diff --git a/spacy/tests/vectors/test_similarity.py b/spacy/tests/vectors/test_similarity.py
index 04bd4ab3b..5819ca219 100644
--- a/spacy/tests/vectors/test_similarity.py
+++ b/spacy/tests/vectors/test_similarity.py
@@ -1,7 +1,7 @@
 # coding: utf-8
 from __future__ import unicode_literals
 
-from ..util import get_doc, get_cosine
+from ..util import get_doc, get_cosine, add_vecs_to_vocab
 
 import numpy
 import pytest
@@ -9,22 +9,16 @@ import pytest
 
 @pytest.fixture
 def vectors():
-    return ("apple", [1, 2, 3], "orange", [-1, -2, -3])
+    return [("apple", [1, 2, 3]), ("orange", [-1, -2, -3])]
 
 
 @pytest.fixture()
 def vocab(en_vocab, vectors):
-    word1, vec1, word2, vec2 = vectors
-    en_vocab.resize_vectors(3)
-    lex1 = en_vocab[word1]
-    lex2 = en_vocab[word2]
-    lex1.vector = vec1
-    lex2.vector = vec2
-    return en_vocab
+    return add_vecs_to_vocab(en_vocab, vectors)
 
 
 def test_vectors_similarity_LL(vocab, vectors):
-    word1, vec1, word2, vec2 = vectors
+    [(word1, vec1), (word2, vec2)] = vectors
     lex1 = vocab[word1]
     lex2 = vocab[word2]
     assert lex1.has_vector
@@ -37,7 +31,7 @@ def test_vectors_similarity_LL(vocab, vectors):
 
 
 def test_vectors_similarity_TT(vocab, vectors):
-    word1, vec1, word2, vec2 = vectors
+    [(word1, vec1), (word2, vec2)] = vectors
     doc = get_doc(vocab, words=[word1, word2])
     assert doc[0].has_vector
     assert doc[1].has_vector
@@ -49,18 +43,18 @@ def test_vectors_similarity_TT(vocab, vectors):
 
 
 def test_vectors_similarity_TD(vocab, vectors):
-    word1, vec1, word2, vec2 = vectors
+    [(word1, vec1), (word2, vec2)] = vectors
     doc = get_doc(vocab, words=[word1, word2])
     assert doc.similarity(doc[0]) == doc[0].similarity(doc)
 
 
 def test_vectors_similarity_DS(vocab, vectors):
-    word1, vec1, word2, vec2 = vectors
+    [(word1, vec1), (word2, vec2)] = vectors
     doc = get_doc(vocab, words=[word1, word2])
     assert doc.similarity(doc[:2]) == doc[:2].similarity(doc)
 
 
 def test_vectors_similarity_TS(vocab, vectors):
-    word1, vec1, word2, vec2 = vectors
+    [(word1, vec1), (word2, vec2)] = vectors
     doc = get_doc(vocab, words=[word1, word2])
     assert doc[:2].similarity(doc[0]) == doc[0].similarity(doc[:2])
diff --git a/spacy/tests/vectors/test_vectors.py b/spacy/tests/vectors/test_vectors.py
index 3c7539e6a..58a81e2fa 100644
--- a/spacy/tests/vectors/test_vectors.py
+++ b/spacy/tests/vectors/test_vectors.py
@@ -1,109 +1,126 @@
+# coding: utf-8
+from __future__ import unicode_literals
+
+from ...tokenizer import Tokenizer
+from ..util import get_doc, add_vecs_to_vocab
+
 import pytest
 
-@pytest.mark.models
-def test_token_vector(EN):
-    token = EN(u'Apples and oranges')[0]
-    token.vector
-    token.vector_norm
 
-@pytest.mark.models
-def test_lexeme_vector(EN):
-    lexeme = EN.vocab[u'apples']
-    lexeme.vector
-    lexeme.vector_norm
+@pytest.fixture
+def vectors():
+    return [("apple", [0.0, 1.0, 2.0]), ("orange", [3.0, -2.0, 4.0])]
 
 
-@pytest.mark.models
-def test_doc_vector(EN):
-    doc = EN(u'Apples and oranges')
-    doc.vector
-    doc.vector_norm
-
-@pytest.mark.models
-def test_span_vector(EN):
-    span = EN(u'Apples and oranges')[0:2]
-    span.vector
-    span.vector_norm
-
-@pytest.mark.models
-def test_token_token_similarity(EN):
-    apples, oranges = EN(u'apples oranges')
-    assert apples.similarity(oranges) == oranges.similarity(apples)
-    assert 0.0 < apples.similarity(oranges) < 1.0
-    
-
-@pytest.mark.models
-def test_token_lexeme_similarity(EN):
-    apples = EN(u'apples')
-    oranges = EN.vocab[u'oranges']
-    assert apples.similarity(oranges) == oranges.similarity(apples)
-    assert 0.0 < apples.similarity(oranges) < 1.0
- 
-
-@pytest.mark.models
-def test_token_span_similarity(EN):
-    doc = EN(u'apples orange juice')
-    apples = doc[0]
-    oranges = doc[1:3]
-    assert apples.similarity(oranges) == oranges.similarity(apples)
-    assert 0.0 < apples.similarity(oranges) < 1.0
- 
-
-@pytest.mark.models
-def test_token_doc_similarity(EN):
-    doc = EN(u'apples orange juice')
-    apples = doc[0]
-    assert apples.similarity(doc) == doc.similarity(apples)
-    assert 0.0 < apples.similarity(doc) < 1.0
- 
-
-@pytest.mark.models
-def test_lexeme_span_similarity(EN):
-    doc = EN(u'apples orange juice')
-    apples = EN.vocab[u'apples']
-    span = doc[1:3]
-    assert apples.similarity(span) == span.similarity(apples)
-    assert 0.0 < apples.similarity(span) < 1.0
+@pytest.fixture()
+def vocab(en_vocab, vectors):
+    return add_vecs_to_vocab(en_vocab, vectors)
 
 
-@pytest.mark.models
-def test_lexeme_lexeme_similarity(EN):
-    apples = EN.vocab[u'apples']
-    oranges = EN.vocab[u'oranges']
-    assert apples.similarity(oranges) == oranges.similarity(apples)
-    assert 0.0 < apples.similarity(oranges) < 1.0
- 
+@pytest.fixture()
+def tokenizer_v(vocab):
+    return Tokenizer(vocab, {}, None, None, None)
 
-@pytest.mark.models
-def test_lexeme_doc_similarity(EN):
-    doc = EN(u'apples orange juice')
-    apples = EN.vocab[u'apples']
-    assert apples.similarity(doc) == doc.similarity(apples)
-    assert 0.0 < apples.similarity(doc) < 1.0
- 
 
-@pytest.mark.models
-def test_span_span_similarity(EN):
-    doc = EN(u'apples orange juice')
-    apples = doc[0:2]
-    oj = doc[1:3]
-    assert apples.similarity(oj) == oj.similarity(apples)
-    assert 0.0 < apples.similarity(oj) < 1.0
- 
+@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.models
-def test_span_doc_similarity(EN):
-    doc = EN(u'apples orange juice')
-    apples = doc[0:2]
-    oj = doc[1:3]
-    assert apples.similarity(doc) == doc.similarity(apples)
-    assert 0.0 < apples.similarity(doc) < 1.0
- 
 
-@pytest.mark.models
-def test_doc_doc_similarity(EN):
-    apples = EN(u'apples and apple pie')
-    oranges = EN(u'orange juice')
-    assert apples.similarity(oranges) == apples.similarity(oranges)
-    assert 0.0 < apples.similarity(oranges) < 1.0
- 
+@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 0.0 < 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 0.0 < 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 0.0 < 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 0.0 < 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 0.0 < 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 0.0 < 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 0.0 < 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 0.0 < 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 0.0 < 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 0.0 < doc1.similarity(doc2) < 1.0