Best Multi-Language OCR APIs with Handwriting Support 2026
The short answer
For multi-language documents with handwriting, use Google Document AI or Azure Document Intelligence; for LLM-ready structured output, use Mistral OCR 4.1; avoid Amazon Textract outside English and five Western European languages. Google’s Enterprise Document OCR and Azure’s Read model both cost about $1.50 per 1,000 pages and read printed and handwritten text across many scripts. Mistral OCR 4.1 costs more ($4 per 1,000 pages) but returns Markdown, tables and confidence scores ready for a RAG pipeline. Prices are list USD as of October 15, 2026.
The comparison
| API | Price (per 1,000 pages) | Languages | Handwriting | Output | Best for |
|---|---|---|---|---|---|
| Google Document AI — Enterprise Document OCR | $1.50 (1K–5M pages/month; first 1,000 free) | Broad list; auto-detection plus language hints | Yes, with handwriting hints | Text, layout, image-quality score, rotation correction | Widest scripts, GCP shops |
| Azure Document Intelligence — Read | About $1.50 (Layout and prebuilt about $10) | Broad list; mixed-language lines, no language code needed | Yes, separate handwriting language list | Text lines, words, language detection | Mixed-language documents, Microsoft shops |
| Mistral OCR 4.1 | $4 ($2 Batch); $5 annotated | Strong in 40+ languages | Yes | Markdown/HTML tables, blocks, confidence scores | RAG and LLM pipelines |
| Amazon Textract | $1.50 first 1M, $0.60 after (Detect Document Text) | Printed: English, German, French, Spanish, Italian, Portuguese | English only | Text, forms, tables, queries | English and Western European forms on AWS |
Why each one is where it is
Google Document AI. Enterprise Document OCR is Google’s specialized OCR processor. It detects the languages in extracted text, accepts language and handwriting hints for known document types, and returns an image-quality score and font-style attributes. Pricing is $1.50 per 1,000 pages from 1,000 to 5 million pages a month, with the first 1,000 free. Its Form Parser and custom extractors cost far more ($30 per 1,000 pages for Form Parser), so use plain OCR plus an LLM for field extraction unless you need Google’s schemas.
Azure Document Intelligence. The Read model is the OCR engine under every Azure prebuilt model. Microsoft’s documentation says the universal models extract multilingual text, including lines that mix languages, without a language code, and lists printed and handwritten language support separately. Read costs about $1.50 per 1,000 pages; Layout, which adds tables, titles and selection marks, is about $10. Pick Azure when documents mix languages on one page — bilingual contracts, customs forms, immigration paperwork.
Mistral OCR 4.1. Mistral’s OCR keeps document structure and returns tables as Markdown or HTML, headers and footers separately, paragraph-level blocks with bounding boxes, and confidence scores at page, block or word level. Mistral says it performs strongly across more than 40 languages. At $4 per 1,000 pages ($2 with Batch) it costs more than the clouds, but it saves a post-processing step when the output goes straight into an LLM.
Amazon Textract. Strong on forms and tables, but its FAQ limits printed text to six languages and handwriting, invoices, IDs and Queries to English. Use it only when your documents fit.
How to choose by document type
- Handwritten forms in many languages: Google Document AI with handwriting hints, then Azure Read as a second opinion.
- Mixed-language pages (two scripts on one line): Azure Read.
- Scanned reports, manuals or contracts going into RAG: Mistral OCR 4.1.
- English invoices and tax forms on AWS: Textract Analyze Document.
- Millions of archive pages a month: price Google and Textract volume tiers, and consider a backfile conversion service for paper.
For complex tables see best OCR for handwriting and complex tables; for vendor platforms with workflow and human review, see enterprise AI OCR vendors.
Last verified: October 15, 2026. Prices are list USD; Azure figures are approximate as published by Microsoft and vary by region.