MLCD ViT bigG Model Card MLCD ViT bigG is a state of the art vision transformer model enhanced with 2D Rotary Position Embedding (RoPE2D), achieving superior performance on document understanding and visual question answering tasks. Developed by DeepGlint AI, this model demonstrates exceptional capabilities in processing complex visual language interactions. We adopted the official LLaVA NeXT and the official training dataset LLaVA NeXT Data for evaluating the foundational visual models. Vision Tower RoPE2D ChartQA DocVQA InfoVQA OCRBench MMMU : : : : : : : : CLIP (ViT L 14 336px) × 66.52 75.21 38.88 525.00 44.20 SigLIP (ViT SO400M 384px) × 69.28 76.71 41.38 554.00 46.78 DFN5B (ViT H 14 378px) × 64.36 70.87 38.59 473.00 48.00 MLCD (ViT L 14 336px) × 67.84 76.46 43.48 531.00 44.30 MLCD (ViT bigG 14 336px) √ 71.07 79.63 44.38 572.00 46.78 Installation Usage Citation
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