diff --git a/array_api_compat/torch/linalg.py b/array_api_compat/torch/linalg.py
index afef7504..52667391 100644
--- a/array_api_compat/torch/linalg.py
+++ b/array_api_compat/torch/linalg.py
@@ -4,6 +4,8 @@
 if TYPE_CHECKING:
     import torch
     array = torch.Tensor
+    from torch import dtype as Dtype
+    from typing import Optional
 
 from torch.linalg import *
 
@@ -12,9 +14,9 @@
 from torch import linalg as torch_linalg
 linalg_all = [i for i in dir(torch_linalg) if not i.startswith('_')]
 
-# These are implemented in torch but aren't in the linalg namespace
-from torch import outer, trace
-from ._aliases import _fix_promotion, matrix_transpose, tensordot
+# outer is implemented in torch but aren't in the linalg namespace
+from torch import outer
+from ._aliases import _fix_promotion, matrix_transpose, tensordot, sum
 
 # Note: torch.linalg.cross does not default to axis=-1 (it defaults to the
 # first axis with size 3), see https://github.com/pytorch/pytorch/issues/58743
@@ -49,6 +51,11 @@ def solve(x1: array, x2: array, /, **kwargs) -> array:
     x1, x2 = _fix_promotion(x1, x2, only_scalar=False)
     return torch.linalg.solve(x1, x2, **kwargs)
 
+# torch.trace doesn't support the offset argument and doesn't support stacking
+def trace(x: array, /, *, offset: int = 0, dtype: Optional[Dtype] = None) -> array:
+    # Use our wrapped sum to make sure it does upcasting correctly
+    return sum(torch.diagonal(x, offset=offset, dim1=-2, dim2=-1), axis=-1, dtype=dtype)
+
 __all__ = linalg_all + ['outer', 'trace', 'matrix_transpose', 'tensordot',
                         'vecdot', 'solve']