A standard 100 pages document (~50,000 words / 66,650 tokens) costs $0.04 to ingest and $0.0409 to generate a comprehensive executive summary using Databricks DBRX Instruct.
Feed the entire 100 pages document into context to extract fields, entities, or answer queries.
Ingest 100 pages and generate a structured 500-token executive summary with key takeaways.
Translate or reformat the entire 100 pages document into an equivalent length output.
| Model | Provider | Ingestion (100 pages) | Cached Ingestion | Summary Cost | Context Limit |
|---|---|---|---|---|---|
| Databricks DBRX Instruct (Current) | databricks | $0.04 | $0.009998 | $0.0409 | 32,768 |
| GPT-5.6 Terra | openai | $0.128 | $0.0128 | $0.134 | 1,050,000 |
| GPT-5.4 Workhorse | openai | $0.16 | $0.016 | $0.1675 | 256,000 |
| o3-mini | openai | $0.0704 | $0.0352 | $0.0726 | 200,000 |
| o4-mini | openai | $0.0704 | $0.0176 | $0.0726 | 256,000 |
| o1-mini | openai | $0.0704 | $0.0352 | $0.0726 | 128,000 |
Assuming a standard single-spaced document with ~500 words per page, a 100 pages document contains approximately 50,000 words, which translates to roughly 66,650 tokens using Databricks DBRX Instruct's tokenizer. Dense PDF tables, legal boilerplate, and OCR scans may increase this by 20–30%.
Databricks DBRX Instruct has a context window of 32,768 tokens. A 100 pages document consumes only 203.40% 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 $0.0409. Using 24-hour async batch API queues drops this cost to $0.0204.
If your workflow repeatedly queries or chats with this same 100 pages document, prompt caching reduces subsequent turn input costs by up to 90% (to $0.009998 per turn instead of $0.04).