diff --git a/pytensor/link/pytorch/dispatch/nlinalg.py b/pytensor/link/pytorch/dispatch/nlinalg.py
new file mode 100644
index 0000000000..6785e479f0
--- /dev/null
+++ b/pytensor/link/pytorch/dispatch/nlinalg.py
@@ -0,0 +1,15 @@
+import torch
+
+from pytensor.link.pytorch.dispatch.basic import pytorch_funcify
+from pytensor.tensor.math import Argmax
+
+
+@pytorch_funcify.register(Argmax)
+def pytorch_funcify_Argmax(op, **kwargs):
+    dim = op.axis
+    keepdim = op.keepdims
+
+    def argmax(x):
+        return torch.argmax(x, dim=dim, keepdim=keepdim)
+
+    return argmax
diff --git a/tests/link/pytorch/test_nlinalg.py b/tests/link/pytorch/test_nlinalg.py
new file mode 100644
index 0000000000..8bbbf21056
--- /dev/null
+++ b/tests/link/pytorch/test_nlinalg.py
@@ -0,0 +1,25 @@
+import numpy as np
+import pytest
+
+from pytensor.configdefaults import config
+from pytensor.graph import FunctionGraph
+from pytensor.graph.op import get_test_value
+from pytensor.tensor.math import argmax
+from pytensor.tensor.type import matrix
+from tests.link.pytorch.test_basic import compare_pytorch_and_py
+
+
+@pytest.mark.parametrize(
+    "keepdims",
+    [True, False],
+)
+@pytest.mark.parametrize(
+    "axis",
+    [None, 1, (0,)],
+)
+def test_pytorch_argmax(axis, keepdims):
+    a = matrix("a", dtype=config.floatX)
+    a.tag.test_value = np.random.randn(4, 4).astype(config.floatX)
+    amx = argmax(a, axis=axis, keepdims=keepdims)
+    fgraph = FunctionGraph([a], amx)
+    compare_pytorch_and_py(fgraph, [get_test_value(i) for i in fgraph.inputs])