diff --git a/pytensor/link/jax/dispatch/nlinalg.py b/pytensor/link/jax/dispatch/nlinalg.py
index c79178a74c..0235f3c5db 100644
--- a/pytensor/link/jax/dispatch/nlinalg.py
+++ b/pytensor/link/jax/dispatch/nlinalg.py
@@ -1,4 +1,5 @@
 import jax.numpy as jnp
+import numpy as np
 
 from pytensor.link.jax.dispatch import jax_funcify
 from pytensor.tensor.blas import BatchedDot
@@ -137,12 +138,10 @@ def argmax(x):
 
         # NumPy does not support multiple axes for argmax; this is a
         # work-around
-        keep_axes = jnp.array(
-            [i for i in range(x.ndim) if i not in axes], dtype="int64"
-        )
+        keep_axes = np.array([i for i in range(x.ndim) if i not in axes], dtype="int64")
         # Not-reduced axes in front
         transposed_x = jnp.transpose(
-            x, jnp.concatenate((keep_axes, jnp.array(axes, dtype="int64")))
+            x, tuple(np.concatenate((keep_axes, np.array(axes, dtype="int64"))))
         )
         kept_shape = transposed_x.shape[: len(keep_axes)]
         reduced_shape = transposed_x.shape[len(keep_axes) :]
@@ -151,9 +150,9 @@ def argmax(x):
         # Otherwise reshape would complain citing float arg
         new_shape = (
             *kept_shape,
-            jnp.prod(jnp.array(reduced_shape, dtype="int64"), dtype="int64"),
+            np.prod(np.array(reduced_shape, dtype="int64"), dtype="int64"),
         )
-        reshaped_x = transposed_x.reshape(new_shape)
+        reshaped_x = transposed_x.reshape(tuple(new_shape))
 
         max_idx_res = jnp.argmax(reshaped_x, axis=-1).astype("int64")
 
diff --git a/tests/link/jax/test_extra_ops.py b/tests/link/jax/test_extra_ops.py
index c9920b31cc..94c442b165 100644
--- a/tests/link/jax/test_extra_ops.py
+++ b/tests/link/jax/test_extra_ops.py
@@ -65,9 +65,9 @@ def test_extra_ops():
 
 @pytest.mark.xfail(
     version_parse(jax.__version__) >= version_parse("0.2.12"),
-    reason="Omnistaging cannot be disabled",
+    reason="JAX Numpy API does not support dynamic shapes",
 )
-def test_extra_ops_omni():
+def test_extra_ops_dynamic_shapes():
     a = matrix("a")
     a.tag.test_value = np.arange(6, dtype=config.floatX).reshape((3, 2))
 
diff --git a/tests/link/jax/test_nlinalg.py b/tests/link/jax/test_nlinalg.py
index 0bc6749448..4340b395cb 100644
--- a/tests/link/jax/test_nlinalg.py
+++ b/tests/link/jax/test_nlinalg.py
@@ -1,6 +1,5 @@
 import numpy as np
 import pytest
-from packaging.version import parse as version_parse
 
 from pytensor.compile.function import function
 from pytensor.compile.mode import Mode
@@ -80,11 +79,7 @@ def assert_fn(x, y):
     compare_jax_and_py(out_fg, [X.astype(config.floatX)], assert_fn=assert_fn)
 
 
-@pytest.mark.xfail(
-    version_parse(jax.__version__) >= version_parse("0.2.12"),
-    reason="Omnistaging cannot be disabled",
-)
-def test_jax_basic_multiout_omni():
+def test_jax_max_and_argmax():
     # Test that a single output of a multi-output `Op` can be used as input to
     # another `Op`
     x = dvector()
@@ -95,10 +90,6 @@ def test_jax_basic_multiout_omni():
     compare_jax_and_py(out_fg, [np.r_[1, 2]])
 
 
-@pytest.mark.xfail(
-    version_parse(jax.__version__) >= version_parse("0.2.12"),
-    reason="Omnistaging cannot be disabled",
-)
 def test_tensor_basics():
     y = vector("y")
     y.tag.test_value = np.r_[1.0, 2.0].astype(config.floatX)