diff --git a/pandas/core/arrays/datetimes.py b/pandas/core/arrays/datetimes.py
index aa1d8f6254e2c..2b2be214428d2 100644
--- a/pandas/core/arrays/datetimes.py
+++ b/pandas/core/arrays/datetimes.py
@@ -24,6 +24,7 @@
 )
 from pandas.errors import PerformanceWarning
 
+from pandas.core.dtypes.cast import astype_dt64_to_dt64tz
 from pandas.core.dtypes.common import (
     DT64NS_DTYPE,
     INT64_DTYPE,
@@ -31,6 +32,7 @@
     is_categorical_dtype,
     is_datetime64_any_dtype,
     is_datetime64_dtype,
+    is_datetime64_ns_dtype,
     is_datetime64tz_dtype,
     is_dtype_equal,
     is_extension_array_dtype,
@@ -591,24 +593,8 @@ def astype(self, dtype, copy=True):
                 return self.copy()
             return self
 
-        elif is_datetime64tz_dtype(dtype) and self.tz is None:
-            # FIXME: GH#33401 this does not match Series behavior
-            return self.tz_localize(dtype.tz)
-
-        elif is_datetime64tz_dtype(dtype):
-            # GH#18951: datetime64_ns dtype but not equal means different tz
-            result = self.tz_convert(dtype.tz)
-            if copy:
-                result = result.copy()
-            return result
-
-        elif dtype == "M8[ns]":
-            # we must have self.tz is None, otherwise we would have gone through
-            #  the is_dtype_equal branch above.
-            result = self.tz_convert("UTC").tz_localize(None)
-            if copy:
-                result = result.copy()
-            return result
+        elif is_datetime64_ns_dtype(dtype):
+            return astype_dt64_to_dt64tz(self, dtype, copy, via_utc=False)
 
         elif is_period_dtype(dtype):
             return self.to_period(freq=dtype.freq)
diff --git a/pandas/core/dtypes/cast.py b/pandas/core/dtypes/cast.py
index ce50b81be7d63..4d7a06b691fa3 100644
--- a/pandas/core/dtypes/cast.py
+++ b/pandas/core/dtypes/cast.py
@@ -15,6 +15,7 @@
     Tuple,
     Type,
     Union,
+    cast,
 )
 import warnings
 
@@ -85,7 +86,7 @@
 
 if TYPE_CHECKING:
     from pandas import Series
-    from pandas.core.arrays import ExtensionArray
+    from pandas.core.arrays import DatetimeArray, ExtensionArray
 
 _int8_max = np.iinfo(np.int8).max
 _int16_max = np.iinfo(np.int16).max
@@ -920,6 +921,56 @@ def coerce_indexer_dtype(indexer, categories):
     return ensure_int64(indexer)
 
 
+def astype_dt64_to_dt64tz(
+    values: ArrayLike, dtype: DtypeObj, copy: bool, via_utc: bool = False
+) -> "DatetimeArray":
+    # GH#33401 we have inconsistent behaviors between
+    #  Datetimeindex[naive].astype(tzaware)
+    #  Series[dt64].astype(tzaware)
+    # This collects them in one place to prevent further fragmentation.
+
+    from pandas.core.construction import ensure_wrapped_if_datetimelike
+
+    values = ensure_wrapped_if_datetimelike(values)
+    values = cast("DatetimeArray", values)
+    aware = isinstance(dtype, DatetimeTZDtype)
+
+    if via_utc:
+        # Series.astype behavior
+        assert values.tz is None and aware  # caller is responsible for checking this
+        dtype = cast(DatetimeTZDtype, dtype)
+
+        if copy:
+            # this should be the only copy
+            values = values.copy()
+        # FIXME: GH#33401 this doesn't match DatetimeArray.astype, which
+        #  goes through the `not via_utc` path
+        return values.tz_localize("UTC").tz_convert(dtype.tz)
+
+    else:
+        # DatetimeArray/DatetimeIndex.astype behavior
+
+        if values.tz is None and aware:
+            dtype = cast(DatetimeTZDtype, dtype)
+            return values.tz_localize(dtype.tz)
+
+        elif aware:
+            # GH#18951: datetime64_tz dtype but not equal means different tz
+            dtype = cast(DatetimeTZDtype, dtype)
+            result = values.tz_convert(dtype.tz)
+            if copy:
+                result = result.copy()
+            return result
+
+        elif values.tz is not None and not aware:
+            result = values.tz_convert("UTC").tz_localize(None)
+            if copy:
+                result = result.copy()
+            return result
+
+        raise NotImplementedError("dtype_equal case should be handled elsewhere")
+
+
 def astype_td64_unit_conversion(
     values: np.ndarray, dtype: np.dtype, copy: bool
 ) -> np.ndarray:
diff --git a/pandas/core/internals/blocks.py b/pandas/core/internals/blocks.py
index 8752224356f61..27acd720b6d71 100644
--- a/pandas/core/internals/blocks.py
+++ b/pandas/core/internals/blocks.py
@@ -22,6 +22,7 @@
 from pandas.util._validators import validate_bool_kwarg
 
 from pandas.core.dtypes.cast import (
+    astype_dt64_to_dt64tz,
     astype_nansafe,
     convert_scalar_for_putitemlike,
     find_common_type,
@@ -649,14 +650,7 @@ def _astype(self, dtype: DtypeObj, copy: bool) -> ArrayLike:
         values = self.values
 
         if is_datetime64tz_dtype(dtype) and is_datetime64_dtype(values.dtype):
-            # if we are passed a datetime64[ns, tz]
-            if copy:
-                # this should be the only copy
-                values = values.copy()
-            # i.e. values.tz_localize("UTC").tz_convert(dtype.tz)
-            # FIXME: GH#33401 this doesn't match DatetimeArray.astype, which
-            #  would be self.array_values().tz_localize(dtype.tz)
-            return DatetimeArray._simple_new(values.view("i8"), dtype=dtype)
+            return astype_dt64_to_dt64tz(values, dtype, copy, via_utc=True)
 
         if is_dtype_equal(values.dtype, dtype):
             if copy: