Morgan Stanley pointed out in its latest report “The Open Weighting Model and Three Future Scenarios” that the open weighting model does not necessarily reduce the demand for AI computing power. On the contrary, lower usage costs may accelerate the spread of AI, forming a typical “Jevans paradox”: after a single inference becomes cheaper, companies will use AI for more tasks, ultimately driving up the overall demand for tokens, computing power, electricity, and infrastructure. The report emphasizes that open weight does not mean completely free; enterprises still have to bear costs such as GPUs, cloud services, operation, maintenance, and security; actual economy depends on application scenarios. Damo believes that regardless of changes in the degree of model openness, Nvidia and the like are expected to benefit.

Morgan Stanley pointed out in its latest report “The Open Weighting Model and Three Future Scenarios” that the open weighting model does not necessarily reduce the demand for AI computing power. On the contrary, lower usage costs may accelerate the spread of AI, forming a typical “Jevans paradox”: after a single inference becomes cheaper, companies will use AI for more tasks, ultimately driving up the overall demand for tokens, computing power, electricity, and infrastructure. The report emphasizes that open weight does not mean completely free; enterprises still have to bear costs such as GPUs, cloud services, operation, maintenance, and security; actual economy depends on application scenarios. Damo believes that regardless of changes in the degree of model openness, Nvidia and the like are expected to benefit.