Because your data and model are balanced, the point estimates should be the same (at least to a few decimal places). However, variance estimates are quite different. Look at the size of the standard errors for the least squares means. For GLM (a narrow inference approach), they are 0.2022..., while for MIXED (a broad inference approach), they are 0.2902, an increase of almost 45%. Note also that the F test for sequence differs for the two approaches, due to the nesting of subjects within treatment*period.
That is the difference. Take a look at Littell et al.'s SAS for Mixed Models, 2nd ed. for additional material that compares GLM to MIXED.
Steve Denham
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