license, base_model, tags, language

license	base_model	tags	language
mit	rednote-hilab/dots.ocr	gguf ocr llama-cpp vision image-to-text	en zh multilingual

dots.ocr GGUF

GGUF conversions of rednote-hilab/dots.ocr for use with llama.cpp.

Files

File	Size	Description
Dots.Ocr-1.8B-Q8_0.gguf	1.8 GB	Text model, 8-bit quantized
Dots.Ocr-1.8B-F16.gguf	3.4 GB	Text model, float16
mmproj-Dots.Ocr-F16.gguf	2.4 GB	Vision encoder (mmproj), float16

Update

On March 23, 2026, mmproj-Dots.Ocr-F16.gguf was regenerated from a corrected DotsOCR converter. The text GGUF files did not change. If you downloaded the mmproj earlier, refresh that file.

Current llama.cpp fork with DotsOCR support and the compatibility fix:

• anthony-maio/llama.cpp

Architecture

dots.ocr = Qwen2 text backbone (1.7B params, 28 layers) + modified Qwen2-VL vision encoder (1.2B params, 42 layers).

Key differences from Qwen2-VL:

• Text model is standard Qwen2 with 1D RoPE (not M-RoPE)
• Vision uses RMSNorm, SiLU gated MLP, Conv2D patches, no attention bias
• 2D M-RoPE internal to vision encoder only

Usage with llama.cpp

Requires a llama.cpp build with DotsOCR support. At the moment, use:

• anthony-maio/llama.cpp

Single-image example on Windows:

llama-mtmd-cli.exe `
  -m .\Dots.Ocr-1.8B-Q8_0.gguf `
  --mmproj .\mmproj-Dots.Ocr-F16.gguf `
  --image .\page.png `
  -p "Extract all text from this image and preserve structure in markdown." `
  --ctx-size 131072 `
  -n 4096 `
  --temp 0 `
  --jinja

Equivalent server launch:

llama-server.exe `
  -m .\Dots.Ocr-1.8B-Q8_0.gguf `
  --mmproj .\mmproj-Dots.Ocr-F16.gguf `
  --port 8111 `
  --host 0.0.0.0 `
  --ctx-size 131072 `
  -n 4096 `
  --temp 0 `
  --jinja