Language and vision intertwine in the human mind, shaping how we perceive and understand the world around us. Our ability to reason is deeply rooted i

QVQ: To See the World with Wisdom

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2024-12-24 18:30:05

Language and vision intertwine in the human mind, shaping how we perceive and understand the world around us. Our ability to reason is deeply rooted in both linguistic thought and visual memory - but what happens when we extend these capabilities to AI? Today’s large language models have demonstrated remarkable reasoning abilities, but we wondered: could they harness the power of visual understanding to reach new heights of cognitive capability?

Imagine an AI that can look at a complex physics problem, and methodically reason its way to a solution with the confidence of a master physicist. This vision inspired us to create QVQ - an open-weight model for multimodal reasoning, built upon Qwen2-VL-72B. QVQ represents a significant leap forward in AI’s capacity for visual understanding and complex problem-solving. QVQ achieves a score of 70.3 on MMMU and shows substantial improvements across math-related benchmarks compared to Qwen2-VL-72B-Instruct. Through careful step-by-step reasoning, QVQ demonstrates enhanced capabilities in visual reasoning tasks, particularly excelling in domains that demand sophisticated analytical thinking.

QvQ-72B-Preview is an experimental research model developed by the Qwen team, focusing on enhancing visual reasoning capabilities. While it has demonstrated performance that exceeds expectations, there are several limitations to be aware of:

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