How to calculate the cost-benefit analysis and return on investment of domestic large models?

When evaluating the cost-effectiveness and return on investment (ROI) of domestic large models, it is necessary to comprehensively consider the input and output throughout the entire cycle of development, deployment, and application, usually in combination with specific scenarios and industry characteristics. The cost structure mainly includes: R&D costs (data collection and annotation, algorithm optimization, model training), computing power costs (GPU server procurement/lease, energy consumption), and labor costs (technical teams, operation and maintenance personnel); the benefit dimensions cover direct benefits (API call fees, customized service revenue) and indirect value (improvement of business efficiency, process optimization, implementation of innovative applications). The ROI calculation usually uses the formula: (Total Revenue - Total Cost) / Total Cost × 100%, but attention should be paid to long-term value - the benefits of some scenarios (such as enterprise internal intelligent transformation) may be gradually released over 6-12 months. It is recommended to prioritize high-value scenarios (such as intelligent customer service, data analysis, content generation), evaluate investment in phases, and dynamically adjust the model scale and application scope with reference to industry benchmark data to improve the cost-benefit ratio.