To examine the performance of a select group of advanced color difference equations against visual color difference data, we report the development of a combined visual dataset consisting of samples in the CIE low and high chroma blue color centers (NCSU-B1 [1] and NCSU-B2 [2]), a recent set of near black samples (NCSU-BK) [3] and a new dataset around a gray center (L^* =50.56, a^* =-0.11, b^* =0.03), hereafter called NCSU-Gr, using the gray scale method. The new gray dataset consisted of 21 matte painted samples, and the visual difference between each of the samples against the standard was assessed by 35 color normal observers under highly controlled viewing and illumination conditions and using the AATCC gray scales, in three separate sittings, and a total of 2205 assessments were obtained. The performance of two groups of color difference equations consisting of: 1- those based on CIELAB color space and 2- those based on more uniform color spaces/appearance model such as DIN, CIECAM02 and OSA, against the visual dataset was examined for the NCSU-Gr, and also for the combined dataset (NCSU-COM). The results show that CIEDE2000 (2:1:1) exhibits the best performance for the NCSU-Gr dataset in comparison to other equations examined. This confirms that the G term in the CIEDE2000 significantly improves its performance in the near neutral gray region. An examination of the performance of the models against the combined dataset, however, shows that the more uniform color space/appearance models produce better results than models based on CIELAB color space, with CAM02-SCD performing significantly better than other equations except CAM02-UCS.