Original model: datalab-to/chandra-ocr-2
Quantization: 8-bit affine, group size 64
Framework: MLX (Apple Silicon)
Modified files: The weight file (model.safetensors) has been quantized from the original bfloat16 weights. All other files are unchanged from the original repository.

About Chandra OCR 2

Chandra 2 is a state-of-the-art OCR model from Datalab that outputs markdown, HTML, and JSON. It is highly accurate at extracting text from images and PDFs while preserving layout information.

What's New in Chandra 2

85.9% olmocr bench score (SOTA), 77.8% multilingual bench score (12% improvement over Chandra 1)
Significant improvements to math, tables, and complex layouts
Improved layout, especially on wider documents
Significantly better image captioning
90+ language support with major accuracy gains

Features

Convert documents to markdown, HTML, or JSON with detailed layout information
Excellent handwriting support
Reconstructs forms accurately, including checkboxes
Strong performance with tables, math, and complex layouts
Extracts images and diagrams with captions and structured data
Support for 90+ languages

Usage with mlx-vlm

Installation

pip install mlx-vlm

Inference

python

from mlx_vlm import load
from mlx_vlm.utils import generate_step
from PIL import Image

model, processor = load("jacobwindle/chandra-ocr-2-8bit-mlx")

image = Image.open("document.png")
prompt = "Convert this image to markdown."

output = generate_step(
    model=model,
    processor=processor,
    image=image,
    prompt=prompt,
    max_tokens=4096,
)
print(output)

Command-line

python -m mlx_vlm.generate --model jacobwindle/chandra-ocr-2-8bit-mlx --image document.png --prompt "Convert this image to markdown." --max-tokens 4096

Quantization Details

Parameter	Value
Bits	8
Group size	64
Mode	Affine
Original dtype	bfloat16
Quantized size	~4.8 GB

Converted using:

python -m mlx_vlm.convert --model datalab-to/chandra-ocr-2 --mlx-path models/chandra-ocr-2-8bit -q --q-bits 8

Attribution

This is a derivative work of datalab-to/chandra-ocr-2. The original model was created by Datalab. The weights in this repository have been modified (8-bit quantized) from the original release. All credit for the model architecture, training data, and original weights belongs to the original authors.

License

This model inherits the modified OpenRAIL-M license from the original datalab-to/chandra-ocr-2. As a derivative work, the same license terms apply, including the share-alike requirement (Section III, paragraph 8) and use-based restrictions (Attachment A).

Key restrictions from the original license:

Free for research, personal use, and startups under $2M funding/revenue
Cannot be used competitively with the Datalab API
Derivative works must retain the same license

For broader commercial licensing, see Datalab pricing.

jwindle47/chandra-ocr-2-8bit-mlx

Chandra OCR 2 — 8-bit MLX Quantization