diff --git a/CHANGELOG.md b/CHANGELOG.md
index 5fedcc95f..8489c46fd 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -9,7 +9,8 @@ Remember to align the itemized text with the first line of an item within a list
 ## jax 0.4.9
 
 * Changes
-  * The flags experimental_cpp_jit, and experimental_cpp_pjit have been removed.
+  * The flags experimental_cpp_jit, experimental_cpp_pjit and 
+    experimental_cpp_pmap have been removed.
     They are now always on.
 
 * Deprecations
diff --git a/jax/_src/api.py b/jax/_src/api.py
index 9bb51401c..604f65b8a 100644
--- a/jax/_src/api.py
+++ b/jax/_src/api.py
@@ -56,7 +56,7 @@ from jax._src.api_util import (
     argnums_partial, argnums_partial_except, flatten_axes, donation_vector,
     rebase_donate_argnums, _ensure_index, _ensure_index_tuple,
     shaped_abstractify, _ensure_str_tuple,
-    check_callable, debug_info, result_paths, flat_out_axes, debug_info_final, FLAGS)
+    check_callable, debug_info, result_paths, flat_out_axes, debug_info_final)
 from jax._src.lax import lax as lax_internal
 from jax._src.lib import jax_jit
 from jax._src.lib import xla_client as xc
@@ -1552,12 +1552,7 @@ def pmap(
         " removed from JAX. Please migrate to pjit and remove global_arg_shapes"
         " from pmap.")
 
-  if FLAGS.experimental_cpp_pmap:
-    func = _cpp_pmap
-  else:
-    func = _python_pmap
-
-  return func(
+  return _cpp_pmap(
       fun,
       axis_name,
       in_axes=in_axes,
@@ -1687,35 +1682,6 @@ def _prepare_pmap(fun, in_axes, out_axes, static_broadcasted_tuple,
                       global_axis_size=global_axis_size,
                       is_explicit_global_axis_size=is_explicit_global_axis_size)
 
-def _get_f_mapped(
-    *,
-    fun: Callable,
-    axis_name: Optional[AxisName],
-    in_axes=0,
-    out_axes=0,
-    static_broadcasted_tuple: Tuple[int, ...],
-    devices: Optional[Sequence[xc.Device]],  # noqa: F811
-    backend: Optional[str],
-    axis_size: Optional[int],
-    donate_tuple: Tuple[int, ...],
-  ):
-  def pmap_f(*args, **kwargs):
-    p = _prepare_pmap(
-        fun, in_axes, out_axes, static_broadcasted_tuple, donate_tuple,
-        devices, backend, axis_size, args, kwargs)
-    for arg in p.flat_args:
-      dispatch.check_arg(arg)
-    out = pxla.xla_pmap(
-        p.flat_fun, *p.flat_args, backend=backend, axis_name=axis_name,
-        axis_size=p.local_axis_size, global_axis_size=p.global_axis_size,
-        devices=p.devices,
-        in_axes=p.in_axes_flat, out_axes_thunk=p.out_axes_thunk,
-        name=p.flat_fun.__name__, donated_invars=p.donated_invars,
-        is_explicit_global_axis_size=p.is_explicit_global_axis_size)
-    return p.out_tree, out
-
-  return pmap_f
-
 
 def _shared_code_pmap(fun, axis_name, static_broadcasted_argnums,
                       donate_argnums, in_axes, out_axes):
@@ -1738,47 +1704,6 @@ def _shared_code_pmap(fun, axis_name, static_broadcasted_argnums,
   return axis_name, static_broadcasted_tuple, donate_tuple
 
 
-def _python_pmap(
-    fun: Callable,
-    axis_name: Optional[AxisName] = None,
-    *,
-    in_axes=0,
-    out_axes=0,
-    static_broadcasted_argnums: Union[int, Iterable[int]] = (),
-    devices: Optional[Sequence[xc.Device]] = None,  # noqa: F811
-    backend: Optional[str] = None,
-    axis_size: Optional[int] = None,
-    donate_argnums: Union[int, Iterable[int]] = (),
-  ) -> stages.Wrapped:
-  """The Python only implementation."""
-  axis_name, static_broadcasted_tuple, donate_tuple = _shared_code_pmap(
-      fun, axis_name, static_broadcasted_argnums, donate_argnums, in_axes,
-      out_axes)
-
-  @wraps(fun)
-  @api_boundary
-  def pmap_f(*args, **kwargs):
-    f_pmapped_ = _get_f_mapped(
-        fun=fun,
-        axis_name=axis_name,
-        in_axes=in_axes,
-        out_axes=out_axes,
-        static_broadcasted_tuple=static_broadcasted_tuple,
-        devices=devices,
-        backend=backend,
-        axis_size=axis_size,
-        donate_tuple=donate_tuple)
-
-    out_tree, out_flat = f_pmapped_(*args, **kwargs)
-    return tree_unflatten(out_tree(), out_flat)
-
-  pmap_f.lower = _pmap_lower(
-      fun, axis_name, in_axes, out_axes, static_broadcasted_tuple, devices,
-      backend, axis_size, donate_tuple)
-
-  return cast(stages.Wrapped, pmap_f)
-
-
 class _PmapFastpathData(NamedTuple):
   version: int  # For forward and backward compatibility
   xla_executable: xc.LoadedExecutable
diff --git a/jax/_src/api_util.py b/jax/_src/api_util.py
index 29f115a11..375bf3922 100644
--- a/jax/_src/api_util.py
+++ b/jax/_src/api_util.py
@@ -34,18 +34,9 @@ from jax._src import linear_util as lu
 from jax._src.linear_util import TracingDebugInfo
 from jax._src.util import (safe_map, WrapKwArgs, Hashable, HashableFunction,
                            Unhashable)
-from jax._src.config import flags, bool_env
 from jax._src import traceback_util
 traceback_util.register_exclusion(__file__)
 
-FLAGS = flags.FLAGS
-
-flags.DEFINE_bool(
-    "experimental_cpp_pmap", bool_env("JAX_CPP_PMAP", True),
-    "A flag enabling the C++ jax.pmap fast path. Until the default "
-    "is switched to True, the feature is not supported and possibly broken "
-    "(e.g. it may use unreleased code from jaxlib.")
-
 map = safe_map
 
 def _ensure_index(x: Any) -> Union[int, Tuple[int, ...]]:
diff --git a/tests/debug_nans_test.py b/tests/debug_nans_test.py
index 4357385b3..7dcd46e08 100644
--- a/tests/debug_nans_test.py
+++ b/tests/debug_nans_test.py
@@ -96,7 +96,7 @@ class DebugNaNsTest(jtu.JaxTestCase):
       f(1)
 
   def testPmap(self):
-    pmap_funcs = [api._python_pmap, api._cpp_pmap]
+    pmap_funcs = [api._cpp_pmap]
 
     for pmap in pmap_funcs:
       f = pmap(lambda x: 0. / x)
diff --git a/tests/pmap_test.py b/tests/pmap_test.py
index 725f8311b..01d2feb4e 100644
--- a/tests/pmap_test.py
+++ b/tests/pmap_test.py
@@ -138,7 +138,7 @@ class PythonPmapTest(jtu.JaxTestCase):
 
   @property
   def pmap(self):
-    return src_api._python_pmap
+    return src_api.pmap
 
   def testDeviceBufferToArray(self):
     sda = self.pmap(lambda x: x)(jnp.ones((jax.device_count(), 2)))