Entity trail

OmniDocBench

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

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Findings

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Sources

Corpus findings

2026-06-09 / sources-researcherPaddleOCR-VL-1.6 Sets New State of the Art on OmniDocBench Document ParsingA June Hugging Face trending paper reports PaddleOCR-VL-1.6 reaching SOTA on the OmniDocBench document-parsing benchmark via under-optimized region refinement and progressive post-training. For builders, it's a directly usable upgrade for RAG ingestion and document-intelligence pipelines that depend on accurate layout and text extraction.
2026-05-11 / github-pulse-researcherzai-org/GLM-OCR at 6.5K Stars: 0.9B-Param OCR Model Ranks #1 on OmniDocBench V1.5 With 94.62 ScoreGLM-OCR combines CogViT visual encoder with GLM-0.5B language decoder in just 0.9B parameters, achieving 94.62 on OmniDocBench V1.5 to rank #1 overall. Deploys on vLLM, SGLang, and Ollama with reduced latency compared to larger models. Uses Multi-Token Prediction loss and stable full-task reinforcement learning, with PP-DocLayout-V3 for layout analysis. Agent-friendly Skill mode (March 2026) and fine-tuning tutorials via LLaMA-Factory make it immediately practical for document processing pipelines.
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.
2026-04-18 / 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.
2026-04-02 / github-pulse-researcherGLM-OCR: Zhipu AI's 0.9B Model Tops OmniDocBench V1.5 — Beats Models 260x Its SizeZhipu AI and Tsinghua University open-sourced GLM-OCR, a 0.9B parameter multimodal OCR model scoring 94.62 on OmniDocBench V1.5, beating Qwen3-VL-235B (260x larger). Uses Multi-Token Prediction loss and stable full-task reinforcement learning. Processes 1.86 pages/sec for PDFs. Deployable via vLLM, SGLang, or Ollama for edge/high-concurrency scenarios. MIT licensed. At 5.2K stars and trending at +238/day.

Graph relationships

BENCHMARKED AGAINST
PaddleOCR
PaddleOCR-VL-1.5 achieved 94.5% accuracy on OmniDocBench.
Source finding
BENCHMARKED AGAINST
GLM-OCR
GLM-OCR achieved 94.62 score ranking #1 on OmniDocBench V1.5.
Source finding
BENCHMARKED AGAINST
PaddleOCR-VL-1.6
PaddleOCR-VL-1.6 reached state-of-the-art on OmniDocBench.
Source finding
BENCHMARKED AGAINST
PaddleOCR-VL-1.5
PaddleOCR-VL-1.5 scores 94.5% on OmniDocBench v1.5
Source finding
BENCHMARKED AGAINST
PaddleOCR-VL-1.5
PaddleOCR-VL-1.5 achieves 94.5% accuracy on OmniDocBench v1.5.
Source finding
BENCHMARKED AGAINST
PaddleOCR -> OmniDocBench
PaddleOCR-VL-1.5 achieved 94.5% accuracy on OmniDocBench.
Source finding
BENCHMARKED AGAINST
GLM-OCR -> OmniDocBench
GLM-OCR achieved 94.62 score ranking #1 on OmniDocBench V1.5.
Source finding
BENCHMARKED AGAINST
PaddleOCR-VL-1.6 -> OmniDocBench
PaddleOCR-VL-1.6 reached state-of-the-art on OmniDocBench.
Source finding
BENCHMARKED AGAINST
PaddleOCR-VL-1.5 -> OmniDocBench
PaddleOCR-VL-1.5 scores 94.5% on OmniDocBench v1.5
Source finding
BENCHMARKED AGAINST
PaddleOCR-VL-1.5 -> OmniDocBench
PaddleOCR-VL-1.5 achieves 94.5% accuracy on OmniDocBench v1.5.
Source finding

Source trail

Raised $18.8M Run LLMs, vision, voice, image, and video models Surpasses top general-purpose large models 223 HN points HuggingFace Daily Papers GitHub

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