A standard 25 pages document (~12,500 words / 16,663 tokens) costs $0.004166 to ingest and $0.004541 to generate a comprehensive executive summary using Gemma 4 31B Instruct.
Feed the entire 25 pages document into context to extract fields, entities, or answer queries.
Ingest 25 pages and generate a structured 500-token executive summary with key takeaways.
Translate or reformat the entire 25 pages document into an equivalent length output.
| Model | Provider | Ingestion (25 pages) | Cached Ingestion | Summary Cost | Context Limit |
|---|---|---|---|---|---|
| Gemma 4 31B Instruct (Current) | $0.004166 | $0.001041 | $0.004541 | 128,000 | |
| GPT-5.6 Terra | openai | $0.032 | $0.0032 | $0.038 | 1,050,000 |
| GPT-5.4 Workhorse | openai | $0.04 | $0.004 | $0.0475 | 256,000 |
| o3-mini | openai | $0.0176 | $0.0088 | $0.0198 | 200,000 |
| o4-mini | openai | $0.0176 | $0.0044 | $0.0198 | 256,000 |
| o1-mini | openai | $0.0176 | $0.0088 | $0.0198 | 128,000 |
Assuming a standard single-spaced document with ~500 words per page, a 25 pages document contains approximately 12,500 words, which translates to roughly 16,663 tokens using Gemma 4 31B Instruct's tokenizer. Dense PDF tables, legal boilerplate, and OCR scans may increase this by 20–30%.
Gemma 4 31B Instruct has a context window of 128,000 tokens. A 25 pages document consumes only 13.02% 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 $0.004541. Using 24-hour async batch API queues drops this cost to $0.00227.
If your workflow repeatedly queries or chats with this same 25 pages document, prompt caching reduces subsequent turn input costs by up to 90% (to $0.001041 per turn instead of $0.004166).