Memory error in Word2vec while loading freebase-skipgram model

I am trying to use word2vec and use an arbitrary freebase grammar model. But I am unable to load the model due to a memory error.

Here is a code snippet for it:

model = gensim.models.Word2Vec()
model = models.Word2Vec.load_word2vec_format('freebase-vectors-skipgram1000.bin.gz', binary=True)

      

        
        
        
      

    

I am getting the following error:

MemoryError                               Traceback (most recent call last)
<ipython-input-40-a1cfacf48c94> in <module>()
      1 model = gensim.models.Word2Vec()
----> 2 model = models.Word2Vec.load_word2vec_format('freebase-vectors-skipgram1000.bin.gz', binary=True)

/../../word2vec.pyc in load_word2vec_format(cls, fname, fvocab, binary, norm_only)
    583             vocab_size, layer1_size = map(int, header.split())  # throws for invalid file format
    584             result = Word2Vec(size=layer1_size)
--> 585             result.syn0 = zeros((vocab_size, layer1_size), dtype=REAL)
    586             if binary:
    587                 binary_len = dtype(REAL).itemsize * layer1_size

MemoryError: 

      

        
        
        
      

    

But the same works fine with google news using the following code:

model = gensim.models.Word2Vec()
model = models.Word2Vec.load_word2vec_format('GoogleNews-vectors-negative300.bin.gz', binary=True)

      

        
        
        
      

    

I can't figure out why. Is it that freebase requires a lot more memory than Google news? I feel like it shouldn't be. Did I miss something?