Four open OCR models, now in the console

You can now choose four more OCR models in the console and through the API: GLM-OCR, LightOnOCR-3, dots.mocr and KDL Frontier Parser nano. They are open models that we run on our own GPUs. Each costs 2 credits a page, like the other preview models.

ModelMade bySizeGood atLicence
dots.mocrrednote hi lababout 3Bmultilingual pages, tables and formulasMIT
LightOnOCR-3LightOn0.8Btables, forms, receipts, charts as tablesApache 2.0
KDL Frontier Parser nanoKoreaDeep1.2BKorean and English documentsAGPL-3.0
GLM-OCRZhipu AI0.9Btables, formulas, Chinese, Japanese, KoreanMIT

First results on Persian

We read the first page of our Persian benchmark with each model. dots.mocr got 0.8% of characters wrong, LightOnOCR-3 2.1% and KDL nano 3.3%. GLM-OCR is not made for Arabic script and got more than half wrong. This is one clean, typed page, not a full test, so treat it as a first impression. The full benchmark run is next.

The first page after a quiet spell is slow

To keep costs down, these models switch off when nobody is using them. The first page after a quiet spell waits while the model starts: about 3 to 6 minutes, depending on the model. After that, a page takes 1 to 3 seconds.

So that nobody waits by surprise:

  • these models are only used when you choose them; Runemic never falls back to them on its own, and the free tool never uses them
  • in the playground, a model starts as soon as you pick it, so it is often ready by the time you have chosen a page
  • through the API, the request simply waits until the model has started; it does not fail

How to use them

In the console, pick a model in the playground, or tick up to three to compare them on the same page. In the API, pass the model id, for example preview-dots-mocr:

curl https://api.runemic.com/v1/ocr \
  -H "Authorization: Bearer $RUNEMIC_API_KEY" \
  -F "file=@page.png" \
  -F "model=preview-dots-mocr"

GET /v1/models lists every model with its credits per page. See the API docs for the rest.

More from the blog

Benchmark

How well does OCR read Persian? We tested six engines

On eight Persian test pages, the best engine got 3.1% of characters wrong and the worst 18.5%. Here is how we tested, what each engine got wrong, and how to rerun it.

Read
Know-how

Why OCR struggles with Persian, Arabic and Urdu

Connected letters, dots that change the letter, calligraphic styles and mixed directions. What makes Arabic-script text hard for OCR, and how to get better results from any engine.

Read

Try Runemic OCR free

Read your own pages in the browser, with no account. When you want more, sign in with GitHub or Hugging Face.

  • Free at runemic.com/try, no sign-up
  • Sign in for 2,500 free credits, no card needed
  • Compare up to three models, and get an API key with cURL, Python and JavaScript examples
# one page in, Markdown out
curl https://api.runemic.com/v1/ocr \
  -H "Authorization: Bearer $RUNEMIC_KEY" \
  -F "file=@page.png"

# → { "text": "# Invoice No. 4821 …",
    "usage": { "credits_used": 2 } }