Aliyun Qvqv1.0.0

Users can upload screenshots of math problems, and the QVQ model performs step-by-step visual reasoning to derive solutions. This is useful for students, educators, or anyone needing automated math assistance from visual inputs.

Business analysts can upload charts, graphs, or diagrams, and QVQ interprets trends, patterns, and data points through visual reasoning. This enables rapid data-driven decision making without manual inspection.

Engineers and technicians can present images of complex systems or equipment, and QVQ guides through multi-step troubleshooting or assembly procedures by analyzing visual cues. This reduces error and speeds up resolution.

Quality control teams can feed product images to QVQ to identify defects, measure dimensions, or verify assembly correctness. The model's strong reasoning over visual evidence enhances accuracy in inspections.

Content creators can use QVQ to generate explanations or step-by-step guides from images, such as solving geometry problems or interpreting scientific diagrams, enriching educational materials.

Charge per API call or per image processed, leveraging the QVQ models (qvq-plus, qvq-max). Customers pay for each visual reasoning task, suitable for varying volumes.

Offer monthly or annual subscription plans with different quotas (e.g., number of images, model tiers). Businesses such as content platforms or analytics tools can integrate the skill for recurring revenue.

License the QVQ skill to enterprise software vendors (e.g., LMS, CRM, BI tools) who embed visual reasoning into their products. Revenue comes from licensing fees or revenue sharing.