diff --git a/test/test_distributions.py b/test/test_distributions.py
index a3adae7df..6d23aa905 100644
--- a/test/test_distributions.py
+++ b/test/test_distributions.py
@@ -53,6 +53,8 @@
 )
 from numpyro.nn import AutoregressiveNN
 
+from .utils import get_python_version_specific_seed
+
 TEST_FAILURE_RATE = 2e-5  # For all goodness-of-fit tests.
 
 
@@ -1653,7 +1655,7 @@ def test_gof(jax_dist, sp_dist, params):
     num_samples = 10000
     if "BetaProportion" in jax_dist.__name__:
         num_samples = 20000
-    rng_key = random.PRNGKey(19470715)
+    rng_key = random.PRNGKey(get_python_version_specific_seed(0, 19470715))
     d = jax_dist(*params)
     samples = d.sample(key=rng_key, sample_shape=(num_samples,))
     probs = np.exp(d.log_prob(samples))
@@ -1935,7 +1937,7 @@ def test_mean_var(jax_dist, sp_dist, params):
         else 200000
     )
     d_jax = jax_dist(*params)
-    k = random.PRNGKey(19470715)
+    k = random.PRNGKey(get_python_version_specific_seed(0, 19470715))
     samples = d_jax.sample(k, sample_shape=(n,)).astype(np.float32)
     # check with suitable scipy implementation if available
     # XXX: VonMises is already tested below
@@ -2433,7 +2435,7 @@ def test_biject_to(constraint, shape):
         assert transform.codomain.upper_bound == constraint.upper_bound
     if len(shape) < event_dim:
         return
-    rng_key = random.PRNGKey(19470715)
+    rng_key = random.PRNGKey(get_python_version_specific_seed(0, 19470715))
     x = random.normal(rng_key, shape)
     y = transform(x)
 
@@ -2558,7 +2560,7 @@ def inv_vec_transform(y):
 )
 def test_bijective_transforms(transform, event_shape, batch_shape):
     shape = batch_shape + event_shape
-    rng_key = random.PRNGKey(20020626)
+    rng_key = random.PRNGKey(get_python_version_specific_seed(0, 20020626))
     x = biject_to(transform.domain)(random.normal(rng_key, shape))
     y = transform(x)
 
diff --git a/test/test_distributions_util.py b/test/test_distributions_util.py
index ef434201a..14be5d47c 100644
--- a/test/test_distributions_util.py
+++ b/test/test_distributions_util.py
@@ -26,6 +26,8 @@
     von_mises_centered,
 )
 
+from .utils import get_python_version_specific_seed
+
 
 @pytest.mark.parametrize("x, y", [(0.2, 10.0), (0.6, -10.0)])
 def test_binary_cross_entropy_with_logits(x, y):
@@ -133,7 +135,9 @@ def test_vec_to_tril_matrix(shape, diagonal):
 @pytest.mark.parametrize("dim", [1, 4])
 @pytest.mark.parametrize("coef", [1, -1])
 def test_cholesky_update(chol_batch_shape, vec_batch_shape, dim, coef):
-    key1, key2 = random.split(random.PRNGKey(19470715))
+    key1, key2 = random.split(
+        random.PRNGKey(get_python_version_specific_seed(0, 19470715))
+    )
     A = random.normal(key1, chol_batch_shape + (dim, dim))
     A = A @ jnp.swapaxes(A, -2, -1) + jnp.eye(dim)
     x = random.normal(key2, vec_batch_shape + (dim,)) * 0.1
diff --git a/test/utils.py b/test/utils.py
new file mode 100644
index 000000000..d1ffb910c
--- /dev/null
+++ b/test/utils.py
@@ -0,0 +1,21 @@
+# Copyright Contributors to the Pyro project.
+# SPDX-License-Identifier: Apache-2.0
+
+
+import sys
+
+
+def get_python_version_specific_seed(
+    seed_for_py_3_9: int, seed_not_for_py_3_9: int
+) -> int:
+    """After release of `jax==0.5.0`, we need different seeds for tests in Python 3.9
+    and other versions. This function returns the seed based on the Python version.
+
+    :param seed_for_py_3_9: Seed for Python 3.9
+    :param seed_not_for_py_3_9: Seed for other versions of Python
+    :return: Seed based on the Python version
+    """
+    if sys.version_info.minor == 9:
+        return seed_for_py_3_9
+    else:
+        return seed_not_for_py_3_9