diff --git a/CHANGES.rst b/CHANGES.rst
index e7ca80022a..54c6f7d742 100644
--- a/CHANGES.rst
+++ b/CHANGES.rst
@@ -135,6 +135,10 @@ Release History
 - Corrected the ``rmses`` values in ``BuiltConnection.solver_info`` when using
   ``NNls`` and ``Nnl2sL2`` solvers, and the ``reg`` argument for ``Nnl2sL2``.
   (`#839 <https://github.com/nengo/nengo/pull/839>`_)
+- ``spa.Vocabulary.create_pointer`` now respects the specified number of
+  creation attempts, and returns the most dissimilar pointer if none can be
+  found below the similarity threshold.
+  (`#817 <https://github.com/nengo/nengo/pull/817>`_)
 
 2.0.1 (January 27, 2015)
 ========================
diff --git a/nengo/spa/tests/test_vocabulary.py b/nengo/spa/tests/test_vocabulary.py
index 6ef6d9a0f7..9a3a957849 100644
--- a/nengo/spa/tests/test_vocabulary.py
+++ b/nengo/spa/tests/test_vocabulary.py
@@ -4,18 +4,19 @@
 import pytest
 
 from nengo.spa import Vocabulary
+from nengo.utils.testing import warns
 
 
-def test_add():
-    v = Vocabulary(3)
+def test_add(rng):
+    v = Vocabulary(3, rng=rng)
     v.add('A', [1, 2, 3])
     v.add('B', [4, 5, 6])
     v.add('C', [7, 8, 9])
     assert np.allclose(v.vectors, [[1, 2, 3], [4, 5, 6], [7, 8, 9]])
 
 
-def test_include_pairs():
-    v = Vocabulary(10)
+def test_include_pairs(rng):
+    v = Vocabulary(10, rng=rng)
     v['A']
     v['B']
     v['C']
@@ -35,8 +36,8 @@ def test_include_pairs():
     assert v.key_pairs == ['A*B', 'A*C', 'B*C']
 
 
-def test_parse():
-    v = Vocabulary(64)
+def test_parse(rng):
+    v = Vocabulary(64, rng=rng)
     A = v.parse('A')
     B = v.parse('B')
     C = v.parse('C')
@@ -64,8 +65,8 @@ def test_invalid_dimensions():
         Vocabulary(-1)
 
 
-def test_identity():
-    v = Vocabulary(64)
+def test_identity(rng):
+    v = Vocabulary(64, rng=rng)
     assert np.allclose(v.identity.v, np.eye(64)[0])
 
 
@@ -92,8 +93,8 @@ def test_text(rng):
     assert v.text(v['D'].v) == '1.00D'
 
 
-def test_capital():
-    v = Vocabulary(16)
+def test_capital(rng):
+    v = Vocabulary(16, rng=rng)
     with pytest.raises(KeyError):
         v.parse('a')
     with pytest.raises(KeyError):
@@ -117,13 +118,25 @@ def test_transform(rng):
     assert v2.parse('B').compare(np.dot(t, B.v)) > 0.95
 
 
-def test_prob_cleanup():
-    v = Vocabulary(64)
+def test_prob_cleanup(rng):
+    v = Vocabulary(64, rng=rng)
     assert 1.0 > v.prob_cleanup(0.7, 10000) > 0.9999
     assert 0.9999 > v.prob_cleanup(0.6, 10000) > 0.999
     assert 0.99 > v.prob_cleanup(0.5, 1000) > 0.9
 
-    v = Vocabulary(128)
+    v = Vocabulary(128, rng=rng)
     assert 0.999 > v.prob_cleanup(0.4, 1000) > 0.997
     assert 0.99 > v.prob_cleanup(0.4, 10000) > 0.97
     assert 0.9 > v.prob_cleanup(0.4, 100000) > 0.8
+
+
+def test_create_pointer_warning(rng):
+    v = Vocabulary(2, rng=rng)
+
+    # five pointers shouldn't fit
+    with warns(UserWarning):
+        v.parse('A')
+        v.parse('B')
+        v.parse('C')
+        v.parse('D')
+        v.parse('E')
diff --git a/nengo/spa/vocab.py b/nengo/spa/vocab.py
index 0271269d40..5f9600cf92 100644
--- a/nengo/spa/vocab.py
+++ b/nengo/spa/vocab.py
@@ -86,18 +86,24 @@ def create_pointer(self, attempts=100, unitary=False):
         """Create a new semantic pointer.
 
         This will take into account the randomize and max_similarity
-        parameters from self.
+        parameters from self. If a pointer satisfying max_similarity
+        is not generated after the specified number of attempts, the
+        candidate pointer with lowest maximum cosine with all existing
+        pointers is returned.
         """
         if self.randomize:
-            count = 0
-            p = pointer.SemanticPointer(self.dimensions, rng=self.rng)
-            if self.vectors.shape[0] > 0:
-                while count < 100:
-                    similarity = np.dot(self.vectors, p.v)
-                    if max(similarity) < self.max_similarity:
-                        break
-                    p = pointer.SemanticPointer(self.dimensions, rng=self.rng)
-                    count += 1
+            if self.vectors.shape[0] == 0:
+                p = pointer.SemanticPointer(self.dimensions, rng=self.rng)
+            else:
+                p_sim = np.inf
+                for _ in range(attempts):
+                    pp = pointer.SemanticPointer(self.dimensions, rng=self.rng)
+                    pp_sim = max(np.dot(self.vectors, pp.v))
+                    if pp_sim < p_sim:
+                        p = pp
+                        p_sim = pp_sim
+                        if p_sim < self.max_similarity:
+                            break
                 else:
                     warnings.warn(
                         'Could not create a semantic pointer with '