diff --git a/pytensor/link/pytorch/dispatch/__init__.py b/pytensor/link/pytorch/dispatch/__init__.py
index 7e476aba04..143d6b1bcb 100644
--- a/pytensor/link/pytorch/dispatch/__init__.py
+++ b/pytensor/link/pytorch/dispatch/__init__.py
@@ -5,4 +5,5 @@
 import pytensor.link.pytorch.dispatch.scalar
 import pytensor.link.pytorch.dispatch.elemwise
 import pytensor.link.pytorch.dispatch.extra_ops
+import pytensor.link.pytorch.dispatch.sort
 # isort: on
diff --git a/pytensor/link/pytorch/dispatch/sort.py b/pytensor/link/pytorch/dispatch/sort.py
new file mode 100644
index 0000000000..95e24c4fe3
--- /dev/null
+++ b/pytensor/link/pytorch/dispatch/sort.py
@@ -0,0 +1,25 @@
+import torch
+
+from pytensor.link.pytorch.dispatch.basic import pytorch_funcify
+from pytensor.tensor.sort import ArgSortOp, SortOp
+
+
+@pytorch_funcify.register(SortOp)
+def pytorch_funcify_Sort(op, **kwargs):
+    stable = op.kind == "stable"
+
+    def sort(arr, axis):
+        sorted, _ = torch.sort(arr, dim=axis, stable=stable)
+        return sorted
+
+    return sort
+
+
+@pytorch_funcify.register(ArgSortOp)
+def pytorch_funcify_ArgSort(op, **kwargs):
+    stable = op.kind == "stable"
+
+    def argsort(arr, axis):
+        return torch.argsort(arr, dim=axis, stable=stable)
+
+    return argsort
diff --git a/tests/link/pytorch/test_sort.py b/tests/link/pytorch/test_sort.py
new file mode 100644
index 0000000000..386a974cf4
--- /dev/null
+++ b/tests/link/pytorch/test_sort.py
@@ -0,0 +1,26 @@
+import numpy as np
+import pytest
+
+from pytensor.graph import FunctionGraph
+from pytensor.tensor import matrix
+from pytensor.tensor.sort import argsort, sort
+from tests.link.pytorch.test_basic import compare_pytorch_and_py
+
+
+@pytest.mark.parametrize("func", (sort, argsort))
+@pytest.mark.parametrize(
+    "axis",
+    [
+        pytest.param(0),
+        pytest.param(1),
+        pytest.param(
+            None, marks=pytest.mark.xfail(reason="Reshape Op not implemented")
+        ),
+    ],
+)
+def test_sort(func, axis):
+    x = matrix("x", shape=(2, 2), dtype="float64")
+    out = func(x, axis=axis)
+    fgraph = FunctionGraph([x], [out])
+    arr = np.array([[1.0, 4.0], [5.0, 2.0]])
+    compare_pytorch_and_py(fgraph, [arr])