Languages Supported

Nanonets supports character/word recognition in over 200+ languages including but not limited to:

  1. Acehnese
  2. Acholi
  3. Adangme
  4. Afrikaans
  5. Akan
  6. Albanian
  7. Algonquinian
  8. Amharic
  9. Ancient Greek
  10. Arabic
  11. Araucanian/Mapuche
  12. Armenian
  13. Assamese
  14. Asturian
  15. Athabaskan
  16. Azerbaijani
  17. Aymara
  18. Balinese
  19. Bambara
  20. Bantu
  21. Bashkir
  22. Basque
  23. Batak
  24. Belarusian
  25. Bemba
  26. Bengali
  27. Bikol
  28. Bislama
  29. Bosnian
  30. Breton
  31. Bulgarian
  32. Burmese
  33. Catalan
  34. Cebuano
  35. Chechen
  36. Cherokee
  37. Chinese
  38. Chinese (Mandarin, Hong Kong)
  39. Chinese (Mandarin, Simplified)
  40. Chinese (Mandarin, Traditional)
  41. Choctaw
  42. Chuvash
  43. Cree
  44. Creek
  45. Crimean Tatar
  46. Croatian
  47. Czech
  48. Dakota
  49. Danish
  50. Dhivehi
  51. Duala
  52. Dutch
  53. Dzonkha
  54. Efik
  55. English
  56. English (British)
  57. Esperanto
  58. Estonian
  59. Ewe
  60. Faroese
  61. Fijian
  62. Filipino
  63. Finnish
  64. Fon
  65. French
  66. French (Canadian)
  67. Fulah
  68. Ga
  69. Galician
  70. Ganda
  71. Gayo
  72. Georgian
  73. German
  74. Gilbertese
  75. Gothic
  76. Greek
  77. Guarani
  78. Gujarati
  79. Haitian Creole
  80. Hausa
  81. Hawaiian
  82. Hebrew
  83. Herero
  84. Hiligaynon
  85. Hindi
  86. Hungarian
  87. Iban
  88. Icelandic
  89. Igbo
  90. Iloko
  91. Indonesian
  92. Irish
  93. Italian
  94. Japanese
  95. Javanese
  96. Kabyle
  97. Kachin
  98. Kalaallisut
  99. Kamba
  100. Kannada
  101. Kanuri
  102. Kara-Kalpak
  103. Kazakh
  104. Khmer
  105. Khasi
  106. Kikuyu
  107. Kinyarwanda
  108. Kirghiz
  109. Komi
  110. Kongo
  111. Korean
  112. Kosraean
  113. Kuanyama
  114. Lao
  115. Latin
  116. Latvian
  117. Lingala
  118. Lithuanian
  119. Low German
  120. Lozi
  121. Luba-Katanga
  122. Luo
  123. Macedonian
  124. Madurese
  125. Malagasy
  126. Malay
  127. Malayalam
  128. Maltese
  129. Mandingo
  130. Manx
  131. Maori
  132. Marathi
  133. Marshallese
  134. Mende
  135. Middle English
  136. Middle High German
  137. Minangkabau
  138. Mohawk
  139. Mongo
  140. Mongolian
  141. Nahuatl
  142. Navajo
  143. Ndonga
  144. Nepali
  145. Niuean
  146. North Ndebele
  147. Northern Sotho
  148. Norwegian
  149. Nyanja
  150. Nyankole
  151. Nyasa Tonga
  152. Nzima
  153. Occitan
  154. Ojibwa
  155. Old English
  156. Old French
  157. Old High German
  158. Old Norse
  159. Old Provencal
  160. Oriya
  161. Ossetic
  162. Pampanga
  163. Pangasinan
  164. Papiamento
  165. Pashto
  166. Persian
  167. Polish
  168. Portuguese
  169. Portuguese (European)
  170. Punjabi
  171. Quechua
  172. Romanian
  173. Romansh
  174. Romany
  175. Rundi
  176. Russian
  177. Sakha
  178. Samoan
  179. Sango
  180. Sanskrit
  181. Scots
  182. Scottish Gaelic
  183. Serbian
  184. Shona
  185. Sinhala
  186. Slovak
  187. Slovenian
  188. Songhai
  189. Southern Sotho
  190. Spanish
  191. Spanish (Latin American)
  192. Sundanese
  193. Swahili
  194. Swati
  195. Swedish
  196. Syriac
  197. Tagalog
  198. Tahitian
  199. Tajik
  200. Tamil
  201. Tatar
  202. Telugu
  203. Temne
  204. Thai
  205. Tibetan
  206. Tigirinya
  207. Tongan
  208. Tsonga
  209. Tswana
  210. Turkish
  211. Turkmen
  212. Udmurt
  213. Ukrainian
  214. Urdu
  215. Uzbek
  216. Venda
  217. Vietnamese
  218. Votic
  219. Welsh
  220. Western Frisian
  221. Wolof
  222. Xhosa
  223. Yiddish
  224. Yoruba
  225. Zapotec
  226. Zulu

Can a single model support multiple different languages?

Yes. You can build a single model to handle documents in multiple languages. It contributes to better accuracy and is easy to deploy.

Is handwritten text supported?

Yes, we support handwritten documents — with some important notes:

  • Handwriting must be legible to the human eye. If a human reader struggles to understand the handwriting, AI models may also have difficulty extracting text reliably
  • Results may vary depending on writing style, image clarity, and document structure
  • We recommend testing a few samples to evaluate performance for your specific use case

Tip: Neat, well-scanned handwritten forms (e.g., block letters or clearly written fields) tend to produce better results