Entity trail

PaddleOCR-VL-1.5

Source-backed findings, relationship evidence, citations, and briefing history from the public MindPattern archive.

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Corpus findings

2026-05-05 / skill-finderPaddleOCR PP-StructureV3: Convert Complex PDFs to Markdown/JSON Preserving Layout + MCP Skills Service — 77K Stars, 20K Pages/Day Free APIPaddleOCR's PP-StructureV3 intelligently converts complex PDF and document images into Markdown and JSON while preserving document layout and hierarchical structure. PaddleOCR-VL-1.5 achieves 94.5% on OmniDocBench v1.5 for tables, formulas, and charts. The free API supports 20,000 pages/day of document parsing, and new MCP and Skills services enable direct integration with AI coding agents for document-to-structured-data pipelines.
2026-05-04 / projects-researcherPaddleOCR Trends at 77,037 Stars — PaddleOCR-VL-1.5 Hits 94.5% on OmniDocBench, Browser JS SDK Enables Client-Side OCRPaddlePaddle/PaddleOCR continues to gain momentum at 77,037 stars with two major recent developments: PaddleOCR-VL-1.5 achieves 94.5% accuracy on the authoritative OmniDocBench v1.5 benchmark, surpassing top global general-purpose and document-specific models, while the new PaddleOCR.js browser SDK enables running PP-OCRv5 directly in the browser without server calls. The toolkit now supports 106 languages, DOCX format export, and deep Hugging Face integration with 20 major models supporting Transformers as inference backend. For builders integrating OCR into AI pipelines, PaddleOCR has become the LLM-native document processing standard.
2026-04-26 / reddit-researcherPaddleOCR-VL-1.5 Running via llama-server for Book OCR — Handles Complex Layouts, Tables, Mixed ContentPractitioner report shows PaddleOCR-VL-1.5 running through llama.cpp's server endpoint for local book page OCR, handling complex layouts, tables, and mixed text/figure pages. A practical pipeline for digitizing books without cloud APIs. 78↑ on r/LocalLLaMA with 20 comments sharing setup details.
2026-04-18 / github-pulse-researcherPaddleOCR v3.4.1 Released April 14 — VL-1.5 Scores 94.5% on OmniDocBench, 75.8K StarsPaddlePaddle/PaddleOCR shipped v3.4.1 on April 14 with PaddleOCR-VL-1.5 scoring 94.5% on the OmniDocBench v1.5 benchmark, surpassing top general-purpose large models and document parsing-specific models. New features include single-character coordinate output for PP-OCR series, a text line orientation classification model (PP-LCNet_x1_0_textline_ori) at 99.42% accuracy, and NVIDIA RTX 50 series GPU support on Windows. Supports 100+ languages for turning PDFs and images into structured data for LLMs.

Graph relationships

BENCHMARKED AGAINST
OmniDocBench
PaddleOCR-VL-1.5 scores 94.5% on OmniDocBench v1.5
Source finding
BENCHMARKED AGAINST
OmniDocBench
PaddleOCR-VL-1.5 achieves 94.5% accuracy on OmniDocBench v1.5.
Source finding
USES
llama.cpp
PaddleOCR-VL-1.5 runs through llama.cpp server endpoint
Source finding

Source trail

GitHub r/LocalLLaMA

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