A standard 5 pages document (~2,500 words / 3,333 tokens) costs $0.000467 to ingest and $0.000607 to generate a comprehensive executive summary using DeepSeek Coder V2.5.
Quick answer
A 5 pages document is modeled as 2,500 words or 3,333 tokens. With DeepSeek Coder V2.5, ingestion costs $0.000467; a 500-token executive summary brings the modeled total to $0.000607.
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 5 pages document into context to extract fields, entities, or answer queries.
Ingest 5 pages and generate a structured 500-token executive summary with key takeaways.
Translate or reformat the entire 5 pages document into an equivalent length output.
| Model | Provider | Ingestion (5 pages) | Cached Ingestion | Summary Cost | Context Limit |
|---|---|---|---|---|---|
| DeepSeek Coder V2.5 (Current) | deepseek | $0.000467 | $0.000047 | $0.000607 | 128,000 |
| GPT-5.3 Codex | openai | $0.0056 | $0.00056 | $0.0126 | 256,000 |
| Codestral 2501 | mistral | $0.001 | $0.00010 | $0.00145 | 256,000 |
| Grok Build 0.1 | xai | $0.003333 | $0.000667 | $0.004333 | 256,000 |
| Qwen 2.5 Coder 32B | qwen | $0.000667 | $0.000067 | $0.000967 | 128,000 |
| GLM-5.3 (Z.ai) | zai | $0.004666 | $0.000867 | $0.006866 | 1,048,576 |
Assuming a standard single-spaced document with ~500 words per page, a 5 pages document contains approximately 2,500 words, which translates to roughly 3,333 tokens using DeepSeek Coder V2.5's tokenizer. Dense PDF tables, legal boilerplate, and OCR scans may increase this by 20–30%.
DeepSeek Coder V2.5 has a context window of 128,000 tokens. A 5 pages document consumes only 2.60% 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 $0.000607. Using 24-hour async batch API queues drops this cost to $0.000303.
If your workflow repeatedly queries or chats with this same 5 pages document, prompt caching reduces subsequent turn input costs by up to 90% (to $0.000047 per turn instead of $0.000467).