OCRBench_V2

OCRBench v2: Enhanced large-scale bilingual benchmark for evaluating Large Multimodal Models on visual text localization and reasoning with 10,000 human-verified question-answering pairs across 8 core OCR capabilities

Qwen2.5-Omni-7B from Alibaba Cloud / Qwen Team currently leads the OCRBench_V2 leaderboard with a score of 0.578 across 1 evaluated AI models.

Paper

Alibaba Cloud / Qwen TeamQwen2.5-Omni-7B leads with 57.8%.

Progress Over Time

Interactive timeline showing model performance evolution on OCRBench_V2

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OCRBench_V2 Leaderboard

1 models
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1
Alibaba Cloud / Qwen Team
Alibaba Cloud / Qwen Team
7B
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FAQ

Common questions about OCRBench_V2.

What is the OCRBench_V2 benchmark?

OCRBench v2: Enhanced large-scale bilingual benchmark for evaluating Large Multimodal Models on visual text localization and reasoning with 10,000 human-verified question-answering pairs across 8 core OCR capabilities

What is the OCRBench_V2 leaderboard?

The OCRBench_V2 leaderboard ranks 1 AI models based on their performance on this benchmark. Currently, Qwen2.5-Omni-7B by Alibaba Cloud / Qwen Team leads with a score of 0.578. The average score across all models is 0.578.

What is the highest OCRBench_V2 score?

The highest OCRBench_V2 score is 0.578, achieved by Qwen2.5-Omni-7B from Alibaba Cloud / Qwen Team.

How many models are evaluated on OCRBench_V2?

1 models have been evaluated on the OCRBench_V2 benchmark, with 0 verified results and 1 self-reported results.

Where can I find the OCRBench_V2 paper?

The OCRBench_V2 paper is available at https://arxiv.org/abs/2501.00321. The paper details the methodology, dataset construction, and evaluation criteria.

What categories does OCRBench_V2 cover?

OCRBench_V2 is categorized under vision and image to text. The benchmark evaluates multimodal models with multilingual support.

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