Mistral
OCR 3

Achieving a new frontier for both accuracy and efficiency in document processing.

Handwritten note

Tuesday 8:30 pm.

Just had dinner. Did not get home until nearly 8 pm. as I am now very busy at the office. Westcott came today and is trying to raise money at last minute. I have to hand over balance of work to the liquidators & also finish off books before shipping them to N. York tomorrow. Glad to say it rained heavily the whole day yesterday, which kept things quiet politically, but of course, it was rotten getting to office back. Went to bed at 9-20 pm. I am not going out tonight. Will martial law, but things look better today as the teams are running & the P.O. is open & I can post this tomorrow. Will be out all day tomorrow as I have invited 6 Chinese & Mr Westcott to tiffin. Will go to Eddie's Cafe on Broadway as I believe it is good & has music. At 6 pm. I am invited to a Chinese dinner which M. H. is giving at his home for me. I bought some socks to-day & studs for shirt. Just thought on - I gave your empty ear-rings to Armenian shop to get Ural stones put in, but he was not able to go to town last week, so perhaps he has now been & I shall take a walk there now & get them back. Don't expect he has got any to fit.

Highlights

  • Breakthrough performance: 74% overall win rate over Mistral OCR 2 on forms, scanned documents, complex tables, and handwriting.

  • State-of-the-art accuracy, outperforming both enterprise document processing solutions as well as AI-native OCR solutions

  • Now powers Document AI Playground in Mistral AI Studio, a simple drag-and-drop interface for parsing PDFs/images into clean text or structured JSON

  • Major upgrade over Mistral OCR 2 in forms, handwritten content, low-quality scans, and tables

Overview

Mistral OCR 3 is designed to extract text and embedded images from a wide range of documents with exceptional fidelity. It supports markdown output enriched with HTML-based table reconstruction, enabling downstream systems to understand not just document content, but also structure. As a much smaller model than most competitive solutions, it is available at an industry-leading price of $2 per 1,000 pages, with a 50% Batch-API discount, reducing the cost to $1 per 1,000 pages.

Developers can integrate the model (mistral-ocr-2512) via API, and users can leverage Document AI, a UI that parses documents into text or structured JSON instantly.

Complex Tables4941 chars

TABLE 21. Doctoral degrees awarded to men, by major field group: 1966-2012

Academic year endingAll fieldsScience and engineering fieldsNon-S&E fields
TotalBiological and agricultural sciencesEarth, atmospheric, and ocean sciencesMathematics and computer sciencesPhysical sciencesPsychologySocial sciencesEngineering
196615,86310,6462,3863927222,5358941,4242,2935,217
196717,96112,0132,5654127822,9301,0301,6992,5955,948
196820,00513,3283,0284329243,0641,1311,9062,8436,677
196922,35514,7813,2784871,0133,2411,3502,1563,2567,574
197025,52716,4043,6274931,1483,6661,4462,6043,4209,123
197127,27117,3853,8975381,1423,7181,6152,9923,4839,886
197227,75417,1913,8025611,1853,4041,6703,0883,48110,563
197327,67016,8533,7645571,1133,2091,7413,1513,31810,817
197426,59416,0433,5715471,0962,9021,7973,0163,11410,551
197525,75115,8703,6235351,0382,8111,8783,0352,9509,881
197625,26215,3753,5595318902,6171,9373,0612,7809,887
197723,85814,7753,4705888372,4771,9022,9322,5699,083
197822,55314,1993,4495248282,3641,9282,7362,3708,354
197922,30114,1283,5165428332,3811,8312,5962,4298,173
198021,61213,8143,5995308462,1991,7872,4642,3897,798
198121,46314,0563,6074848222,3181,8852,5112,4297,407
198221,01613,9243,5945128242,3371,7202,4152,5227,092
198320,74813,9203,4295018382,4301,7502,3152,6576,828
198420,63613,9543,5654728412,4461,6252,2442,7616,682
198520,55214,0433,5304708592,4521,5762,1882,9686,509
198620,59214,2683,3784629592,5851,5272,2073,1506,324
198720,93414,5803,3074919992,6861,4742,1533,4706,354
198821,67715,2673,4775411,0872,7591,3922,1113,9006,410
198921,81115,6223,4815421,2092,6271,4082,1884,1676,189
199022,96016,4983,6805811,3292,8401,3682,2214,4796,462
199123,52116,9823,7436261,5142,9191,2492,2294,7026,539
199224,23517,4233,8165851,5882,9611,3272,2854,8616,812
199324,38717,5713,8005661,6022,8681,3222,3155,0986,816
199425,06118,1673,9406221,6413,1041,2732,4355,1526,894
199525,16218,1193,9895771,7272,9221,2452,3885,2717,043
199625,29318,4614,1015651,6562,9611,1632,5235,4926,832
199724,94418,0844,0466081,5942,8801,1622,4785,3166,860
199824,63017,8104,0755641,6382,8651,2052,3525,1116,820
199923,43916,7353,9195351,4952,7221,2092,3504,5056,704
200023,16616,5183,9434951,5072,5461,2032,3654,4596,648
200122,78216,1893,7664611,4072,5311,1282,3244,5726,593
200221,81215,3923,8304771,2912,3351,0652,2174,1776,420
200322,25715,7613,7774701,4192,3961,0432,2864,3706,496
200422,96516,4173,8304481,5202,4701,0812,3134,7556,548
200523,73617,4053,9134701,7822,6701,0582,2855,2276,331
200625,02318,3753,9984902,0742,8319362,3175,7296,648
200726,20319,5424,3885422,3082,9059412,3176,1416,661
200826,27219,8574,4895482,3532,9579992,3436,1686,415
200926,33219,8404,4955392,3272,9959912,4876,0066,492
201025,52719,5704,3554962,4352,9241,0332,5235,8045,957
201126,19220,3804,4645222,4943,1671,0032,5276,2035,812
201227,39021,2334,5784962,6833,2141,0472,6886,5276,157

S&E = science and engineering. NOTE: See appendix B for specific fields that are included in each category. SOURCE: National Science Foundation, National Center for Science and Engineering Statistics, Survey of Earned Doctorates.

Benchmarks

To raise the bar, we introduced more challenging internal benchmarks based on real business use-case examples from customers. We then evaluated several models across the domains highlighted below, comparing their outputs to ground truth using fuzzy-match metric for accuracy.

Ocr Multilangual

Ocr 3

Upgrades over previous generations of OCR models

Whereas most OCR solutions today specialize in specific document types, Mistral OCR 3 is designed to excel at processing the vast majority of document types in organizations and everyday settings.

  • Handwriting: Mistral OCR accurately interprets cursive, mixed-content annotations, and handwritten text layered over printed forms.

  • Forms: Improved detection of boxes, labels, handwritten entries, and dense layouts. Works well on invoices, receipts, compliance forms, government documents, and such.

  • Scanned & complex documents: Significantly more robust to compression artifacts, skew, distortion, low DPI, and background noise.

  • Complex tables: Reconstructs table structures with headers, merged cells, multi-row blocks, and column hierarchies. Outputs HTML table tags with colspan/rowspan to fully preserve layout.

Mistral OCR 3 is a significant upgrade across all languages and document form factors compared to Mistral OCR 2. 

Win Rates   Mistral Ocr 3 Vs Ocr 2

Recommend use cases and applications

Mistral OCR 3 is ideal for both high-volume enterprise pipelines and interactive document workflows. Developers can use it for:

  • Extracting text and images into markdown for downstream agents and knowledge systems

  • Automated parsing of forms, invoices, and operational documents

  • End-to-end document understanding pipelines

  • Digitization of handwritten or historical documents

  • Any other document → knowledge transformation applications. 

Our early customers are using Mistral OCR 3 to process invoices into structured fields, digitize company archives, extract clean text from technical and scientific reports, and improve enterprise search. 

“OCR remains foundational for enabling generative AI and agentic AI,” said Tim Law, IDC Director of Research for AI and Automation. “Those organizations that can efficiently and cost-effectively extract text and embedded images with high fidelity will unlock value and will gain a competitive advantage from their data by providing richer context.”

Available today 

Access the model either through the API or via the new Document AI Playground interface, both in Mistral AI Studio. Mistral OCR 3 is fully backward compatible with Mistral OCR 2. For more details, head over to mistral.ai/docs