A hyperspectral image compression framework, GS-HSI, is proposed based on 2D Gaussian splatting, which simplifies the traditional 3D splatting process and enhances compression efficiency. By improving image representation through a cross-band prior information reuse mechanism, GS-HSI facilitates the efficient transfer of key parameters and incorporates an adaptive resampling module to optimize local structures at low bitrates. Compared to existing methods, GS-HSI reduces training time by a factor of 10, achieving an average PSNR improvement of 2 dB. Experiments show that the method balances compression efficiency and image quality. It provides a new approach to hyperspectral image compression.