diff --git a/keras/src/backend/jax/math.py b/keras/src/backend/jax/math.py
index 9ee94de7cf2..720dd965d0c 100644
--- a/keras/src/backend/jax/math.py
+++ b/keras/src/backend/jax/math.py
@@ -43,6 +43,10 @@ def in_top_k(targets, predictions, k):
     preds_at_label = jnp.take_along_axis(
         predictions, jnp.expand_dims(targets, axis=-1), axis=-1
     )
+    # `nan` shouldn't be considered as large probability.
+    preds_at_label = jnp.where(
+        jnp.isnan(preds_at_label), -jnp.inf, preds_at_label
+    )
     rank = 1 + jnp.sum(jnp.greater(predictions, preds_at_label), axis=-1)
     return jnp.less_equal(rank, k)
 
diff --git a/keras/src/backend/numpy/math.py b/keras/src/backend/numpy/math.py
index 630b7912695..c75292c34d2 100644
--- a/keras/src/backend/numpy/math.py
+++ b/keras/src/backend/numpy/math.py
@@ -53,26 +53,17 @@ def segment_max(data, segment_ids, num_segments=None, sorted=False):
 
 
 def top_k(x, k, sorted=False):
-    sorted_indices = np.argsort(x, axis=-1)[..., ::-1]
-    sorted_values = np.sort(x, axis=-1)[..., ::-1]
-
     if sorted:
         # Take the k largest values.
+        sorted_indices = np.argsort(x, axis=-1)[..., ::-1]
+        sorted_values = np.take_along_axis(x, sorted_indices, axis=-1)
         top_k_values = sorted_values[..., :k]
         top_k_indices = sorted_indices[..., :k]
     else:
         # Partition the array such that all values larger than the k-th
         # largest value are to the right of it.
-        top_k_values = np.partition(x, -k, axis=-1)[..., -k:]
         top_k_indices = np.argpartition(x, -k, axis=-1)[..., -k:]
-
-        # Get the indices in sorted order.
-        idx = np.argsort(-top_k_values, axis=-1)
-
-        # Get the top k values and their indices.
-        top_k_values = np.take_along_axis(top_k_values, idx, axis=-1)
-        top_k_indices = np.take_along_axis(top_k_indices, idx, axis=-1)
-
+        top_k_values = np.take_along_axis(x, top_k_indices, axis=-1)
     return top_k_values, top_k_indices
 
 
diff --git a/keras/src/ops/math_test.py b/keras/src/ops/math_test.py
index 78caa448be3..7acbdb1b8b7 100644
--- a/keras/src/ops/math_test.py
+++ b/keras/src/ops/math_test.py
@@ -632,6 +632,14 @@ def test_in_top_k(self):
             kmath.in_top_k(targets, predictions, k=3), [True, True, True]
         )
 
+        # Test `nan` in predictions
+        # https://github.com/keras-team/keras/issues/19995
+        targets = np.array([1, 0])
+        predictions = np.array([[0.1, np.nan, 0.5], [0.3, 0.2, 0.5]])
+        self.assertAllEqual(
+            kmath.in_top_k(targets, predictions, k=2), [False, True]
+        )
+
     def test_logsumexp(self):
         x = np.random.rand(5, 5)
         outputs = kmath.logsumexp(x)