Introducing the Qwen2.5-VL-32B-Instruct model, optimized through reinforcement learning for superior performance. This model excels in aligning responses with human preferences, mathematical reasoning accuracy, and fine-grained image understanding. Outperforming other state-of-the-art models in benchmarks, it shines in complex, multi-step reasoning tasks. Impressively, it tackles subjective user experience evaluations and visual reasoning tasks with top-tier performance. In a demo case, it accurately calculates arrival time for a truck journey. Future research aims to enhance long reasoning processes for visual models. Cite the Qwen2.5-VL-32B-Instruct model as referenced in the technical report.
https://qwenlm.github.io/blog/qwen2.5-vl-32b/