diff --git a/spacy/tests/vectors/test_similarity.py b/spacy/tests/vectors/test_similarity.py
index 1260728be..f9c18adca 100644
--- a/spacy/tests/vectors/test_similarity.py
+++ b/spacy/tests/vectors/test_similarity.py
@@ -14,10 +14,9 @@ def vectors():
 
 @pytest.fixture()
 def vocab(en_vocab, vectors):
-    #return add_vecs_to_vocab(en_vocab, vectors)
-    return None
+    add_vecs_to_vocab(en_vocab, vectors)
+    return en_vocab
 
-@pytest.mark.xfail
 def test_vectors_similarity_LL(vocab, vectors):
     [(word1, vec1), (word2, vec2)] = vectors
     lex1 = vocab[word1]
@@ -31,7 +30,6 @@ def test_vectors_similarity_LL(vocab, vectors):
     assert numpy.isclose(lex2.similarity(lex2), lex1.similarity(lex1))
 
 
-@pytest.mark.xfail
 def test_vectors_similarity_TT(vocab, vectors):
     [(word1, vec1), (word2, vec2)] = vectors
     doc = get_doc(vocab, words=[word1, word2])
@@ -44,21 +42,18 @@ def test_vectors_similarity_TT(vocab, vectors):
     assert numpy.isclose(doc[1].similarity(doc[0]), doc[0].similarity(doc[1]))
 
 
-@pytest.mark.xfail
 def test_vectors_similarity_TD(vocab, vectors):
     [(word1, vec1), (word2, vec2)] = vectors
     doc = get_doc(vocab, words=[word1, word2])
     assert doc.similarity(doc[0]) == doc[0].similarity(doc)
 
 
-@pytest.mark.xfail
 def test_vectors_similarity_DS(vocab, vectors):
     [(word1, vec1), (word2, vec2)] = vectors
     doc = get_doc(vocab, words=[word1, word2])
     assert doc.similarity(doc[:2]) == doc[:2].similarity(doc)
 
 
-@pytest.mark.xfail
 def test_vectors_similarity_TS(vocab, vectors):
     [(word1, vec1), (word2, vec2)] = vectors
     doc = get_doc(vocab, words=[word1, word2])
diff --git a/spacy/tests/vectors/test_vectors.py b/spacy/tests/vectors/test_vectors.py
index c42c3a4ce..0e4464d93 100644
--- a/spacy/tests/vectors/test_vectors.py
+++ b/spacy/tests/vectors/test_vectors.py
@@ -2,6 +2,8 @@
 from __future__ import unicode_literals
 
 from ...vectors import Vectors
+from ...tokenizer import Tokenizer
+from ..util import add_vecs_to_vocab, get_doc
 
 import numpy
 import pytest
@@ -11,11 +13,27 @@ import pytest
 def strings():
     return ["apple", "orange"]
 
+@pytest.fixture
+def vectors():
+    return [
+        ("apple", [1, 2, 3]),
+        ("orange", [-1, -2, -3]),
+        ('and', [-1, -1, -1]),
+        ('juice', [5, 5, 10]),
+        ('pie', [7, 6.3, 8.9])]
+
+
 @pytest.fixture
 def data():
     return numpy.asarray([[0.0, 1.0, 2.0], [3.0, -2.0, 4.0]], dtype='f')
 
 
+@pytest.fixture()
+def vocab(en_vocab, vectors):
+    add_vecs_to_vocab(en_vocab, vectors)
+    return en_vocab
+
+
 def test_init_vectors_with_data(strings, data):
     v = Vectors(strings, data)
     assert v.shape == data.shape
@@ -42,125 +60,111 @@ def test_set_vector(strings, data):
     assert list(v[strings[0]]) != list(orig[0])
 
 
-#
-#@pytest.fixture()
-#def tokenizer_v(vocab):
-#    return Tokenizer(vocab, {}, None, None, None)
-#
-#
-#@pytest.mark.xfail
-#@pytest.mark.parametrize('text', ["apple and orange"])
-#def test_vectors_token_vector(tokenizer_v, vectors, text):
-#    doc = tokenizer_v(text)
-#    assert vectors[0] == (doc[0].text, list(doc[0].vector))
-#    assert vectors[1] == (doc[2].text, list(doc[2].vector))
-#
-#
-#@pytest.mark.xfail
-#@pytest.mark.parametrize('text', ["apple", "orange"])
-#def test_vectors_lexeme_vector(vocab, text):
-#    lex = vocab[text]
-#    assert list(lex.vector)
-#    assert lex.vector_norm
-#
-#
-#@pytest.mark.xfail
-#@pytest.mark.parametrize('text', [["apple", "and", "orange"]])
-#def test_vectors_doc_vector(vocab, text):
-#    doc = get_doc(vocab, text)
-#    assert list(doc.vector)
-#    assert doc.vector_norm
-#
-#
-#@pytest.mark.xfail
-#@pytest.mark.parametrize('text', [["apple", "and", "orange"]])
-#def test_vectors_span_vector(vocab, text):
-#    span = get_doc(vocab, text)[0:2]
-#    assert list(span.vector)
-#    assert span.vector_norm
-#
-#
-#@pytest.mark.xfail
-#@pytest.mark.parametrize('text', ["apple orange"])
-#def test_vectors_token_token_similarity(tokenizer_v, text):
-#    doc = tokenizer_v(text)
-#    assert doc[0].similarity(doc[1]) == doc[1].similarity(doc[0])
-#    assert 0.0 < doc[0].similarity(doc[1]) < 1.0
-#
-#
-#@pytest.mark.xfail
-#@pytest.mark.parametrize('text1,text2', [("apple", "orange")])
-#def test_vectors_token_lexeme_similarity(tokenizer_v, vocab, text1, text2):
-#    token = tokenizer_v(text1)
-#    lex = vocab[text2]
-#    assert token.similarity(lex) == lex.similarity(token)
-#    assert 0.0 < token.similarity(lex) < 1.0
-#
-#
-#@pytest.mark.xfail
-#@pytest.mark.parametrize('text', [["apple", "orange", "juice"]])
-#def test_vectors_token_span_similarity(vocab, text):
-#    doc = get_doc(vocab, text)
-#    assert doc[0].similarity(doc[1:3]) == doc[1:3].similarity(doc[0])
-#    assert 0.0 < doc[0].similarity(doc[1:3]) < 1.0
-#
-#
-#@pytest.mark.xfail
-#@pytest.mark.parametrize('text', [["apple", "orange", "juice"]])
-#def test_vectors_token_doc_similarity(vocab, text):
-#    doc = get_doc(vocab, text)
-#    assert doc[0].similarity(doc) == doc.similarity(doc[0])
-#    assert 0.0 < doc[0].similarity(doc) < 1.0
-#
-#
-#@pytest.mark.xfail
-#@pytest.mark.parametrize('text', [["apple", "orange", "juice"]])
-#def test_vectors_lexeme_span_similarity(vocab, text):
-#    doc = get_doc(vocab, text)
-#    lex = vocab[text[0]]
-#    assert lex.similarity(doc[1:3]) == doc[1:3].similarity(lex)
-#    assert 0.0 < doc.similarity(doc[1:3]) < 1.0
-#
-#
-#@pytest.mark.xfail
-#@pytest.mark.parametrize('text1,text2', [("apple", "orange")])
-#def test_vectors_lexeme_lexeme_similarity(vocab, text1, text2):
-#    lex1 = vocab[text1]
-#    lex2 = vocab[text2]
-#    assert lex1.similarity(lex2) == lex2.similarity(lex1)
-#    assert 0.0 < lex1.similarity(lex2) < 1.0
-#
-#
-#@pytest.mark.xfail
-#@pytest.mark.parametrize('text', [["apple", "orange", "juice"]])
-#def test_vectors_lexeme_doc_similarity(vocab, text):
-#    doc = get_doc(vocab, text)
-#    lex = vocab[text[0]]
-#    assert lex.similarity(doc) == doc.similarity(lex)
-#    assert 0.0 < lex.similarity(doc) < 1.0
-#
-#
-#@pytest.mark.xfail
-#@pytest.mark.parametrize('text', [["apple", "orange", "juice"]])
-#def test_vectors_span_span_similarity(vocab, text):
-#    doc = get_doc(vocab, text)
-#    assert doc[0:2].similarity(doc[1:3]) == doc[1:3].similarity(doc[0:2])
-#    assert 0.0 < doc[0:2].similarity(doc[1:3]) < 1.0
-#
-#
-#@pytest.mark.xfail
-#@pytest.mark.parametrize('text', [["apple", "orange", "juice"]])
-#def test_vectors_span_doc_similarity(vocab, text):
-#    doc = get_doc(vocab, text)
-#    assert doc[0:2].similarity(doc) == doc.similarity(doc[0:2])
-#    assert 0.0 < doc[0:2].similarity(doc) < 1.0
-#
-#
-#@pytest.mark.xfail
-#@pytest.mark.parametrize('text1,text2', [
-#    (["apple", "and", "apple", "pie"], ["orange", "juice"])])
-#def test_vectors_doc_doc_similarity(vocab, text1, text2):
-#    doc1 = get_doc(vocab, text1)
-#    doc2 = get_doc(vocab, text2)
-#    assert doc1.similarity(doc2) == doc2.similarity(doc1)
-#    assert 0.0 < doc1.similarity(doc2) < 1.0
+
+@pytest.fixture()
+def tokenizer_v(vocab):
+    return Tokenizer(vocab, {}, None, None, None)
+
+
+@pytest.mark.parametrize('text', ["apple and orange"])
+def test_vectors_token_vector(tokenizer_v, vectors, text):
+    doc = tokenizer_v(text)
+    assert vectors[0] == (doc[0].text, list(doc[0].vector))
+    assert vectors[1] == (doc[2].text, list(doc[2].vector))
+
+
+@pytest.mark.parametrize('text', ["apple", "orange"])
+def test_vectors_lexeme_vector(vocab, text):
+    lex = vocab[text]
+    assert list(lex.vector)
+    assert lex.vector_norm
+
+
+@pytest.mark.parametrize('text', [["apple", "and", "orange"]])
+def test_vectors_doc_vector(vocab, text):
+    doc = get_doc(vocab, text)
+    assert list(doc.vector)
+    assert doc.vector_norm
+
+
+@pytest.mark.parametrize('text', [["apple", "and", "orange"]])
+def test_vectors_span_vector(vocab, text):
+    span = get_doc(vocab, text)[0:2]
+    assert list(span.vector)
+    assert span.vector_norm
+
+
+@pytest.mark.parametrize('text', ["apple orange"])
+def test_vectors_token_token_similarity(tokenizer_v, text):
+    doc = tokenizer_v(text)
+    assert doc[0].similarity(doc[1]) == doc[1].similarity(doc[0])
+    assert -1. < doc[0].similarity(doc[1]) < 1.0
+
+
+@pytest.mark.parametrize('text1,text2', [("apple", "orange")])
+def test_vectors_token_lexeme_similarity(tokenizer_v, vocab, text1, text2):
+    token = tokenizer_v(text1)
+    lex = vocab[text2]
+    assert token.similarity(lex) == lex.similarity(token)
+    assert -1. < token.similarity(lex) < 1.0
+
+
+@pytest.mark.parametrize('text', [["apple", "orange", "juice"]])
+def test_vectors_token_span_similarity(vocab, text):
+    doc = get_doc(vocab, text)
+    assert doc[0].similarity(doc[1:3]) == doc[1:3].similarity(doc[0])
+    assert -1. < doc[0].similarity(doc[1:3]) < 1.0
+
+
+@pytest.mark.parametrize('text', [["apple", "orange", "juice"]])
+def test_vectors_token_doc_similarity(vocab, text):
+    doc = get_doc(vocab, text)
+    assert doc[0].similarity(doc) == doc.similarity(doc[0])
+    assert -1. < doc[0].similarity(doc) < 1.0
+
+
+@pytest.mark.parametrize('text', [["apple", "orange", "juice"]])
+def test_vectors_lexeme_span_similarity(vocab, text):
+    doc = get_doc(vocab, text)
+    lex = vocab[text[0]]
+    assert lex.similarity(doc[1:3]) == doc[1:3].similarity(lex)
+    assert -1. < doc.similarity(doc[1:3]) < 1.0
+
+
+@pytest.mark.parametrize('text1,text2', [("apple", "orange")])
+def test_vectors_lexeme_lexeme_similarity(vocab, text1, text2):
+    lex1 = vocab[text1]
+    lex2 = vocab[text2]
+    assert lex1.similarity(lex2) == lex2.similarity(lex1)
+    assert -1. < lex1.similarity(lex2) < 1.0
+
+
+@pytest.mark.parametrize('text', [["apple", "orange", "juice"]])
+def test_vectors_lexeme_doc_similarity(vocab, text):
+    doc = get_doc(vocab, text)
+    lex = vocab[text[0]]
+    assert lex.similarity(doc) == doc.similarity(lex)
+    assert -1. < lex.similarity(doc) < 1.0
+
+
+@pytest.mark.parametrize('text', [["apple", "orange", "juice"]])
+def test_vectors_span_span_similarity(vocab, text):
+    doc = get_doc(vocab, text)
+    assert doc[0:2].similarity(doc[1:3]) == doc[1:3].similarity(doc[0:2])
+    assert -1. < doc[0:2].similarity(doc[1:3]) < 1.0
+
+
+@pytest.mark.parametrize('text', [["apple", "orange", "juice"]])
+def test_vectors_span_doc_similarity(vocab, text):
+    doc = get_doc(vocab, text)
+    assert doc[0:2].similarity(doc) == doc.similarity(doc[0:2])
+    assert -1. < doc[0:2].similarity(doc) < 1.0
+
+
+@pytest.mark.parametrize('text1,text2', [
+    (["apple", "and", "apple", "pie"], ["orange", "juice"])])
+def test_vectors_doc_doc_similarity(vocab, text1, text2):
+    doc1 = get_doc(vocab, text1)
+    doc2 = get_doc(vocab, text2)
+    assert doc1.similarity(doc2) == doc2.similarity(doc1)
+    assert -1. < doc1.similarity(doc2) < 1.0