diff --git a/pandas/core/groupby/groupby.py b/pandas/core/groupby/groupby.py
index 9aba9723e0546..91cc878124cdc 100644
--- a/pandas/core/groupby/groupby.py
+++ b/pandas/core/groupby/groupby.py
@@ -1895,6 +1895,8 @@ def post_processor(vals: np.ndarray, inference: Optional[Type]) -> np.ndarray:
 
             return vals
 
+        algorithms.check_percentile(q)
+
         return self._get_cythonized_result(
             "group_quantile",
             self.grouper,
diff --git a/pandas/tests/groupby/test_function.py b/pandas/tests/groupby/test_function.py
index efc3142b25b82..fc4cda97620f0 100644
--- a/pandas/tests/groupby/test_function.py
+++ b/pandas/tests/groupby/test_function.py
@@ -1333,3 +1333,15 @@ def test_groupby_mean_no_overflow():
         }
     )
     assert df.groupby("user")["connections"].mean()["A"] == 3689348814740003840
+
+
+def test_quantile_validation():
+    # GH#27470
+    df = pd.DataFrame(dict(a=[0, 0, 0, 1, 1, 1]))
+    g = df.groupby(np.repeat([0, 1], 3))
+    result = g.quantile(0.5)
+    expected = DataFrame(dict(a=[0.0, 1.0]))
+    tm.assert_frame_equal(result, expected)
+
+    with pytest.raises(ValueError, match="all be in the interval"):
+        g.quantile(1.1)