PaddleOCR-VL-1.6-GGUF Windows 11

If you want the fastest local installation for this model, use standard pip packages.

Follow the sequence of steps detailed below.

Everything happens automatically, including the heavy cloud asset download.

The installer will automatically analyze your hardware and select the optimal configuration.

📘 Build Hash: 083f8608aae5c00f67500e11f8c06a39 • 🗓 2026-07-01

CPU: AVX2/AVX-512 instruction set required for llama.cpp
RAM: required: 16 GB absolute minimum for small models
Storage:100 GB free space for HuggingFace cache folder
Graphics: 12 GB VRAM minimum required for basic quantization

The PaddleOCR-VL-1.6-GGUF is a state‑of‑the‑art vision‑language model designed for high‑accuracy optical character recognition in multilingual documents. It leverages a transformer‑based encoder‑decoder architecture that jointly processes text and layout information, enabling robust recognition of curved and distorted scripts. The model supports over 100 languages and can handle a wide range of document types, from printed books to handwritten notes. Its quantized GGUF format ensures efficient inference on consumer‑grade hardware while maintaining competitive performance metrics. A built‑in language detection module automatically identifies the script, reducing preprocessing overhead. Users can integrate the model into existing pipelines via simple API calls, benefiting from its low memory footprint and fast loading times.

Model Name	PaddleOCR-VL-1.6-GGUF
Architecture	Transformer‑based encoder‑decoder
Supported Languages	100+
Input Resolution	1024×1024 pixels
Parameter Count	1.6 B
Quantization	GGUF (Q4_K_M)
Hardware Requirements	CPU/GPU with ≥4 GB VRAM
License	Apache 2.0

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