legal boilerplate, and OCR scans may increase this by 20–30%.
Qwen3.8 27B (OpenRouter) has a context window of 1,000,000 tokens. A 10 pages document consumes only 0.67% 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 $0.004299. Using 24-hour async batch API queues drops this cost to $0.00215.
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 $0.0007 per turn instead of $0.002799).