Mistral AI has launched Mistral OCR, a high-performance API for accurate and scalable document processing, capable of extracting structured data from complex documents at 2000 pages per minute. It outperforms leading solutions, achieving 98.96% accuracy in scanned text and excelling in table recognition, multilingual processing, and mathematical expression extraction.
Mistral AI has launched Mistral OCR, a high-performance Optical Character Recognition (OCR) API designed to extract structured data from complex documents with exceptional accuracy and speed. The API is engineered to process up to 2000 pages per minute while preserving document structure, including text formatting, images, tables, and equations.
With an increasing volume of digitised information across industries, Mistral OCR addresses a critical need for accurate and efficient document processing. The API outperforms industry leaders, including Google Document AI, Azure OCR, and OpenAI’s GPT-4o, in various benchmark tests. This advancement positions Mistral OCR as a pivotal tool for enterprises, developers, and organisations requiring structured data extraction at scale.
Key features of Mistral OCR
Mistral OCR has been developed to handle a wide range of document formats while ensuring accuracy in text and structural recognition. Its primary features include:
- Preserving Document Structure: The API extracts text while maintaining formatting, including headers, lists, multi-column text, tables, and embedded images.
- Multilingual Recognition: Supports text extraction in thousands of languages, ensuring accurate results across different scripts.
- Advanced Processing Capabilities: Recognises scanned content, equations, and media while structuring extracted data using bounding boxes and markdown formatting.
- Structured Data Output: Generates results in JSON, Markdown, and other structured formats for easy integration into AI-driven workflows.
Mistral OCR outperforms leading solutions
Mistral OCR has set a new benchmark in document processing, outperforming major industry leaders such as Google, Microsoft, and OpenAI in multiple key areas. With an impressive overall accuracy of 94.89%, the API demonstrates a higher capability for extracting structured data with precision. Its table recognition accuracy of 96.12% surpasses that of GPT-4o and Gemini-1.5-Pro, ensuring that complex tabular data is accurately captured and formatted.
Additionally, Mistral OCR achieves an outstanding 98.96% accuracy for scanned text, making it a more effective solution than Google Document AI for digitising real-world documents. The API also excels in recognising mathematical expressions, reaching 94.29% accuracy, which is higher than Azure OCR, making it particularly beneficial for academic and scientific document processing.
Moreover, Mistral OCR demonstrates exceptional multilingual capabilities, achieving 99.54% accuracy in Spanish, 99.51% in German, and 99.20% in French, ensuring high-quality text extraction across various languages. These results firmly position Mistral OCR as one of the most robust and reliable solutions available for organisations and developers looking to streamline their document processing workflows.
Transforming document processing across industries
Mistral OCR is designed to streamline structured document extraction across multiple industries, enabling businesses and organisations to automate workflows, enhance search capabilities, and efficiently process large volumes of data. In enterprise automation, the API facilitates large-scale text extraction, reducing manual effort and improving data retrieval efficiency.
Legal and financial services benefit from its ability to extract structured information from contracts, regulatory filings, and reports, making compliance and document analysis more accurate. In academic and research settings, Mistral OCR is particularly useful for processing technical papers, extracting formulas, tables, and datasets into machine-readable formats. Additionally, the API enhances AI-powered search and retrieval by improving document indexing and enabling advanced semantic search functionalities.
Users have already found it effective in real-world applications, with Mark Rejhon stating, “I simply attach the PDF file or the smartphone photo (each page) and say ‘Please OCR this’ (three words) and it apparently works great.”
As organisations continue their digital transformation, Mistral OCR offers a scalable and efficient solution for document understanding, ensuring structured data extraction with high accuracy and minimal effort.
Technical Advancements in Mistral OCR
Mistral OCR differentiates itself from traditional OCR technologies by taking a whole-document approach rather than analysing individual characters in isolation. It uses transformer-based AI models with advanced attention mechanisms to understand the document layout and extract information contextually.
The API is built on deep learning algorithms trained to recognise complex structures such as:
- Mathematical expressions in LaTeX notation.
- Programming code snippets with indentation and syntax recognition.
- Database schemas extracted from documentation.
- API endpoints from technical manuals.
This enables Mistral OCR to preserve meaning and relationships within documents, ensuring structured data extraction rather than mere text recognition.
Developer and Enterprise Integration
Mistral OCR is available for developers through Mistral’s developer suite, la Plateforme. It supports multiple deployment options:
- Cloud-based API Access: Allows seamless integration with enterprise systems.
- On-Premises Deployment: Ensures data security and compliance for organisations handling sensitive information.
- Batch Inference: Reduces processing costs by allowing bulk document extraction at a lower rate.
Mistral OCR is now the default model for document processing across millions of users on Le Chat, Mistral’s AI platform. The mistral-ocr-latest API is available at 1000 pages per dollar, with batch inference providing even greater cost efficiency.
Shikha Negi is a Content Writer at ztudium with expertise in writing and proofreading content. Having created more than 500 articles encompassing a diverse range of educational topics, from breaking news to in-depth analysis and long-form content, Shikha has a deep understanding of emerging trends in business, technology (including AI, blockchain, and the metaverse), and societal shifts, As the author at Sarvgyan News, Shikha has demonstrated expertise in crafting engaging and informative content tailored for various audiences, including students, educators, and professionals.
