### Summary of QvQ and User Feedback The post discusses QvQ, a new visual reasoning model developed by Qwen that focuses on understanding and generating responses based on visual prompts. User comments raise concerns about the openness of Qwen's model, particularly in terms of its source data and training, indicating that some limitations exist in its responses, especially regarding advice on corporate authority issues. They express skepticism about its utility for tasks beyond coding and logic due to noted compliance-oriented responses. Additionally, the model’s casual tone is highlighted, which some users find entertaining compared to the formal style of other AI models like GPT-4. ### Key Points Highlighted: - **Visual Reasoning:** QvQ's capability to interpret images and provide feedback or assistance. - **Open Source Concerns:** Questions regarding the transparency of Qven’s model. - **Compliance Issues:** The model's tendency to recommend compliance to authority, raising red flags for users looking for more independent advice. - **Casual Interaction Style:** Users have noted a more informal and humorous response style compared to other AI models, which may affect user experience positively or negatively depending on context.