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The Qwen team recently announced the open-source release of their latest multimodal reasoning model, QVQ, marking an important step forward in the capabilities of artificial intelligence in visual understanding and complex problem-solving. This model is based on Qwen2-VL-72B and aims to enhance AI reasoning capabilities by combining language and visual information. In the MMMU evaluation, QVQ achieved a high score of 70.3, demonstrating significant performance improvements over Qwen2-VL-72B-Instruct in several math-related benchmark tests.

The Tongyi Qianwen team announced the official open source of the latest member of the Qwen family, the Qwen2.5 series language models, three months after the Qwen2 release. This marks one of the largest open source releases in history, including the general language model Qwen2.5, as well as the Qwen2.5-Coder and Qwen2.5-Math models specifically designed for programming and mathematics.