Is mask working differently using inplace?

I've just found out about this strange behaviour of mask, could someone explain this to me?

A) [input]

df = pd.DataFrame(np.arange(10).reshape(-1, 2), columns=['A', 'B'])
df['C'] ='hi'
df.mask(df[['A', 'B']]<3, inplace=True)

[output]

	A	B	C
0	NaN	NaN	hi
1	NaN	3.0	hi
2	4.0	5.0	hi
3	6.0	7.0	hi
4	8.0	9.0	hi

B) [input]

df = pd.DataFrame(np.arange(10).reshape(-1, 2), columns=['A', 'B'])
df['C'] ='hi'
df.mask(df[['A', 'B']]<3)

[output]

	A	B	C
0	NaN	NaN	NaN
1	NaN	3.0	NaN
2	4.0	5.0	NaN
3	6.0	7.0	NaN
4	8.0	9.0	NaN

Thank you in advance

from Is mask working differently using inplace?