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LatestBaiduv6
BaiduVision-Language

PaddleOCR's PP-OCRv6 Adds a Medium Detection Model

Baidu's open-source OCR toolkit ships an Apache-licensed text-line detector in safetensors format, tuned for a balance of accuracy and speed.

Jun 9, 2026
UpdateApache 2.0
PP-OCRv6 Medium Detection

Baidu has published PP-OCRv6 Medium Detection, the text-line detection component of the latest generation of its widely used PaddleOCR toolkit. The model is available on Hugging Face in safetensors format under a permissive Apache-2.0 license.

Text detection is the first stage in most OCR pipelines: before any characters can be read, a model has to locate where text actually sits on the page. This "medium" variant targets the practical middle ground between lightweight mobile-friendly detectors and heavier, higher-accuracy ones, making it a reasonable default for documents, receipts, and natural-scene imagery.

Why it matters

PaddleOCR has become one of the more popular open OCR stacks, particularly for Chinese and multilingual text, and a modular detection model lets developers swap stages without committing to the full framework.

  • Apache-2.0 licensing allows commercial use and redistribution.
  • The safetensors format improves loading safety and interoperability.
  • A sub-1B parameter footprint keeps inference costs modest.

As an early v6-generation release, the model signals continued investment in PaddleOCR's pipeline approach rather than a single end-to-end system. Teams already building on PaddleOCR can treat it as a drop-in detection upgrade, while others may find it a useful standalone building block for document-processing workflows.

Sources

  • PaddlePaddle/PP-OCRv6_medium_det_safetensors

    Hugging Face

    Visit
OlderCohere Releases North-Mini-Code, an Open MoE ModelCohere · Code · 5 months agoNewerZhipu AI Releases SCAIL-2 for Character AnimationZhipu AI · Image → Video · 5 months ago

Get the model

Hugging Face

Specs

Size100 MB
PrecisionFP32
Architecturepp_ocrv6_medium_det
LicenseAPACHE-2.0
Downloads2.6K
Likes141

Can you run it?

Runs on just about anything.

  • FP32 (as published)

    Any modern laptop · 8 GB RAM

    1.3 GB
  • 16-bit

    Any modern laptop · 8 GB RAM

    1.2 GB
  • 8-bit

    Any modern laptop · 8 GB RAM

    1.2 GB
  • 4-bit

    Any modern laptop · 8 GB RAM

    1.2 GB
Your machine
  • KV cache approximated from model size (no config metadata) at 8,192 tokens.

Based on Hugging Face weights metadata. Assumes an 8K context and ~1 GB runtime overhead; actual needs vary. How we estimate


Modalities

Vision-Language

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