With the rapid development of information technology, computer communication plays an increasingly important role in data transmission and real-time interaction. However, existing communication systems often face latency and instability issues under high load conditions, and there is an urgent need to improve their real-time performance. This study aims to optimize the real-time performance of computer communications using SVM (Support vector machine). First, the existing communication protocols and system architectures are analyzed to identify the key factors causing delays. Then, a dynamic routing algorithm based on SVM and an adaptive flow control strategy are used to optimize the transmission path and flow distribution of data packets through real-time data monitoring and analysis. Then, experiments are conducted to verify the effectiveness of the algorithm in different network environments. After using the SVM algorithm, the data transmission delay reaches a minimum of 3 ms, and the stability of the network is significantly enhanced. The application of intelligent algorithms effectively improves the real-time nature of computer communication, lays the foundation for an efficient and stable network environment in the future, and also provides new ideas for the development of intelligent communication technology.