The outlier rule is based on the inter-quartile range (upper minus lower quartile). 

If you have so many RAM values at 4 and 8 that those are the lower and upper quartiles, respectively, then IQR = 4, and any value above $8 + 1.5*4 = 14$ will show as a high outlier. A small-sample version follows:

    x = c(2,2,4,4,4,4,4,4,8,8,8,8,8,8,8,8,16,16,16,24,24)
    summary(x)
       Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
      2.000   4.000   8.000   8.952   8.000  24.000 
    IQR(x)
    [1] 4


    boxplot(x, horizontal=T, col="skyblue2", pch=19)

[![enter image description here][1]][1] 

If you take logs of your observations, a boxplot may be somewhat better suited as a graphical description.

    y = log2(x)
    summary(y)
       Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
      1.000   2.000   3.000   2.818   3.000   4.585 
    IQR(y)
    [1] 1
    boxplot(y, horizontal=T, col="skyblue2", pch=19)

 [![enter image description here][2]][2]


  [1]: https://i.sstatic.net/E7CNt.png
  [2]: https://i.sstatic.net/F5tph.png