<p>With the development of the Internet and artificial intelligence technology, the demand for sharing art education resources is increasing. This article aims to build a distributed art education resource sharing platform based on a multimodal Transformer model and differential privacy protection, in order to solve the privacy protection and efficiency issues in traditional resource sharing. The study analyzed the shortcomings of existing art education resource sharing platforms and introduced a multimodal model construction method. In terms of multimodal model construction, a model framework was designed, and the Transformer architecture was used to integrate and process various artistic resources, and a related model evaluation system was established. The model analysis results show that the model has significant advantages in handling complex and diverse art education content. The study explores differential privacy protection mechanisms in multimodal networks. By introducing the label distribution constraint algorithm, privacy protection is effectively achieved and the security of user data is guaranteed. In performance analysis, experimental results show that the proposed privacy protection mechanism significantly reduces the risk of data leakage while ensuring model accuracy. Based on the above research results, this article designs and implements a fully functional art education resource sharing platform. The platform framework is reasonable and has efficient resource upload, management, and download functions. In the result testing, the platform demonstrated a good user experience and system performance, which can meet various sharing needs.</p>