Cost Estimation
Costs depend on model pricing, OCR requirements, document size, image usage, and retry rate. The estimates below are practical planning ranges for a document of about five pages.
These values are indicative and must be recalculated against the active provider price list before production budgeting.
Assumptions
- Five-page document.
- One classification pass.
- One extraction pass.
- Optional validation pass for complex documents.
- OCR cost excluded unless provider includes vision/image processing.
- Output JSON is small compared with input.
Estimated cost per document
| Provider | Simple document | Complex document | Notes |
|---|---|---|---|
| OpenAI GPT | $0.01 - $0.05 | $0.05 - $0.20 | Higher accuracy and reliable structured output. |
| Anthropic Claude | $0.02 - $0.08 | $0.08 - $0.30 | Good for long contracts and legal text. |
| Google Gemini | $0.01 - $0.06 | $0.05 - $0.25 | Good multimodal option for scans and image-heavy bills. |
| DeepSeek | < $0.01 - $0.03 | $0.02 - $0.10 | Cost-effective for simpler text extraction. |
Cost drivers
- page count
- scanned image quality
- OCR requirement
- number of retry attempts
- need for multiple model passes
- context length
- validation and self-check prompts
Accuracy vs cost trade-off
Low-cost models can be effective for invoices and simple schedules. Contracts, tax documents, and ownership documents justify more accurate models because errors have legal or fiscal impact.
Suggested policy
- Use the cheapest model that consistently passes validation for a document type.
- Route high-risk documents to higher-accuracy models.
- Track cost per successful confirmed extraction, not only cost per API call.
- Include retries and manual correction time in real cost analysis.