Mistral AI Launches Advanced OCR API, Outperforming Industry Giants

Mistral's new OCR API turns any PDF document into an AI-ready Markdown file | TechCrunch

Large language models work particularly well with raw text. Companies that want to create their own AI workflow know that it has become extremely important to store and index data in a clean format so that this data can be reused for AI processing. That's why Mistral is launching a new API today for developers who handle complex PDF documents. Mistral OCR is an optical character recognition API that can turn any PDF into a text file. Unlike most OCR APIs, Mistral OCR is a multimodal API, meaning that it can detect when there are illustrations and photos intertwined with blocks of text. The OCR API creates bounding boxes around these graphical elements and includes them in the output. Similarly, Mistral OCR doesn't just output a big wall of text. The output is formatted in Markdown, a formatting syntax that developers use to add links, headers and other formatting elements to a plain text file. Large language models rely heavily on Markdown for their training data sets. Similarly, when you use an AI assistant, such as Mistral's Le Chat or OpenAI's ChatGPT, they often generate Markdown to create bullet lists, add links or put some elements in bold. Assistant apps seamlessly format the Markdown output into a rich text output. That's why raw text -- and Markdown -- have become more important in recent years. "Over the years, organizations have accumulated numerous documents, often in PDF or slide formats, which are inaccessible to LLMs, particularly RAG systems. With Mistral OCR, our customers can now convert rich and complex documents into readable content in all languages," Mistral co-founder and chief science officer Guillaume Lample said. "This is a crucial step toward the widespread adoption of AI assistants in companies that need to simplify access to their vast internal documentation," he added. Mistral OCR is available on Mistral's own API platform or through its cloud partners (AWS, Azure, Google Cloud Vertex, etc.). And for companies working with classified or sensitive data, Mistral also offers on-premises deployment. According to the Paris-based AI company, Mistral OCR performs better than APIs from Google, Microsoft and OpenAI. The company has tested its OCR model with complex documents that include mathematical expressions (LaTeX formatting), advanced layouts or tables. It is also supposed to perform better with non-English documents. Given that Mistral OCR does one thing and one thing only, the company believes it is also faster than what's out there. That's not a surprise if you compare it with a multimodal large language model like GPT-4o, which also has OCR capabilities (among many other features). Mistral is also using Mistral OCR for its own AI assistant Le Chat. When a user uploads a PDF file, the company uses Mistral OCR in the background to understand what's in the document before processing the text. Companies and developers will most likely use Mistral OCR with a RAG system to use multimodal documents as input in an LLM. And there are many potential use cases. For instance, I could see law firms using it to help them swift through huge volumes of documents.

Mistral releases new optical character recognition (OCR) API claiming top performance globally

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Well-funded French AI startup Mistral is content to go its own way. In a sea of competing reasoning models, the company today introduced Mistral OCR, a new Optical Character Recognition (OCR) API designed to provide advanced document understanding capabilities. The API extracts content -- including handwritten notes, typed text, images, tables, and equations -- from unstructured PDFs and images with high accuracy, presenting in a structured format. Structured data is information that is organized in a predefined manner, typically using rows and columns, making it easy to search and analyze. Common examples include names, addresses, and financial transactions stored in databases or spreadsheets. In contrast, unstructured data lacks a specific format or structure, making it more challenging to process and analyze. This category encompasses a wide range of data types, such as emails, social media posts, videos, images, and audio files. Since unstructured data doesn't fit neatly into traditional databases, specialized tools and techniques, like natural language processing and machine learning, are often employed to extract meaningful insights from it. Understanding the distinction between these data types is crucial for businesses aiming to effectively manage and leverage their information assets. With multilingual support, fast processing speeds, and integration with large language models for document understanding, Mistral OCR is positioned to assist organizations in making their documentation AI-ready. Given that, according to Mistral's blog post announcing the new API, 90% of all business information is unstructured, the new API should be a huge boon to organizations seeking to digitize and catalog their data for use in AI applications or internal/external knowledge bases. A new gold standard for OCR Mistral OCR aims to improve how organizations process and analyze complex documents. Unlike traditional OCR solutions that primarily focus on text extraction, Mistral OCR is designed to interpret various document typographical elements and characters, including tables, mathematical expressions, and interleaved images, while maintaining structured outputs. According to Guillaume Lample, Chief Science Officer at Mistral AI, this technology represents a significant step toward wider AI adoption in enterprises, particularly for companies seeking to simplify access to their internal documentation. The API is already integrated into Le Chat, where millions of users rely on it for document processing. Now, with the release of mistral-ocr-latest, developers and businesses can access the model via la Plateforme, Mistral AI's developer suite. The API is also expected to become available through cloud and inference partners and will offer on-premises deployment for organizations with high-security requirements. Advancing an early (70-year-old) computing technology OCR technology has played a significant role in automating data extraction and document digitization for decades. The first commercial OCR machine was developed in the 1950s by David Shepard and his colleagues Harvey and William Lawless Jr., who founded Intelligent Machines Research Co. (IMR) to bring the technology to market. The system gained traction when Reader's Digest became its first major customer, followed by banks, telecom companies like AT&T, and major oil firms. In 1959, IBM licensed IMR's patents and introduced its own Optical Character Recognition machine, formalizing the term OCR as the industry standard. Since then, OCR technology has continued to evolve, incorporating artificial intelligence and machine learning to improve accuracy, expand language support, and handle increasingly complex document formats, and can be found in such leading enterprise software as PDF reader Adobe Acrobat. Mistral OCR represents the next step in this evolution, leveraging AI to enhance document comprehension beyond simple text recognition. Benchmarks show the power of Mistral OCR Mistral AI highlights Mistral OCR's competitive edge over existing OCR solutions, citing benchmark tests where it outperformed major alternatives, including Google Document AI, Azure OCR, and OpenAI's GPT-4o. The model achieved the highest accuracy scores in math recognition, scanned documents, and multilingual text processing. Mistral OCR is also designed to operate faster than competing models, capable of processing up to 2,000 pages per minute on a single node. This speed advantage makes it suitable for high-volume document processing in industries such as research, customer service, and historical preservation. Sophia Yang, Ph.D., Head of Developer Relations at Mistral AI, has been actively showcasing Mistral OCR's capabilities on her X account. She highlighted its top-tier performance benchmarks, multilingual support, and the ability to accurately extract mathematical equations from PDFs. In a recent post, she shared an example of Mistral OCR successfully recognizing and formatting complex mathematical expressions, reinforcing its effectiveness for scientific and academic applications. Key features and use cases Mistral OCR introduces several features that make it a versatile solution for businesses and institutions handling large document repositories: * Multilingual and multimodal processing: The model supports a wide range of languages, scripts, and document layouts, making it useful for global organizations. Sophia Yang emphasized this capability, calling it a game-changer for multilingual document processing. * Structured output and document hierarchy preservation: Unlike basic OCR models, Mistral OCR retains formatting elements such as headers, paragraphs, lists, and tables, ensuring extracted text is more useful for downstream applications. * Document-as-prompt and structured outputs: Users can extract specific content and format it in structured outputs, such as JSON or Markdown, enabling integration with other AI-driven workflows. * Self-hosting option: Organizations with stringent data security and compliance requirements can deploy Mistral OCR within their own infrastructure. The Mistral AI developer documentation online also highlights document understanding capabilities that go beyond OCR. After extracting text and structure, Mistral OCR integrates with large language models (LLMs), allowing users to interact with document content using natural language queries. This feature enables: * Question answering about specific document content * Automated information extraction and summarization * Comparative analysis across multiple documents * Context-aware responses that consider the full document What enterprise decision makers should know about Mistral OCR For CEOs, CIOs, CTOs, IT managers, and team leaders, Mistral OCR presents significant opportunities for efficiency, security, and scalability in document-driven workflows. 1. Increased Efficiency and Cost Savings By automating document processing and reducing manual data entry, Mistral OCR cuts down on administrative overhead and streamlines operations. Organizations can process large volumes of documents faster and with higher accuracy, reducing the need for human intervention. This is particularly valuable for industries like finance, healthcare, legal, and compliance, where extensive paperwork is a bottleneck. 2. Enhanced Decision-Making with AI-Driven Insights Mistral OCR's document understanding capabilities allow decision-makers to extract actionable insights from reports, contracts, financial documents, and research papers. IT leaders can integrate the API into business intelligence platforms, enabling AI-assisted document analysis that supports faster, data-driven decision-making. 3. Improved Data Security and Compliance With an on-premises deployment option, Mistral OCR meets the security and compliance needs of enterprises handling sensitive or classified data. CIOs and compliance officers can ensure that proprietary information remains within internal infrastructure while leveraging AI for document processing. 4. Seamless Integration with Enterprise Workflows CTOs and IT managers can integrate Mistral OCR with existing enterprise systems, including content management platforms, CRM software, legal tech solutions, and AI-driven assistants. The API's support for structured outputs (JSON, Markdown) makes it easy to automate document-based workflows, improving overall productivity. 5. Competitive Advantage Through AI-Driven Innovation For organizations looking to stay ahead in digital transformation, Mistral OCR offers a scalable AI-powered solution for making vast document repositories more accessible. By leveraging AI for information extraction, enterprises can enhance customer experiences, optimize internal knowledge bases, and reduce operational inefficiencies. Pricing and availability Mistral OCR is priced at 1,000 pages per $1, with batch inference offering 2,000 pages per $1 USD. The API is available now on la Plateforme, with plans for expansion to cloud and inference partners in the near future. The model is also free to try on Mistral's website Le Chat, a conversational chatbot powered by its large language models similar to and rivalrous of OpenAI's ChatGPT, allowing users to test its capabilities before integrating it into their workflows. Mistral AI expects continued improvements to the model based on user feedback in the coming weeks. When I briefly tested it on a short handwritten (and messy) note on a scrap of paper, it provided an accurate, structured text line back within less than one second. What's next? With Mistral OCR, Mistral AI continues to expand its suite of AI-driven tools, targeting enterprises that require high-performance document processing solutions. By integrating OCR with AI-powered document understanding, Mistral AI enables businesses to extract, analyze, and interact with their documents in more intelligent ways. Enterprise leaders, developers, and IT teams can explore Mistral OCR through la Plateforme or request on-premises deployment for specialized use cases.

Mistral AI Launches OCR API, Beats Azure OCR, Google Gemini, and OpenAI GPT-4o

The API is accessible on Mistral's developer suite, La Plateforme, and will soon be available through cloud, inference partners, and on-premises deployment. French AI company Mistral AI has unveiled Mistral OCR, a powerful new API for Optical Character Recognition that boosts document analysis. The tool processes images and PDFs, accurately pulling out structured text, media, tables, and equations. "Approximately 90% of the world's organisational data is stored as documents, and to harness this potential, we are introducing Mistral OCR," said the Mistral AI. The API integrates with Retrieval-Augmented Generation (RAG) systems, making it suitable for processing multimodal documents such as slides and complex PDFs. Mistral OCR is now the default model for document understanding on Le Chat and is available via the API 'mistral-ocr-latest' at 1000 pages per dollar, with batch inference doubling efficiency. The API is accessible on Mistral's developer suite, La Plateforme, and will soon be available through cloud, inference partners, and on-premises deployment. Mistral OCR supports multilingual and multimodal content, outperforming leading OCR models in benchmarks. It has been tested against Google Document AI, Azure OCR, Gemini models, and GPT-4o, scoring 94.89 overall, with high performance in mathematical expressions, scanned documents, and tables. Mistral OCR can handle a diverse range of scripts, fonts, and languages. "This versatility is crucial for both global organisations that handle documents from diverse linguistic backgrounds, as well as hyperlocal businesses serving niche markets," the company said. The API processes up to 2000 pages per minute on a single node. It also supports "doc-as-prompt" functionality, allowing structured output extraction in formats like JSON. This feature enables integration with downstream workflows. Beta customers are using Mistral OCR for scientific research, historical preservation, customer service, and technical literature indexing. Research institutions have leveraged it to convert academic papers into AI-ready formats, while heritage organizations are digitizing historical records. Customer service teams are transforming manuals into searchable knowledge bases. For enterprises handling sensitive data, Mistral AI offers a self-hosted deployment option. "Organisations with strict data privacy requirements can maintain full control over their infrastructure," Mistral AI said. Mistral AI plans to improve the model further and expand on-premises deployment in the coming weeks.

Mistral AI OCR : The Secret Weapon for Faster, Smarter Document Digitization

Mistral OCR is an innovative optical character recognition (OCR) model designed to address the evolving challenges of modern document processing. It provides a robust and efficient solution for extracting structured data from a variety of document types. Whether working with scanned images, PDFs, or documents with intricate layouts, Mistral AI OCR simplifies the process, making sure faster and more accurate results. Its ability to handle diverse formats and languages makes it an essential tool for organizations managing complex workflows. This isn't just another AI OCR model; it's a powerhouse built to handle everything from extracting text and images to processing tables and multilingual content -- all while delivering structured outputs tailored to your workflow. Whether you're working with PDFs, scanned images, or complex layouts, Mistral OCR promises to simplify the process and help you reclaim your time. Key Features of Mistral AI OCR Mistral OCR distinguishes itself with a range of advanced features tailored to meet the demands of organizations dealing with diverse and large-scale document processing tasks. These features include: These features make Mistral OCR a versatile and reliable solution for organizations seeking to streamline their document processing operations. Performance and Efficiency Mistral OCR is engineered for exceptional performance, particularly in handling multilingual and multimodal documents. It outpaces competitors such as Gemini 2.0 and Aure OCR in both speed and accuracy. Capable of processing up to 2,000 pages per minute on a single node in on-premise setups, it is ideal for enterprises managing large-scale digitization projects. This high processing speed ensures rapid turnaround times without compromising the accuracy of the extracted data. The model's efficiency is further enhanced by its ability to maintain consistency across diverse document types, making it a reliable choice for organizations with high-volume processing needs. Multimodal & Multilingual AI OCR Explore further guides and articles from our vast library that you may find relevant to your interests in AI writing. Applications and Use Cases The versatility of Mistral OCR allows it to be applied across a wide range of industries and workflows. Some of the most common use cases include: These use cases demonstrate the model's adaptability and its ability to address the unique challenges faced by various industries, including finance, healthcare, education, and research. Pricing and Deployment Options Mistral OCR offers flexible pricing and deployment options to cater to the diverse needs of organizations. These options include: While the model is proprietary and not open source, its accessibility through API or on-premise deployment ensures it remains a viable and scalable solution for businesses with varying requirements. Limitations to Consider Despite its many strengths, Mistral OCR has certain limitations that users should take into account: These limitations highlight the importance of evaluating the model's capabilities against specific organizational needs before adoption. Additional Features for Enhanced Usability Mistral AI OCR includes several auxiliary features designed to further streamline document processing and enhance usability: These additional features make Mistral OCR a comprehensive tool capable of addressing a wide range of document processing challenges. Who Should Use Mistral OCR? Mistral AI OCR is particularly well-suited for organizations that require advanced OCR capabilities to manage complex workflows. It is ideal for: Its ability to extract structured data while preserving the layout and positioning of elements makes it a valuable asset for industries such as finance, healthcare, legal services, and academic research. Final Thoughts Mistral OCR offers a powerful and versatile solution for modern document processing needs. Its multimodal and multilingual capabilities, combined with high performance and structured outputs, make it a standout choice for organizations managing diverse and complex workflows. While it is not open source, its flexible deployment options and robust feature set ensure it remains a competitive and practical tool for businesses of all sizes. By addressing both efficiency and accuracy, Mistral OCR establishes itself as a reliable and indispensable resource for document digitization and data extraction.

Mistral's New OCR API Can Convert PDFs Into AI-Ready Text Format

The API can extract text, images, tables, and equations from PDFs Mistral introduced the Mistral Optical Character Recognition (OCR) application programming interface (API) on Thursday. The artificial intelligence (AI) model is capable of analysing and processing PDF documents and converting it into an AI-ready text format such as Markdown or raw text file. The tool is capable of extracting data from PDFs to make them digestible for AI models. The Paris-based AI firm claimed that the Mistral OCR API will allow developers to build AI applications for PDF files as well as allow them to create datasets to train new AI models. PDF documents pose a unique challenge for AI models. The content in this file format cannot be accessed by large language models (LLMs) using traditional Retrieval-Augmented Generation (RAG) techniques as the data cannot be processed by them. For example, if you ask an AI application to scan through PDF documents in your laptop to find a piece of information, it might struggle to do so. This means that developers building AI applications will be limited in offering PDF-analysis capability. While Google's NotebookLM, Adobe's AI assistant, and several other tools use specialised OCR tools to overcome this challenge, developers in the open-source community do not have access to a high-efficiency tool. Mistral OCR API solves this challenge by allowing developers to extract PDF data into an AI-ready format. The company claims in a newsroom post that the tool can understand separate elements in documents, including media, text, tables, and equations with high accuracy. Once analysed, it can extract and present the information in the Markdown or a raw text file format. AI models can then use this extracted text as input and RAG systems can easily access them and answer queries about them. "Mistral OCR excels in understanding complex document elements, including interleaved imagery, mathematical expressions, tables, and advanced layouts such as LaTeX formatting. The model enables deeper understanding of rich documents such as scientific papers with charts, graphs, equations and figures," the post stated. The company claimed that the Mistral OCR can process up to 2,000 pages per minute on a single node. The API also lets developers use the document as a prompt, and chain outputs to build function calling tools and AI agents. Based on internal testing, the Mistral OCR outperformed models such as Google Document AI, Azure OCR, and GPT-4o version 2024-11-20 for "text-only" documents. It also outperformed Google and Azure in multilingual capabilities. Those interested in trying out the capability of the model can go to Mistral's Le Chat platform. The API can be accessed from la Plateforme.

Mistral OCR - The World's Best Document Understanding Model

Mistral OCR represents a significant advancement in the field of optical character recognition (OCR), offering a robust solution for extracting text from diverse document types. Designed to handle a wide range of inputs -- including PDFs, images, and handwritten documents -- it combines speed, accuracy, and flexibility to meet the demands of modern workflows. Its ability to process complex, multilingual, and multimodal content makes it an indispensable tool for organizations aiming to streamline document digitization and analysis. Imagine a tool that not only extracts text with remarkable accuracy but also transforms it into formats ready for further use -- like markdown for seamless integration into your workflows. Mistral OCR is designed to do just that, combining speed, precision, and adaptability to handle everything from PDFs and images to even handwritten documents. Whether you're dealing with complex layouts or multilingual content, this model is built to simplify your processes and save you time. In this guide, All About AI explores how Mistral OCR is setting a new standard in document processing and why it could be the solution you've been waiting for. Mistral OCR is engineered to extract text from various document formats and convert it into usable outputs, such as structured text or markdown. This capability ensures seamless integration into workflows, allowing further processing or analysis with minimal manual intervention. Whether dealing with structured documents like invoices or unstructured formats such as scanned books, Mistral OCR demonstrates remarkable precision and adaptability. Key features include: These features make Mistral OCR a versatile tool for industries that rely heavily on document processing, such as finance, healthcare, and legal. Mistral OCR stands out for its ability to process large volumes of documents efficiently while maintaining high levels of accuracy. Its performance is particularly notable when dealing with complex layouts, unconventional document structures, or multilingual content. This combination of speed and precision makes it a reliable choice for organizations aiming to optimize their document workflows. Performance highlights include: By using these capabilities, Mistral OCR enables businesses to enhance productivity and reduce errors in document-related tasks. Take a look at other insightful guides from our broad collection that might capture your interest in Mistral AI. The versatility of Mistral OCR unlocks a wide range of applications, making it a valuable asset across various industries. Its ability to digitize and analyze documents with precision allows organizations to improve efficiency and accuracy in their operations. Some of the most impactful use cases include: These applications demonstrate how Mistral OCR can transform traditional workflows, allowing organizations to focus on higher-value tasks by automating repetitive processes. Despite its impressive capabilities, Mistral OCR is not without limitations. Certain scenarios, such as processing unclear handwriting or distorted text, can pose challenges. Additionally, numerical data extraction may occasionally suffer from inaccuracies, particularly when dealing with low-quality documents or images. Key limitations include: While these challenges highlight areas for improvement, they also underscore the importance of pairing Mistral OCR with complementary tools or workflows to address specific needs. The future of Mistral OCR lies in its potential for integration with advanced AI-driven workflows. By combining its OCR capabilities with technologies like large language models (LLMs), organizations can create intelligent, automated solutions for document handling and analysis. This integration is particularly valuable in industries where efficient and accurate document processing is critical, such as finance, healthcare, and legal. Looking ahead, enhancements in areas like handwriting recognition and numerical data accuracy could further solidify Mistral OCR's position as a leader in the OCR space. As AI technologies continue to evolve, Mistral OCR is well-positioned to remain at the forefront of document understanding, offering innovative solutions to meet the growing demands of modern workflows. Mistral OCR redefines the possibilities of document processing by combining speed, accuracy, and adaptability in a single, powerful tool. Its ability to handle diverse document types and integrate seamlessly into AI-driven workflows makes it an essential resource for organizations seeking to enhance their document processing capabilities. While challenges remain in areas like handwriting recognition, its overall performance and potential for future advancements ensure its relevance in a rapidly evolving technological landscape. By adopting Mistral OCR, businesses can unlock new levels of efficiency and accuracy, paving the way for smarter, more streamlined operations.