diff --git a/keras/backend/torch/numpy.py b/keras/backend/torch/numpy.py
index 3f058f39b7e..e3ab6d0b170 100644
--- a/keras/backend/torch/numpy.py
+++ b/keras/backend/torch/numpy.py
@@ -892,9 +892,7 @@ def min(x, axis=None, keepdims=False, initial=None):
     if axis is None:
         result = torch.min(x)
     else:
-        if isinstance(axis, list):
-            axis = axis[-1]
-        result = torch.min(x, dim=axis, keepdim=keepdims)
+        result = amin(x, axis=axis, keepdims=keepdims)
 
     if isinstance(getattr(result, "values", None), torch.Tensor):
         result = result.values
diff --git a/keras/ops/numpy_test.py b/keras/ops/numpy_test.py
index a52e138f7d5..40043f5dd3f 100644
--- a/keras/ops/numpy_test.py
+++ b/keras/ops/numpy_test.py
@@ -3429,6 +3429,12 @@ def test_min(self):
         self.assertAllClose(knp.min(x), np.min(x))
         self.assertAllClose(knp.Min()(x), np.min(x))
 
+        self.assertAllClose(knp.min(x, axis=(0, 1)), np.min(x, (0, 1)))
+        self.assertAllClose(knp.Min((0, 1))(x), np.min(x, (0, 1)))
+
+        self.assertAllClose(knp.min(x, axis=()), np.min(x, axis=()))
+        self.assertAllClose(knp.Min(())(x), np.min(x, axis=()))
+
         self.assertAllClose(knp.min(x, 0), np.min(x, 0))
         self.assertAllClose(knp.Min(0)(x), np.min(x, 0))