diff --git a/CHANGELOG.md b/CHANGELOG.md
index 3190fe95d3b2..cca7775bad04 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -29,6 +29,14 @@ PLEASE REMEMBER TO CHANGE THE '..main' WITH AN ACTUAL TAG in GITHUB LINK.
     `dialect=` is passed.
   * The `jax.jit(f).lower(...).compiler_ir(dialect='mhlo')` now returns an MLIR
     `ir.Module` object instead of its string representation.
+  * `jax.test_util.JaxTestCase` now sets `jax_numpy_rank_promotion='raise'` by
+    default. To recover the previous behavior, use the `jax.test_util.with_config`
+    decorator:
+    ```python
+    @jtu.with_config(jax_numpy_rank_promotion='allow')
+    class MyTest(jtu.JaxTestCase):
+      ...
+    ```
 
 ## jaxlib 0.1.76 (Jan 27, 2022)
 
diff --git a/jax/_src/test_util.py b/jax/_src/test_util.py
index 484134a48f6b..baff15718876 100644
--- a/jax/_src/test_util.py
+++ b/jax/_src/test_util.py
@@ -915,7 +915,10 @@ def decorator(cls):
 
 class JaxTestCase(parameterized.TestCase):
   """Base class for JAX tests including numerical checks and boilerplate."""
-  _default_config = {'jax_enable_checks': True}
+  _default_config = {
+    'jax_enable_checks': True,
+    'jax_numpy_rank_promotion': 'raise',
+  }
 
   # TODO(mattjj): this obscures the error messages from failures, figure out how
   # to re-enable it
diff --git a/jax/experimental/jax2tf/tests/tf_test_util.py b/jax/experimental/jax2tf/tests/tf_test_util.py
index b12b448a0965..2ad4f9492737 100644
--- a/jax/experimental/jax2tf/tests/tf_test_util.py
+++ b/jax/experimental/jax2tf/tests/tf_test_util.py
@@ -150,6 +150,7 @@ def ComputeTfValueAndGrad(tf_f: Callable, tf_args: Sequence,
   return f1(*args1)
 
 
+@jtu.with_config(jax_numpy_rank_promotion="allow")
 class JaxToTfTestCase(jtu.JaxTestCase):
 
   def setUp(self):
diff --git a/tests/api_test.py b/tests/api_test.py
index 671cadd2d57a..2a9704613be7 100644
--- a/tests/api_test.py
+++ b/tests/api_test.py
@@ -70,7 +70,6 @@
 numpy_version = tuple(map(int, np.__version__.split('.')[:3]))
 
 
-@jtu.with_config(jax_numpy_rank_promotion="raise")
 class CPPJitTest(jtu.BufferDonationTestCase):
   """Shared tests between the Python and the C++ jax,jit implementations.
 
@@ -860,7 +859,7 @@ def f(k):
       python_should_be_executing = False
       self.assertEqual(x, f(x))
 
-@jtu.with_config(jax_numpy_rank_promotion="raise")
+
 class PythonJitTest(CPPJitTest):
 
   @property
@@ -868,7 +867,6 @@ def jit(self):
     return api._python_jit
 
 
-@jtu.with_config(jax_numpy_rank_promotion="raise")
 class APITest(jtu.JaxTestCase):
 
   def test_grad_item(self):
@@ -3416,7 +3414,6 @@ def f(x):
         FLAGS.jax_numpy_rank_promotion = allow_promotion
 
 
-@jtu.with_config(jax_numpy_rank_promotion="raise")
 class RematTest(jtu.JaxTestCase):
 
   @parameterized.named_parameters(
@@ -4273,7 +4270,6 @@ def f(u, x):
 
     _ = api.linearize(partial(f, core.unit), 3.)
 
-@jtu.with_config(jax_numpy_rank_promotion="raise")
 class JaxprTest(jtu.JaxTestCase):
 
   def test_scalar_literals(self):
@@ -4417,7 +4413,6 @@ def test_convert_element_type_literal_constant_folding(self):
     self.assertLen(jaxpr.eqns, 0)
 
 
-@jtu.with_config(jax_numpy_rank_promotion="raise")
 class CustomJVPTest(jtu.JaxTestCase):
 
   def test_basic(self):
@@ -5392,7 +5387,6 @@ def f_jvp(primals, tangents):
     self.assertEqual(shape, ())
 
 
-@jtu.with_config(jax_numpy_rank_promotion="raise")
 class CustomVJPTest(jtu.JaxTestCase):
 
   def test_basic(self):
@@ -6361,7 +6355,6 @@ def transposed(y):
   return transposed
 
 
-@jtu.with_config(jax_numpy_rank_promotion="raise")
 class CustomTransposeTest(jtu.JaxTestCase):
 
   def test_linear_call(self):
@@ -6690,7 +6683,6 @@ def tp(r, t): return t / r
     self.assertAllClose(f_t(x), jax.jit(f_t)(x))
 
 
-@jtu.with_config(jax_numpy_rank_promotion="raise")
 class CustomVmapTest(jtu.JaxTestCase):
 
   def test_basic(self):
@@ -7117,7 +7109,6 @@ def vmap_ref(xs, y):
     self.assertEqual(str(jaxpr), str(jaxpr_ref))
 
 
-@jtu.with_config(jax_numpy_rank_promotion="raise")
 class CustomApiTest(jtu.JaxTestCase):
   """Test interactions among the custom_{vmap,jvp,vjp,transpose,*} APIs"""
 
@@ -7155,7 +7146,6 @@ def test_def_method_forwarding_all_permutations(self):
           self.assertIsInstance(getattr(f, method), Callable)
 
 
-@jtu.with_config(jax_numpy_rank_promotion="raise")
 class InvertibleADTest(jtu.JaxTestCase):
 
   @jtu.ignore_warning(message="Values that an @invertible function closes")
@@ -7264,7 +7254,6 @@ def f(x, y):
                         check_dtypes=True)
 
 
-@jtu.with_config(jax_numpy_rank_promotion="raise")
 class BufferDonationTest(jtu.BufferDonationTestCase):
 
   @jtu.skip_on_devices("cpu")  # In/out aliasing not supported on CPU.
@@ -7287,7 +7276,6 @@ def test_pmap_nested_donate_ignored(self):
     pmap_fun(a)  # doesn't crash
 
 
-@jtu.with_config(jax_numpy_rank_promotion="raise")
 class NamedCallTest(jtu.JaxTestCase):
 
   def test_default_name(self):
@@ -7368,7 +7356,6 @@ def test_integer_overflow(self, jit_type, func):
     self.assertRaises(OverflowError, f, int_min - 1)
 
 
-@jtu.with_config(jax_numpy_rank_promotion="raise")
 class BackendsTest(jtu.JaxTestCase):
 
   @unittest.skipIf(not sys.executable, "test requires sys.executable")
@@ -7391,7 +7378,6 @@ def test_cpu_warning_suppression(self):
     assert "No GPU/TPU found" not in result.stderr.decode()
 
 
-@jtu.with_config(jax_numpy_rank_promotion="raise")
 class CleanupTest(jtu.JaxTestCase):
   def test_call_wrapped_second_phase_cleanup(self):
     try:
@@ -7552,6 +7538,7 @@ def f(x, n):
     self.assertIs(jaxpr.jaxpr.invars[1], jaxpr.out_avals[0].shape[0])
     self.assertEqual(4, jaxpr.out_avals[0].shape[1])
 
+  @jax.numpy_rank_promotion("allow")  # explicitly exercises implicit rank promotion.
   def test_basic_batchpoly_neuralnet(self):
     def predict(params, inputs):
       for W, b in params:
diff --git a/tests/batching_test.py b/tests/batching_test.py
index 00cea40a6bea..b7d0cf640856 100644
--- a/tests/batching_test.py
+++ b/tests/batching_test.py
@@ -40,7 +40,6 @@
 # These are 'manual' tests for batching (vmap). The more exhaustive, more
 # systematic tests are in lax_test.py's LaxVmapTest class.
 
-@jtu.with_config(jax_numpy_rank_promotion="raise")
 class BatchingTest(jtu.JaxTestCase):
 
   def testConstantFunction(self):
diff --git a/tests/fft_test.py b/tests/fft_test.py
index 53125e15e45d..b597cc6b7bf0 100644
--- a/tests/fft_test.py
+++ b/tests/fft_test.py
@@ -93,7 +93,6 @@ def _zero_for_irfft(z, axes):
   return jnp.concatenate(parts, axis=axis)
 
 
-@jtu.with_config(jax_numpy_rank_promotion="raise")
 class FftTest(jtu.JaxTestCase):
 
   def testNotImplemented(self):
diff --git a/tests/infeed_test.py b/tests/infeed_test.py
index 2d9e75ed59f1..570038343309 100644
--- a/tests/infeed_test.py
+++ b/tests/infeed_test.py
@@ -26,7 +26,6 @@
 
 config.parse_flags_with_absl()
 
-@jtu.with_config(jax_numpy_rank_promotion="raise")
 class InfeedTest(jtu.JaxTestCase):
 
   @jax.numpy_rank_promotion("allow")  # Test explicitly exercises implicit rank promotion.
diff --git a/tests/lax_autodiff_test.py b/tests/lax_autodiff_test.py
index e91bd02f4fdf..4c959a7f1c58 100644
--- a/tests/lax_autodiff_test.py
+++ b/tests/lax_autodiff_test.py
@@ -189,7 +189,7 @@ def check_grads_bilinear(f, args, order,
   check_grads(lambda rhs: f(lhs, rhs), (rhs,), order,
               modes=modes, atol=atol, rtol=rtol, eps=1.)
 
-@jtu.with_config(jax_numpy_rank_promotion="raise")
+
 class LaxAutodiffTest(jtu.JaxTestCase):
 
   @parameterized.named_parameters(itertools.chain.from_iterable(
diff --git a/tests/lax_numpy_einsum_test.py b/tests/lax_numpy_einsum_test.py
index 12c687a0a9bd..a9ed44a06a48 100644
--- a/tests/lax_numpy_einsum_test.py
+++ b/tests/lax_numpy_einsum_test.py
@@ -30,7 +30,6 @@
 config.parse_flags_with_absl()
 
 
-@jtu.with_config(jax_numpy_rank_promotion="raise")
 class EinsumTest(jtu.JaxTestCase):
 
   def _check(self, s, *ops):
diff --git a/tests/lax_numpy_indexing_test.py b/tests/lax_numpy_indexing_test.py
index cdf19edda531..740eb2a371db 100644
--- a/tests/lax_numpy_indexing_test.py
+++ b/tests/lax_numpy_indexing_test.py
@@ -414,7 +414,6 @@ def check_grads(f, args, order, atol=None, rtol=None, eps=None):
 MODES = ["clip", "drop", "promise_in_bounds"]
 
 
-@jtu.with_config(jax_numpy_rank_promotion="raise")
 class IndexingTest(jtu.JaxTestCase):
   """Tests for Numpy indexing translation rules."""
 
@@ -997,7 +996,6 @@ def _update_tol(op):
   return tol
 
 
-@jtu.with_config(jax_numpy_rank_promotion="raise")
 class IndexedUpdateTest(jtu.JaxTestCase):
 
   @parameterized.named_parameters(jtu.named_cases_from_sampler(lambda s: ({
diff --git a/tests/lax_numpy_test.py b/tests/lax_numpy_test.py
index db3a458b70aa..bc596d8d2703 100644
--- a/tests/lax_numpy_test.py
+++ b/tests/lax_numpy_test.py
@@ -519,7 +519,6 @@ def wrapper(*args, **kw):
   return wrapper
 
 
-@jtu.with_config(jax_numpy_rank_promotion="raise")
 class LaxBackedNumpyTests(jtu.JaxTestCase):
   """Tests for LAX-backed Numpy implementation."""
 
@@ -5915,7 +5914,6 @@ def grad_test_spec(op, nargs, order, rng_factory, dtypes, name=None, tol=None):
     GradSpecialValuesTestSpec(jnp.sinc, [0.], 1),
 ]
 
-@jtu.with_config(jax_numpy_rank_promotion="raise")
 class NumpyGradTests(jtu.JaxTestCase):
 
   @parameterized.named_parameters(itertools.chain.from_iterable(
@@ -6020,7 +6018,6 @@ def testGradLogaddexp2Complex(self, shapes, dtype):
       tol = 3e-2
     check_grads(jnp.logaddexp2, args, 1, ["fwd", "rev"], tol, tol)
 
-@jtu.with_config(jax_numpy_rank_promotion="raise")
 class NumpySignaturesTest(jtu.JaxTestCase):
 
   def testWrappedSignaturesMatch(self):
@@ -6136,7 +6133,6 @@ def _dtypes_for_ufunc(name: str) -> Iterator[Tuple[str, ...]]:
       yield arg_dtypes
 
 
-@jtu.with_config(jax_numpy_rank_promotion="raise")
 class NumpyUfuncTests(jtu.JaxTestCase):
 
   @parameterized.named_parameters(
@@ -6168,7 +6164,6 @@ def testUfuncInputTypes(self, name, arg_dtypes):
     # that jnp returns float32. e.g. np.cos(np.uint8(0))
     self._CheckAgainstNumpy(np_op, jnp_op, args_maker, check_dtypes=False, tol=1E-2)
 
-@jtu.with_config(jax_numpy_rank_promotion="raise")
 class NumpyDocTests(jtu.JaxTestCase):
 
   def test_lax_numpy_docstrings(self):
diff --git a/tests/lax_numpy_vectorize_test.py b/tests/lax_numpy_vectorize_test.py
index 0e8fd29fe91d..2cbf3ef28794 100644
--- a/tests/lax_numpy_vectorize_test.py
+++ b/tests/lax_numpy_vectorize_test.py
@@ -25,7 +25,6 @@
 config.parse_flags_with_absl()
 
 
-@jtu.with_config(jax_numpy_rank_promotion="raise")
 class VectorizeTest(jtu.JaxTestCase):
 
   @parameterized.named_parameters(jtu.cases_from_list(
diff --git a/tests/lax_scipy_sparse_test.py b/tests/lax_scipy_sparse_test.py
index 93c9140b6bbf..671050fe9bd8 100644
--- a/tests/lax_scipy_sparse_test.py
+++ b/tests/lax_scipy_sparse_test.py
@@ -64,7 +64,6 @@ def rand_sym_pos_def(rng, shape, dtype):
   return matrix @ matrix.T.conj()
 
 
-@jtu.with_config(jax_numpy_rank_promotion="raise")
 class LaxBackedScipyTests(jtu.JaxTestCase):
 
   def _fetch_preconditioner(self, preconditioner, A, rng=None):
diff --git a/tests/lax_scipy_test.py b/tests/lax_scipy_test.py
index 489c6023202c..346981b3de57 100644
--- a/tests/lax_scipy_test.py
+++ b/tests/lax_scipy_test.py
@@ -144,7 +144,6 @@ def op_record(name, nargs, dtypes, rng_factory, test_grad, nondiff_argnums=(), t
 ]
 
 
-@jtu.with_config(jax_numpy_rank_promotion="raise")
 class LaxBackedScipyTests(jtu.JaxTestCase):
   """Tests for LAX-backed Scipy implementation."""
 
diff --git a/tests/lax_test.py b/tests/lax_test.py
index d1efe27f8d7b..2b0b44c72ee3 100644
--- a/tests/lax_test.py
+++ b/tests/lax_test.py
@@ -181,7 +181,6 @@ def op_record(op, nargs, dtypes, rng_factory, tol=None):
 ]
 
 
-@jtu.with_config(jax_numpy_rank_promotion="raise")
 class LaxTest(jtu.JaxTestCase):
   """Numerical tests for LAX operations."""
 
@@ -2669,7 +2668,6 @@ def testDynamicSliceU8Index(self):
         np.array(lax.dynamic_slice(x, np.uint8([128]), (1,))), [128])
 
 
-@jtu.with_config(jax_numpy_rank_promotion="raise")
 class LazyConstantTest(jtu.JaxTestCase):
   def _Check(self, make_const, expected):
     # check casting to ndarray works
@@ -2872,7 +2870,6 @@ def testLog1pNearOne(self):
         np.log1p(np.float32(1e-5)), lax.log1p(np.complex64(1e-5)))
 
 
-@jtu.with_config(jax_numpy_rank_promotion="raise")
 class LaxNamedShapeTest(jtu.JaxTestCase):
 
   def test_abstract_eval(self):
diff --git a/tests/linalg_test.py b/tests/linalg_test.py
index 2f98b07b81d1..5d3863eeabb0 100644
--- a/tests/linalg_test.py
+++ b/tests/linalg_test.py
@@ -42,7 +42,6 @@
 complex_types = jtu.dtypes.complex
 
 
-@jtu.with_config(jax_numpy_rank_promotion='raise')
 class NumpyLinalgTest(jtu.JaxTestCase):
 
   def testNotImplemented(self):
@@ -957,7 +956,6 @@ def f(inp):
     self.assertFalse(np.any(np.isnan(cube_func(a))))
 
 
-@jtu.with_config(jax_numpy_rank_promotion='raise')
 class ScipyLinalgTest(jtu.JaxTestCase):
 
   @parameterized.named_parameters(jtu.cases_from_list(
@@ -1374,7 +1372,7 @@ def expm(x):
       jtu.check_grads(expm, (a,), modes=["fwd", "rev"], order=1, atol=tol,
                       rtol=tol)
 
-@jtu.with_config(jax_numpy_rank_promotion='raise')
+
 class LaxLinalgTest(jtu.JaxTestCase):
 
   def run_test(self, alpha, beta):
diff --git a/tests/nn_test.py b/tests/nn_test.py
index fe41be4e5f0c..1659f7d40781 100644
--- a/tests/nn_test.py
+++ b/tests/nn_test.py
@@ -35,7 +35,6 @@
 config.parse_flags_with_absl()
 
 
-@jtu.with_config(jax_numpy_rank_promotion="raise")
 class NNFunctionsTest(jtu.JaxTestCase):
   @jtu.skip_on_flag("jax_skip_slow_tests", True)
   def testSoftplusGrad(self):
@@ -230,7 +229,7 @@ def initializer_record(name, initializer, dtypes, min_dims=2, max_dims=4):
     initializer_record("delta_orthogonal", nn.initializers.delta_orthogonal, jtu.dtypes.floating, 4, 4)
 ]
 
-@jtu.with_config(jax_numpy_rank_promotion="raise")
+
 class NNInitializersTest(jtu.JaxTestCase):
   @parameterized.named_parameters(jtu.cases_from_list(
       {"testcase_name":
diff --git a/tests/pjit_test.py b/tests/pjit_test.py
index b02eb8d4854c..d847fed51c1f 100644
--- a/tests/pjit_test.py
+++ b/tests/pjit_test.py
@@ -74,7 +74,6 @@ def check_1d_2d_mesh(f, set_mesh):
 
 
 # TODO(skye): make the buffer donation utils part of JaxTestCase
-@jtu.with_config(jax_numpy_rank_promotion="raise")
 class PJitTest(jtu.BufferDonationTestCase):
 
   @jtu.with_mesh([('x', 1)])
@@ -635,7 +634,6 @@ def f(x, y):
     self.assertEqual(f(1, 'bye'), 5)
 
 
-@jtu.with_config(jax_numpy_rank_promotion="raise")
 class GDAPjitTest(jtu.JaxTestCase):
 
   @jtu.with_mesh([('x', 4), ('y', 2)])
@@ -953,7 +951,6 @@ def spec_regex(s):
   return str(s).replace(r"(", r"\(").replace(r")", r"\)")
 
 
-@jtu.with_config(jax_numpy_rank_promotion="raise")
 class PJitErrorTest(jtu.JaxTestCase):
   @check_1d_2d_mesh(set_mesh=True)
   def testNonDivisibleArgs(self, mesh, resources):
@@ -1181,7 +1178,6 @@ def h(x):
       f(x)
 
 
-@jtu.with_config(jax_numpy_rank_promotion="raise")
 class UtilTest(jtu.JaxTestCase):
 
   def testOpShardingRoundTrip(self):
diff --git a/tests/pmap_test.py b/tests/pmap_test.py
index 0f60577b16f6..a00dde7a131f 100644
--- a/tests/pmap_test.py
+++ b/tests/pmap_test.py
@@ -109,7 +109,6 @@ def tearDownModule():
   jtu.ignore_warning, message=".*is an experimental.*")
 
 
-@jtu.with_config(jax_numpy_rank_promotion="raise")
 class PythonPmapTest(jtu.JaxTestCase):
 
   @property
@@ -1905,7 +1904,6 @@ def pmap(self):
     return src_api._cpp_pmap
 
 
-@jtu.with_config(jax_numpy_rank_promotion="raise")
 class VmapOfPmapTest(jtu.JaxTestCase):
 
   # TODO(apaszke)
@@ -1948,7 +1946,6 @@ def args_slice(vi, pi):
     self.assertAllClose(ans, expected)
 
 
-@jtu.with_config(jax_numpy_rank_promotion="raise")
 class VmapPmapCollectivesTest(jtu.JaxTestCase):
 
   @parameterized.named_parameters(
@@ -2134,7 +2131,6 @@ def f(x):
     self.assertAllClose(f(jax.pmap)(x), f(jax.vmap)(x))
 
 
-@jtu.with_config(jax_numpy_rank_promotion="raise")
 class PmapWithDevicesTest(jtu.JaxTestCase):
 
   def testAllDevices(self):
@@ -2387,7 +2383,6 @@ def h(y):
                         jax.grad(mk_case(vmap))(x, y))
 
 
-@jtu.with_config(jax_numpy_rank_promotion="raise")
 class ShardedDeviceArrayTest(jtu.JaxTestCase):
 
   def testThreadsafeIndexing(self):
@@ -2493,7 +2488,6 @@ def test_delete_is_idempotent(self):
       _ = x[0]
 
 
-@jtu.with_config(jax_numpy_rank_promotion="raise")
 class SpecToIndicesTest(jtu.JaxTestCase):
 
   def testShardsPerAxis(self):
@@ -2623,7 +2617,6 @@ def _spec_str(spec):
           f"{spec.mesh_mapping},)")
 
 
-@jtu.with_config(jax_numpy_rank_promotion="raise")
 class ShardArgsTest(jtu.JaxTestCase):
 
   def numpy_array(x):
diff --git a/tests/qdwh_test.py b/tests/qdwh_test.py
index 6377ef2c1c49..5e2e35d627a2 100644
--- a/tests/qdwh_test.py
+++ b/tests/qdwh_test.py
@@ -58,7 +58,6 @@ def _compute_relative_diff(actual, expected):
 _dot = functools.partial(jnp.dot, precision="highest")
 
 
-@jtu.with_config(jax_numpy_rank_promotion="raise")
 class QdwhTest(jtu.JaxTestCase):
 
   @parameterized.named_parameters(jtu.cases_from_list(
diff --git a/tests/random_test.py b/tests/random_test.py
index 68dbf53f2e08..c949a706c314 100644
--- a/tests/random_test.py
+++ b/tests/random_test.py
@@ -56,7 +56,6 @@ def _prng_key_as_array(key):
               ('unsafe_rbg', prng.unsafe_rbg_prng_impl)]
 
 
-@jtu.with_config(jax_numpy_rank_promotion="raise")
 class PrngTest(jtu.JaxTestCase):
 
   def testThreefry2x32(self):
@@ -315,7 +314,6 @@ def test_key_array_indexing_nd(self):
                            lambda: keys[0, 1, None, 2])
 
 
-@jtu.with_config(jax_numpy_rank_promotion="raise")
 class LaxRandomTest(jtu.JaxTestCase):
 
   def _CheckCollisions(self, samples, nbits):
@@ -1226,7 +1224,6 @@ def _double_threefry_fold_in(key, data):
 
 @skipIf(not config.jax_enable_custom_prng,
         'custom PRNG tests require config.jax_enable_custom_prng')
-@jtu.with_config(jax_numpy_rank_promotion="raise")
 class LaxRandomWithCustomPRNGTest(LaxRandomTest):
   def seed_prng(self, seed):
     return prng.seed_with_impl(double_threefry_prng_impl, seed)
@@ -1255,7 +1252,6 @@ def test_grad_of_prng_key(self):
 
 @skipIf(not config.jax_enable_custom_prng,
         'custom PRNG tests require config.jax_enable_custom_prng')
-@jtu.with_config(jax_numpy_rank_promotion="raise")
 class LaxRandomWithRBGPRNGTest(LaxRandomTest):
   def seed_prng(self, seed):
     return random.rbg_key(seed)
diff --git a/tests/scipy_fft_test.py b/tests/scipy_fft_test.py
index a4ab47066226..31bc01e7173a 100644
--- a/tests/scipy_fft_test.py
+++ b/tests/scipy_fft_test.py
@@ -42,7 +42,7 @@ def _get_dctn_test_s(shape, axes):
     s_list.extend(itertools.product(*[[shape[ax]+i for i in range(-shape[ax]+1, shape[ax]+1)] for ax in axes]))
   return s_list
 
-@jtu.with_config(jax_numpy_rank_promotion="raise")
+
 class LaxBackedScipyFftTests(jtu.JaxTestCase):
   """Tests for LAX-backed scipy.fft implementations"""
 
diff --git a/tests/scipy_ndimage_test.py b/tests/scipy_ndimage_test.py
index 347e025c52b0..045146d6a052 100644
--- a/tests/scipy_ndimage_test.py
+++ b/tests/scipy_ndimage_test.py
@@ -57,7 +57,6 @@ def _fixed_ref_map_coordinates(input, coordinates, order, mode, cval=0.0):
   return result
 
 
-@jtu.with_config(jax_numpy_rank_promotion="raise")
 class NdimageTest(jtu.JaxTestCase):
 
   @parameterized.named_parameters(jtu.cases_from_list(
diff --git a/tests/scipy_optimize_test.py b/tests/scipy_optimize_test.py
index a2207e8c2e05..d98329735310 100644
--- a/tests/scipy_optimize_test.py
+++ b/tests/scipy_optimize_test.py
@@ -64,7 +64,6 @@ def zakharovFromIndices(x, ii):
   return answer
 
 
-@jtu.with_config(jax_numpy_rank_promotion="raise")
 class TestBFGS(jtu.JaxTestCase):
 
   @parameterized.named_parameters(jtu.cases_from_list(
@@ -141,7 +140,6 @@ def f(x):
       jax.scipy.optimize.minimize(f, jnp.ones(2), args=45, method='BFGS')
 
 
-@jtu.with_config(jax_numpy_rank_promotion="raise")
 class TestLBFGS(jtu.JaxTestCase):
 
   @parameterized.named_parameters(jtu.cases_from_list(
diff --git a/tests/scipy_signal_test.py b/tests/scipy_signal_test.py
index 4c9a80747114..0162a2915a96 100644
--- a/tests/scipy_signal_test.py
+++ b/tests/scipy_signal_test.py
@@ -35,7 +35,6 @@
 default_dtypes = jtu.dtypes.floating + jtu.dtypes.integer + jtu.dtypes.complex
 
 
-@jtu.with_config(jax_numpy_rank_promotion="raise")
 class LaxBackedScipySignalTests(jtu.JaxTestCase):
   """Tests for LAX-backed scipy.stats implementations"""
 
diff --git a/tests/sharded_jit_test.py b/tests/sharded_jit_test.py
index 37248e36f281..a83784e1d042 100644
--- a/tests/sharded_jit_test.py
+++ b/tests/sharded_jit_test.py
@@ -39,7 +39,6 @@
 config.parse_flags_with_absl()
 
 
-@jtu.with_config(jax_numpy_rank_promotion="raise")
 class ShardedJitTest(jtu.JaxTestCase):
 
   def setUp(self):
@@ -277,7 +276,6 @@ def testCompilationCache(self):
 
 
 # TODO(skye): add more error tests
-@jtu.with_config(jax_numpy_rank_promotion="raise")
 class ShardedJitErrorsTest(jtu.JaxTestCase):
 
   def setUp(self):
@@ -300,7 +298,6 @@ def f(x):
 
 
 # Tests that don't need a TPU to run.
-@jtu.with_config(jax_numpy_rank_promotion="raise")
 class ShardedJitTestNoTpu(jtu.JaxTestCase):
 
   def testTranslationRule(self):
@@ -329,7 +326,7 @@ def f(x):
     # Annotation from sharded_jit
     self.assertIn("sharding={replicated}", hlo.as_hlo_text())
 
-@jtu.with_config(jax_numpy_rank_promotion="raise")
+
 class PmapOfShardedJitTest(jtu.JaxTestCase):
 
   def setUp(self):
diff --git a/tests/sparse_test.py b/tests/sparse_test.py
index 9c672d4531cc..72456ad6c830 100644
--- a/tests/sparse_test.py
+++ b/tests/sparse_test.py
@@ -116,7 +116,6 @@ def _rand_sparse(shape, dtype, nse=nse):
   return _rand_sparse
 
 
-@jtu.with_config(jax_numpy_rank_promotion="raise")
 class cuSparseTest(jtu.JaxTestCase):
   def gpu_dense_conversion_warning_context(self, dtype):
     if jtu.device_under_test() == "gpu" and np.issubdtype(dtype, np.integer):
@@ -555,7 +554,6 @@ def test_coo_matmul_ad(self, shape, dtype, bshape):
     self.assertAllClose(out_dense, out_sparse, atol=tol, rtol=tol)
 
 
-@jtu.with_config(jax_numpy_rank_promotion="raise")
 class BCOOTest(jtu.JaxTestCase):
   @parameterized.named_parameters(jtu.cases_from_list(
       {"testcase_name": "_{}_nbatch={}_ndense={}".format(
@@ -1679,7 +1677,6 @@ def test_bcoo_bad_fillvals(self):
     self.assertArraysEqual((y_sp @ x_sp).todense(), y_de @ x_de)
 
 
-@jtu.with_config(jax_numpy_rank_promotion="raise")
 class SparseGradTest(jtu.JaxTestCase):
   def test_sparse_grad(self):
     rng_sparse = rand_sparse(self.rng())
@@ -1702,7 +1699,6 @@ def f(X, y):
     self.assertArraysEqual(grad_sparse.todense(), grad_sparse_from_dense)
 
 
-@jtu.with_config(jax_numpy_rank_promotion="raise")
 class SparseObjectTest(jtu.JaxTestCase):
   def test_repr(self):
     M = sparse.BCOO.fromdense(jnp.arange(5, dtype='float32'))
@@ -1898,7 +1894,6 @@ def test_bcoo_methods(self):
     self.assertArraysEqual(M.sum(), Msp.sum())
 
 
-@jtu.with_config(jax_numpy_rank_promotion="raise")
 class SparseRandomTest(jtu.JaxTestCase):
   @parameterized.named_parameters(jtu.cases_from_list(
       {"testcase_name": "_{}_indices_dtype={}_nbatch={}_ndense={}".format(
diff --git a/tests/sparsify_test.py b/tests/sparsify_test.py
index b622d59dfb69..aa03ef129135 100644
--- a/tests/sparsify_test.py
+++ b/tests/sparsify_test.py
@@ -30,7 +30,6 @@
 config.parse_flags_with_absl()
 
 
-@jtu.with_config(jax_numpy_rank_promotion="raise")
 class SparsifyTest(jtu.JaxTestCase):
   @classmethod
   def sparsify(cls, f):
diff --git a/tests/xmap_test.py b/tests/xmap_test.py
index b196e9812374..f3ec3f40e8b3 100644
--- a/tests/xmap_test.py
+++ b/tests/xmap_test.py
@@ -210,7 +210,6 @@ def divisors2(n: int) -> Iterator[Tuple[int, int]]:
           yield axis_resources, mesh_data
 
 
-@jtu.with_config(jax_numpy_rank_promotion="raise")
 class XMapTestCase(jtu.BufferDonationTestCase):
   pass
 
@@ -1178,7 +1177,6 @@ def test_xeinsum_no_named_axes_reduce_sum(self):
     self.assertAllClose(out, expected, check_dtypes=True)
 
 
-@jtu.with_config(jax_numpy_rank_promotion="raise")
 class XMapErrorTest(jtu.JaxTestCase):
 
   @jtu.with_mesh([('x', 2)])
@@ -1410,7 +1408,6 @@ def testAxesMismatch(self):
       xmap(lambda x: x, (p,), (p, ['x']))([x, x, x])  # Error, we raise a generic tree mismatch message
 
 
-@jtu.with_config(jax_numpy_rank_promotion="raise")
 class NamedAutodiffTests(jtu.JaxTestCase):
 
   def testVjpReduceAxes(self):