This paper introduces an innovative strategy to improve the computing power of intelligent computers—building a multi-dimensional computing model with the help of intelligent computers. The core of this strategy is to make full use of the powerful parallel processing capabilities and flexible architecture of intelligent computers, and to achieve optimal configuration and efficient utilization of computing resources by building a multi-dimensional computing model that includes multiple computing modes. This study first constructs a multivariate computing model based on the hardware characteristics and computing requirements of intelligent computers. Then, the task scheduling system of the intelligent computer is used to finely decompose the computing tasks to be processed, and reasonably allocate the tasks to different computing modules according to the characteristics of each computing mode and the performance of the computing unit. After the task allocation is completed, the parallel processing capability of intelligent computers is used to start multiple computing modules at the same time to perform calculations. By optimizing data transmission and computing processes, waiting time and resource conflicts can be reduced. In addition, a real-time monitoring mechanism is implemented to dynamically track the performance indicators and resource usage of each computing module. Based on the monitoring results, task allocation and computing resources are dynamically adjusted to ensure that the model always maintains the optimal operating state. The multi-computation model significantly outperforms the traditional model in terms of execution time, ranging from 322 to 566 ms; the resource utilization rate averages 92.2%; and the throughput is also advantageous in different tasks. Based on the above results, this paper provides new ideas and practical guidance for the future development of intelligent computing.