Liu Zhiyuan, Chief Scientist at ModelBest, Proposes "Density Law": Open-Source Large Model Intelligence Density Doubles Approximately Every 100 Days
Liu Zhiyuan argues that the core evolution of large models is not merely an expansion of parameters, but the formation of a general technical route capable of continuously absorbing new types of data; as data and computing power become new constraints, increasing "intelligence density" is more sustainable than simply scaling up. He draws an analogy to Moore's Law, estimating that intelligence density doubles approximately every 100 days, and believes that edge AI will become a crucial carrier for AI's entry into the physical world.
Liu Zhiyuan, Co-founder and Chief Scientist of ModelBest (面壁智能), presented a testable hypothesis at the 8th Intelligent Driving Conference held in Suzhou, China: the intelligence density of global open-source large models increases by approximately one doubling every 100 days, meaning that half the parameters and half the computational cost can achieve similar intelligence capabilities as before every 100 days. He termed this observation the "Density Law."
Liu Zhiyuan believes that the core change in large models over the past eight years has not been solely the continuous expansion of parameter scale, but rather the formation of a general technical route capable of continuously absorbing different types of data. However, as models continue to expand, data and computing power are becoming new constraints. On the data side, starting around 2024, large-scale reinforcement learning has driven models from imitation learning toward exploratory learning, enabling models to actively explore and generate new training data; on the computing side, if capability improvements rely solely on expanding parameter scales, computational demands will ultimately become unsustainable. Therefore, large models need to increase "intelligence density," i.e., achieving the same level of intelligence with fewer parameters and less computing power.
Liu Zhiyuan analogizes the Density Law to Moore's Law in the semiconductor industry: in the future, models will continue to shrink on one hand, while terminal computing power for devices such as smartphones, cars, and robots will continue to improve on the other. These two trends will eventually converge, allowing large models that previously could only run on servers to gradually enter terminals. According to the Density Law, if intelligence density continues to double approximately every 100 days, within less than two years, the number of parameters and computing power required for equivalent capabilities may drop by two orders of magnitude, compressing some capabilities of originally trillion-parameter models into the hundred-billion range and enabling deployment on terminal devices.