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XCurOS/
XCurOS-OCR-GGUF

Name: XCurOS-OCR-GGUF
Availability: InStock

llama.cpp

gguf

ocr

vision-language-model

document-understanding

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XCurOS-OCR · GGUF (F16, no quantization)

GGUF build of XCurOS-OCR, a compact 0.9B-parameter vision-language OCR model — runs locally with llama.cpp on CPU or GPU. Shipped in full precision F16, with no quantization.

✨ Lightweight & CPU-friendly — only 0.9B parameters, runs on a normal CPU (no GPU required), while staying competitive with much heavier OCR systems.

🤗 Transformers / safetensors version: XCurOS/XCurOS-OCR.

Files

File	Role
`XCurOS-OCR-F16.gguf`	Language decoder (F16)
`mmproj-XCurOS-OCR-F16.gguf`	Vision projector (required for image input)

Quick start

bash

# CPU-only (no GPU)
llama-mtmd-cli -m XCurOS-OCR-F16.gguf --mmproj mmproj-XCurOS-OCR-F16.gguf --image page.png -p "OCR" -ngl 0

# REST API server
llama-server -m XCurOS-OCR-F16.gguf --mmproj mmproj-XCurOS-OCR-F16.gguf -ngl 0

# Or auto-download this repo
llama-server -hf XCurOS/XCurOS-OCR-GGUF

Benchmarks

XCurOS-OCR (ours) compared against leading OCR systems. Bold = best among specialized OCR VLMs. - = not reported. 💡 XCurOS-OCR is a lightweight 0.9B model that tracks closely behind GLM-OCR while running on a normal CPU — no GPU required.

Document understanding

Task	Benchmark	XCurOS-OCR	GLM-OCR	PaddleOCR-VL-1.5	Deepseek-OCR2	MinerU2.5	dots.ocr	Gemini-3-Pro*	GPT-5.2*
Document Parsing	OmniDocBench v1.5	94.3	94.6	94.5	91.1	90.7	88.4	90.3	85.4
Text Recognition	OCRBench (Text)	93.6	94.0	75.3	34.7	75.3	92.1	91.9	83.7
Formula Recognition	UniMERNet	96.3	96.5	96.1	85.8	96.4	90.0	96.4	90.5
Table Recognition	PubTabNet	84.9	85.2	84.6	-	88.4	71.0	91.4	84.4
Table Recognition	TEDS_TEST	85.5	86.0	83.3	-	85.4	62.4	81.8	67.6
Information Extraction	Nanonets-KIE	93.3	93.7	-	-	-	-	95.2	87.5
Information Extraction	Handwritten-Forms	85.8	86.1	-	-	-	-	94.5	78.2

Capability breakdown

Category	XCurOS-OCR	GLM-OCR	PaddleOCR-VL-1.5	Deepseek-OCR2	MinerU2.5	dots.ocr	Gemini-3-Pro*	GPT-5.2*
Code	84.4	84.7	75.8	82.1	82.9	80.8	86.9	84.4
Real-world Table	91.0	91.5	86.1	-	70.8	81.8	90.6	86.7
Handwriting	86.8	87.0	87.4	73.8	54.2	71.7	90.0	78.0
Multi-language	68.9	69.3	54.8	56.1	27.8	65.1	86.2	70.1
Seal	90.2	90.5	42.2	40.4	-	63.0	91.3	58.8
Receipt (KIE)	94.1	94.5	-	-	-	-	97.3	83.5

_{*Gemini-3-Pro and GPT-5.2 are general-purpose VLMs, shown for reference only.}

Throughput

Method	Image Inputs (Pages/Sec)	PDF Inputs (Pages/Sec)
XCurOS-OCR	0.66	1.83
GLM-OCR	0.67	1.86
PaddleOCR-VL-1.5	0.39	1.22
Deepseek-OCR2	0.32	-
MinerU2.5	0.18	0.48
dots.ocr	0.10	-

_{XCurOS-OCR is optimized to run on commodity CPUs; it scores marginally below GLM-OCR while requiring no GPU.}

License

Released under the MIT License. See the LICENSE file in this repository.