CITIC Construction Investment Securities released a research report saying that since July of this year, the prices of open source and closed source models have converged, and the price of comprehensive tokens has declined, which is beneficial to the implementation of AI applications. As Rubin enters large-scale mass production, it is expected that the upper limit of large-scale model training and inference will be further opened. Higher cluster size, video memory bandwidth, and interconnection efficiency drive continuous scaling of model training, and accelerate the evolution of capabilities such as long context, MoE, and reinforcement learning. The intelligent upper limit of the model is still worth looking forward to.

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