This study designed a brain-computer interface (BCI) with high frequency steady-state visual evoked potentials (SSVEPs) paradigm based on dual frequency modulation. The information transfer rates (ITR) of traditional low-frequency SSVEP-BCIs are high, but are very irritating to the human eye for long-term use. High-frequency stimulation can greatly improve the comfort of the system, but the communication rate of high-frequency systems is poor for the EEG response of high-frequency stimulation is weak. This study introduces a dual-frequency modulation method to improve the recognition accuracy of high-frequency BCI. Each target in the paradigm is composed of sinusoidal brightness modulated flicker light of the same initial phase with different stimulation frequencies in a space composition of the checkerboard. Using the above method, a relatively high-frequency SSVEP-BCI paradigm with a relatively complex code is proposed. Due to the complexity of the coding, only the training-based identification algorithm is used. With a data length of 0.5s, the average recognition accuracy is 91.02±7.77%, and ITR is 267.85±39.36bits/min. The performance is higher than the existing high frequency SSVEP-based BCI paradigms.