A standard 1 page document (~500 words / 667 tokens) costs $0.001334 to ingest and $0.005334 to generate a comprehensive executive summary using Perplexity Sonar Deep Research.
Quick answer
A 1 page document is modeled as 500 words or 667 tokens. With Perplexity Sonar Deep Research, ingestion costs $0.001334; a 500-token executive summary brings the modeled total to $0.005334.
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 |
|---|---|---|---|---|---|
| Perplexity Sonar Deep Research (Current) | perplexity | $0.001334 | $0.000334 | $0.005334 | 128,000 |
| 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 Perplexity Sonar Deep Research's tokenizer. Dense PDF tables, legal boilerplate, and OCR scans may increase this by 20–30%.
Perplexity Sonar Deep Research has a context window of 128,000 tokens. A 1 page document consumes only 0.52% 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 $0.005334. Using 24-hour async batch API queues drops this cost to $0.002667.
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 $0.000334 per turn instead of $0.001334).