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"benchmarks": {
"DocVQA": {
"metric": "ANLS",
"SOTA": {
"Claude 3.5 Sonnet": 95.2,
"InternVL2-76B": 94.1,
"Molmo-7B-D": 93.2,
"GPT-4o": 92.8,
"Qwen2-VL-72B": 94.5,
"Llama 3.2 Vision (90B)": 90.1,
"Gemini 1.5 Pro": 90.9
}
},
"TextVQA": {
"metric": "Accuracy",
"SOTA": {
"Claude 3.5 Sonnet": 94.9,
"GPT-4o": 93.7,
"Molmo-7B-D": 92.2,
"Qwen2-VL-72B": 91.2,
"InternVL2-76B": 84.4,
"Gemini 1.5 Pro": 82.3,
"Llama 3.2 Vision (11B)": 73.5
}
},
"InfographicVQA": {
"metric": "ANLS",
"SOTA": {
"Claude 3.5 Sonnet": 90.7,
"Molmo-7B-D": 85.6,
"Qwen2-VL-72B": 85.5,
"InternVL2-76B": 82.0,
"GPT-4o": 80.3,
"Gemini 1.5 Pro": 75.8,
"Llama 3.2 Vision (90B)": 56.8
}
},
"VMCBench": {
"metric": "Accuracy",
"SOTA": {
"Qwen2-VL-72B": 85.0,
"GPT-4o": 80.3,
"Claude 3.5 Sonnet": 78.5,
"Gemini 1.5 Pro": 75.0,
"InternVL2-76B": 74.5,
"Llama 3.2 Vision (11B)": 60.3,
"Molmo-7B-D": 72.0
}
}
},
"sources": [
"https://arxiv.org/abs/2409.11340 (Llama 3.2)",
"https://arxiv.org/abs/2410.05248 (VMCBench)",
"https://molmo.allenai.org/blog (Molmo Release)",
"https://github.com/OpenGVLab/InternVL (InternVL2)",
"https://artificialanalysis.ai/models"
]
}
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