dots.ocr

Name: dots.ocr
Author: Rednote

by Rednote

Vision OCR

dots.ocr is Rednote's document-parsing model, built to read complex layouts — tables, columns, and mixed text — and return structured output. It targets accurate OCR and document understanding across a 131K-token context.

Publisher: Rednote
Context window: 128K tokens
Sizes: 1.7B
Licence: MIT

Run dots.ocr

Install it on a Pendra worker, then call it through the OpenAI-compatible API with a pdr_sk_ key.

from pendra import Pendra

client = Pendra(api_key="pdr_sk_...")

response = client.chat.completions.create(
    model="dots-ocr:dots.ocr",
    messages=[
        {
            "role": "user",
            "content": [
                {"type": "text", "text": "Extract all the text from this image."},
                {"type": "image_url", "image_url": {"url": "https://example.com/receipt.png"}},
            ],
        }
    ],
)

print(response.choices[0].message.content)

import { Pendra } from "pendra";

const client = new Pendra({ apiKey: "pdr_sk_..." });

const response = await client.chat.completions.create({
  model: "dots-ocr:dots.ocr",
  messages: [
    {
      role: "user",
      content: [
        { type: "text", text: "Extract all the text from this image." },
        { type: "image_url", image_url: { url: "https://example.com/receipt.png" } },
      ],
    },
  ],
});

console.log(response.choices[0].message.content);

Run dots.ocr on your own UK infrastructure

Deploy a worker, install dots.ocr, and start serving it through one sovereign API endpoint.

Get started free Read the quickstart