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Quick Run PaddleOCR-VL-1.6-GGUF For Low VRAM (6GB/8GB) Full Method

Using a native PowerShell script is the absolute quickest way to install this model.

Please adhere to the deployment steps listed below.

1-click setup: the app automatically fetches the large weight files.

The installer diagnoses your environment to deploy the most compatible profile.

📎 HASH: 0c7b021739c7d85cefef5792ffdd1aed | Updated: 2026-06-26



  • CPU: AVX2/AVX-512 instruction set required for llama.cpp
  • RAM: fast 5600MHz+ required to avoid memory bottlenecks
  • Storage:100 GB free space for HuggingFace cache folder
  • GPU: 16 GB+ video memory highly recommended for exl2 / AWQ formats

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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