ColModernVBERT

Usage

[!WARNING] This repository only contains the base model weights of ColModernVBERT, and should be paired with ModernVBERT/colmodernvbert.

Table of Contents

1. Overview
2. Usage
3. Evaluation
4. License
5. Citation

Overview

The ModernVBERT suite is a suite of compact 250M-parameter vision-language encoders, achieving state-of-the-art performance in this size class, matching the performance of models up to 10x larger.

For more information about ModernVBERT, please check the arXiv preprint.

Models

• ColModernVBERT is the late-interaction version that is fine-tuned for visual document retrieval tasks, our most performant model on this task.
• BiModernVBERT is the bi-encoder version that is fine-tuned for visual document retrieval tasks.
• ModernVBERT-embed is the bi-encoder version after modality alignment (using a MLM objective) and contrastive learning, without document specialization.
• ModernVBERT is the base model after modality alignment (using a MLM objective).

Evaluation

ColModernVBERT matches the performance of models nearly 10x larger on visual document benchmarks. Additionally, it provides an interesting inference speed on CPU compared to the models of similar performance.

License

We release the ModernVBERT model architectures, model weights, and training codebase under the MIT license.

Citation

If you use ModernVBERT in your work, please cite:

@misc{teiletche2025modernvbertsmallervisualdocument,
      title={ModernVBERT: Towards Smaller Visual Document Retrievers}, 
      author={Paul Teiletche and Quentin Macé and Max Conti and Antonio Loison and Gautier Viaud and Pierre Colombo and Manuel Faysse},
      year={2025},
      eprint={2510.01149},
      archivePrefix={arXiv},
      primaryClass={cs.IR},
      url={https://arxiv.org/abs/2510.01149}, 
}

[More Information Needed]