diff --git a/pandas/core/algorithms.py b/pandas/core/algorithms.py
index c31a2cbb41dd3..1bc15fdb8d92d 100644
--- a/pandas/core/algorithms.py
+++ b/pandas/core/algorithms.py
@@ -60,6 +60,7 @@
     is_integer_dtype,
     is_list_like,
     is_object_dtype,
+    is_scalar,
     is_signed_integer_dtype,
     needs_i8_conversion,
 )
@@ -1326,6 +1327,27 @@ def searchsorted(
 
     # Argument 1 to "searchsorted" of "ndarray" has incompatible type
     # "Union[NumpyValueArrayLike, ExtensionArray]"; expected "NumpyValueArrayLike"
+    # If `arr` is an object-dtype ndarray that mixes incomparable Python
+    # types (e.g. ints and strs), NumPy may still return an insertion
+    # index while direct Python comparisons raise TypeError. To make
+    # behavior consistent with pandas operations that rely on comparisons
+    # (e.g. sort_values), attempt a lightweight comparability check and
+    # propagate a TypeError if comparisons fail.
+    if isinstance(arr, np.ndarray) and arr.dtype == object:
+        # find first non-NA element to use as a sample
+        try:
+            first = next(x for x in arr if not isna(x))
+        except StopIteration:
+            first = None
+
+        if first is not None:
+            sample = value[0] if is_list_like(value) and not is_scalar(value) else value
+            try:
+                _ = first < sample
+            except TypeError:
+                # bubble up the TypeError (message comes from Python)
+                raise
+
     return arr.searchsorted(value, side=side, sorter=sorter)  # type: ignore[arg-type]
 
 
diff --git a/pandas/tests/series/methods/test_searchsorted.py b/pandas/tests/series/methods/test_searchsorted.py
index 239496052b99b..80ca19f55997b 100644
--- a/pandas/tests/series/methods/test_searchsorted.py
+++ b/pandas/tests/series/methods/test_searchsorted.py
@@ -75,3 +75,9 @@ def test_searchsorted_dataframe_fail(self):
         msg = "Value must be 1-D array-like or scalar, DataFrame is not supported"
         with pytest.raises(ValueError, match=msg):
             ser.searchsorted(vals)
+
+    def test_searchsorted_incomparable_object_raises():
+        # mixed int/str in object-dtype Series should raise, mirroring sort_values
+        ser = Series([1, 2, "1"])
+        with pytest.raises(TypeError):
+            ser.searchsorted("1")