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🔍 Hash-sum: 9b492c99d1127780c3c3fa257b5bb81a | 🕓 Last update: 2026-06-24
- CPU: 8-core / 16-thread recommended for orchestration
- RAM: at least 32 GB in dual-channel mode for bandwidth
- Disk: 150+ GB for high-context vector database storage
- GPU: modern architecture (Ada Lovelace / Ampere minimum)
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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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