NaviDC-OCR GGUF
GGUF conversions of the original StarDoc-AI/NaviDC-OCR vision-language model for use with llama.cpp and other GGUF-compatible inference runtimes.
Important: This repository contains converted GGUF files of the original
StarDoc-AI/NaviDC-OCRmodel. It is not the original model repository, and the GGUF files have not been trained or fine-tuned by the maintainer of this repository.
⚠️ Requires a patched llama.cpp build — stock llama.cpp fails to load this model with a
check_tensor_dimsshape error; see PATCHES.md for the required source changes before building.
Original Model
Original model: StarDoc-AI/NaviDC-OCR
Original model organization: StarDoc-AI
Original model repository: StarDoc-AI/NaviDC-OCR
NaviDC-OCR is a lightweight (~1.2B parameter) open-source Vision-Language Model designed specifically for document parsing.
The original model is designed to handle both:
- Digital documents
- Camera-captured documents
The model supports document understanding tasks including:
- OCR / text extraction
- Document parsing
- Table recognition
- Formula recognition
- Layout understanding
- Reading order
- Distorted document analysis
- Scientific document understanding
Please refer to the original StarDoc-AI/NaviDC-OCR repository for the
official model documentation, training details, evaluation results,
architecture information, examples, and original model files.
About This Repository
This repository provides GGUF versions converted from the original
StarDoc-AI/NaviDC-OCR model.
The conversion was performed using the GGUF conversion and quantization
tools provided by the llama.cpp project.
The main purpose of this repository is to make NaviDC-OCR available in GGUF format for users who want to experiment with local inference, CPU inference, GPU inference, or llama.cpp-compatible applications.
GGUF Files
The repository may contain the following files:
| File | Description |
|---|---|
NaviDC-OCR-f16.gguf | F16 GGUF version of the main model |
NaviDC-OCR-mmproj-f16.gguf | F16 multimodal projector / vision component |
NaviDC-OCR-Q2_K.gguf | Q2_K quantized main model |
NaviDC-OCR-Q3_K_S.gguf | Q3_K_S quantized main model |
NaviDC-OCR-Q3_K_M.gguf | Q3_K_M quantized main model |
NaviDC-OCR-Q3_K_L.gguf | Q3_K_L quantized main model |
NaviDC-OCR-Q4_K_S.gguf | Q4_K_S quantized main model |
NaviDC-OCR-Q4_K_M.gguf | Q4_K_M quantized main model |
NaviDC-OCR-Q5_K_S.gguf | Q5_K_S quantized main model |
NaviDC-OCR-Q5_K_M.gguf | Q5_K_M quantized main model |
NaviDC-OCR-Q6_K.gguf | Q6_K quantized main model |
NaviDC-OCR-Q8_0.gguf | Q8_0 quantized main model |
Not all quantization variants may be available at all times.
What is the MMProj file?
For multimodal models, llama.cpp uses a separate GGUF file containing the multimodal components.
The file:
NaviDC-OCR-mmproj-f16.gguf
is the multimodal projector / vision-side GGUF component.
Depending on the llama.cpp version and model architecture, the main GGUF model and the MMProj GGUF may both be required for image-based inference.
The MMProj file is intentionally kept separate from the main quantized LLM weights.
For multimodal models, llama.cpp documentation recommends keeping multimodal components in a high-quality format such as BF16 or Q8_0 when possible because these components directly process the input image and their quality can affect the final generation quality.
Quantization
The original model was first converted to GGUF in F16 format and then quantized from the F16 GGUF model.
Citation
If you use NaviDC-OCR or the GGUF models in this repository, please cite the original NaviDC-OCR paper:
BibTeX
@article{cai2026navidcocr,
title={NaviDC-OCR: Navigating Document Parsing Across Digital and Camera-Captured Documents},
author={Cai, Peng and Zou, Zhaofan and Liu, Shifa and Wang, Yikun and Tang, Jiawei and Yang, Kaicheng and Tong, Meng and He, Zhongjiang and Sun, Hao},
journal={arXiv preprint arXiv:2608.12898},
year={2026}
}