diff --git a/spacy/language.py b/spacy/language.py
index 643a0c0f8..c35a8c016 100644
--- a/spacy/language.py
+++ b/spacy/language.py
@@ -1696,9 +1696,12 @@ class Language:
                 else:
                     model = pipe_cfg["source"]
                     if model not in source_nlps:
-                        # We only need the components here and we need to init
-                        # model with the same vocab as the current nlp object
-                        source_nlps[model] = util.load_model(model, vocab=nlp.vocab)
+                        # We only need the components here and we intentionally
+                        # do not load the model with the same vocab because
+                        # this would cause the vectors to be copied into the
+                        # current nlp object (all the strings will be added in
+                        # create_pipe_from_source)
+                        source_nlps[model] = util.load_model(model)
                     source_name = pipe_cfg.get("component", pipe_name)
                     listeners_replaced = False
                     if "replace_listeners" in pipe_cfg:
diff --git a/spacy/tests/test_language.py b/spacy/tests/test_language.py
index 86cce5f9e..137aea04f 100644
--- a/spacy/tests/test_language.py
+++ b/spacy/tests/test_language.py
@@ -475,3 +475,26 @@ def test_language_init_invalid_vocab(value):
     with pytest.raises(ValueError) as e:
         Language(value)
     assert err_fragment in str(e.value)
+
+
+def test_language_source_and_vectors(nlp2):
+    nlp = Language(Vocab())
+    textcat = nlp.add_pipe("textcat")
+    for label in ("POSITIVE", "NEGATIVE"):
+        textcat.add_label(label)
+    nlp.initialize()
+    long_string = "thisisalongstring"
+    assert long_string not in nlp.vocab.strings
+    assert long_string not in nlp2.vocab.strings
+    nlp.vocab.strings.add(long_string)
+    assert nlp.vocab.vectors.to_bytes() != nlp2.vocab.vectors.to_bytes()
+    vectors_bytes = nlp.vocab.vectors.to_bytes()
+    # TODO: convert to pytest.warns for v3.1
+    logger = logging.getLogger("spacy")
+    with mock.patch.object(logger, "warning") as mock_warning:
+        nlp2.add_pipe("textcat", name="textcat2", source=nlp)
+        mock_warning.assert_called()
+    # strings should be added
+    assert long_string in nlp2.vocab.strings
+    # vectors should remain unmodified
+    assert nlp.vocab.vectors.to_bytes() == vectors_bytes