This work reports experiments based on the Psychology Implicit Association Test to identify and quantify biases in a Word Embeding (WE) of the Portuguese language. For this, we use a GloVe model trained on an Internet corpus collection. The results show that several common sense and gender stereotypes can be found in WE. Within the context of professions, we note a historical sexism, since the identified bias often reflects the statistics of gender performance in occupation groups in Brazil. The results show discrimination similar to those of international studies and allow discussing the impact of the use of language models in our society