---

license: apache-2.0

library_name: gguf

pipeline_tag: image-text-to-text

base_model: ATH-MaaS/OvisOCR2

tags:

• ocr
• document-parsing
• multimodal
• markdown
• tables
• formulas
• gguf
• llama-cpp

---

OvisOCR2 - GGUF Quantizations

<p align="center">

<img src="https://cdn-uploads.huggingface.co/production/uploads/658a8a837959448ef5500ce5/vRCIu5QD8VuIJolkC_ZHQ.png" alt="Ovis" width="30%" />

</p>

This repository contains GGUF format quantizations of OvisOCR2, a compact 0.8B end-to-end model for page-level document parsing. The original model was developed by ATH-MaaS by post-training Qwen3.5-0.8B to parse full document pages directly into clean Markdown (including LaTeX formulas, HTML tables, and layout components).

OvisOCR2 establishes a new state-of-the-art for compact document understanding, scoring 96.58 on OmniDocBench v1.6 and outperforming traditional, multi-stage layout analysis pipelines.

---

Available Files

Main Text Models

| File Name | Precision / Quantization | File Size | Description |

| :--- | :--- | :--- | :--- |

| OvisOCR2-F16.gguf | 16-bit Float | 1.52 GB | Baseline unquantized model |

| OvisOCR2-BF16.gguf | 16-bit Brain Float | 1.52 GB | Native weight precision |

| OvisOCR2-Q8_0.gguf | 8-bit | 812 MB | Near-identical precision to F16 |

| OvisOCR2-Q6_K.gguf | 6-bit | 630 MB | Excellent balance of size and accuracy |

| OvisOCR2-Q5_K_M.gguf | 5-bit (Medium) | 578 MB | Recommended for low-resource deployment |

| OvisOCR2-Q5_K_S.gguf | 5-bit (Small) | 564 MB | Highly optimized 5-bit layout |

| OvisOCR2-Q4_K_M.gguf | 4-bit (Medium) | 529 MB | Standard 4-bit quantization |

| OvisOCR2-Q4_K_S.gguf | 4-bit (Small) | 505 MB | Lightweight 4-bit footprint |

| OvisOCR2-Q3_K_M.gguf | 3-bit (Medium) | 466 MB | Maximum compression ratio |

Multimodal Projectors (mmproj)

Note: Because OvisOCR2 is a vision-language model, you must download one of these image processing units alongside your choice of the text models listed above.

• mmproj-F32.gguf (402 MB) - Unquantized full precision projector.
• mmproj-F16.gguf (205 MB) - Recommended standard performance/size option.
• mmproj-BF16.gguf (207 MB) - Target alternative precision layout.

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Inference Guide (llama.cpp)

To run multimodal OCR tasks using these GGUF files, you need to use the llama-minicpmv-cli or llama-llava-cli tool (depending on your build version of llama.cpp) to handle simultaneous image and text tokens.

Basic Command Line Example

# Run parsing via llama.cpp cli tools
./llama-minicpmv-cli \
  -m OvisOCR2-Q5_K_M.gguf \
  --mmproj mmproj-F16.gguf \
  --image /path/to/your/document_page.jpg \
  -p "<|im_start|>user\nExtract all readable content from the image in natural human reading order and output the result as a single Markdown document. Format formulas as LaTeX. Format tables as HTML: <table>...</table>. Preserve the original text without translation.<|im_end|>\n<|im_start|>assistant\n" \
  -n 4096 \
  --temp 0.0