A standard 1 page document (~500 words / 667 tokens) costs $0.00026 to ingest and $0.00143 to generate a comprehensive executive summary using Qwen3.5 397B A17B (OpenRouter).
Quick answer
A 1 page document is modeled as 500 words or 667 tokens. With Qwen3.5 397B A17B (OpenRouter), ingestion costs $0.00026; a 500-token executive summary brings the modeled total to $0.00143.
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 1 page document into context to extract fields, entities, or answer queries.
Ingest 1 page and generate a structured 500-token executive summary with key takeaways.
Translate or reformat the entire 1 page document into an equivalent length output.
| Model | Provider | Ingestion (1 page) | Cached Ingestion | Summary Cost | Context Limit |
|---|---|---|---|---|---|
| Qwen3.5 397B A17B (OpenRouter) (Current) | qwen | $0.00026 | $0.000065 | $0.00143 | 262,144 |
| GPT-5.6 Sol | openai | $0.0032 | $0.00032 | $0.0182 | 1,050,000 |
| GPT-5.6 Cyber | openai | $0.008 | $0.0008 | $0.0455 | 1,050,000 |
| GPT-5.5 Standard | openai | $0.0032 | $0.00032 | $0.0182 | 512,000 |
| GPT-5.5 Pro | openai | $0.0192 | $0.00192 | $0.1092 | 512,000 |
| o3-pro (Frontier Reasoning) | openai | $0.0128 | $0.00128 | $0.0528 | 1,000,000 |
Assuming a standard single-spaced document with ~500 words per page, a 1 page document contains approximately 500 words, which translates to roughly 667 tokens using Qwen3.5 397B A17B (OpenRouter)'s tokenizer. Dense PDF tables, legal boilerplate, and OCR scans may increase this by 20–30%.
Qwen3.5 397B A17B (OpenRouter) has a context window of 262,144 tokens. A 1 page document consumes only 0.25% 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 $0.00143. Using 24-hour async batch API queues drops this cost to $0.000715.
If your workflow repeatedly queries or chats with this same 1 page document, prompt caching reduces subsequent turn input costs by up to 90% (to $0.000065 per turn instead of $0.00026).