The best AI models for data extraction, ranked by extraction score. JSON mode is critical for structured output, vision enables document and image reading, and function calling powers pipeline integration. Updated hourly from 367+ models.
129
JSON Mode
152
With Vision
132
Function Calling
145
128K+ Context
| # | Model | Score |
|---|---|---|
| 1 | GPT-5.4 ProOpenAI | 115 |
| 2 | GPT-5.4OpenAI | 115 |
| 3 | GPT-5.2 ProOpenAI | 114 |
| 4 | Claude Opus 4.6 (Fast)Anthropic | 113 |
| 5 | Claude Opus 4.6Anthropic | 113 |
| 6 | GPT-5.2-CodexOpenAI | 113 |
| 7 | GPT-5.2OpenAI | 113 |
| 8 | Grok 4.20xAI | 112 |
| 9 | GPT-5.3-CodexOpenAI | 112 |
| 10 | GPT-5 ProOpenAI | 112 |
| 11 | Gemini 3 Flash PreviewGoogle | 111 |
| 12 | Grok 4xAI | 111 |
| 13 | GPT-5.1-Codex-MaxOpenAI | 111 |
| 14 | GPT-5 CodexOpenAI | 111 |
| 15 | GPT-5OpenAI | 111 |
| 16 | GPT-5.3 ChatOpenAI | 110 |
| 17 | GPT-5.1OpenAI | 110 |
| 18 | GPT-5.1-CodexOpenAI | 110 |
| 19 | GPT-5.1-Codex-MiniOpenAI | 110 |
| 20 | o3 Deep ResearchOpenAI | 110 |
| 21 | o3 ProOpenAI | 110 |
| 22 | o3OpenAI | 110 |
| 23 | GPT-5.1 ChatOpenAI | 110 |
| 24 | Claude Sonnet 4.6Anthropic | 108 |
| 25 | Claude Opus 4.5Anthropic | 108 |
Extract structured data from PDFs, contracts, and reports. Models with vision can read scanned documents and handwritten text, while JSON mode ensures output is machine-parseable for downstream systems. Ideal for automating document intake pipelines.
Automatically parse invoices, receipts, and financial documents into structured fields -- vendor name, line items, totals, tax amounts, and dates. Vision-capable models handle photographed or scanned receipts with high accuracy.
Feed raw HTML or page text into an LLM to extract product details, pricing, reviews, or article metadata. JSON mode guarantees consistent output schemas, and function calling enables multi-page crawl orchestration from a single prompt.
Function calling lets extraction models plug directly into your data pipeline -- calling APIs, writing to databases, or triggering downstream transformations. Combined with JSON mode, this enables fully automated ETL workflows powered by AI.
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Yes, vision-capable models extract tables, forms, and key-value pairs from PDFs, images, and scanned documents. JSON mode ensures the output is machine-readable. Reasoning handles complex layouts where traditional OCR fails (multi-column, nested tables, handwritten annotations).
Top vision models achieve 95-99% accuracy on printed documents and 85-95% on handwritten text. Accuracy depends on document quality, layout complexity, and domain-specific terminology. Always implement validation rules and human review for critical data.
Models with web search and function calling can scrape structured data from web pages. JSON mode ensures consistent output format. For large-scale extraction, combine AI with traditional scraping tools and use models for the parsing/structuring step.
Vision models process PDFs, images (JPEG, PNG), scanned documents, and screenshots. Models without vision handle plain text, HTML, CSV, and JSON. For best results on complex documents, use vision-capable models that can see the actual layout.