diff --git a/onnxscript/function_libs/torch_lib/ops/core.py b/onnxscript/function_libs/torch_lib/ops/core.py
index 4754588921..06fe120395 100644
--- a/onnxscript/function_libs/torch_lib/ops/core.py
+++ b/onnxscript/function_libs/torch_lib/ops/core.py
@@ -7699,12 +7699,23 @@ def aten_softmax_no_dtype(self: TFloatOrBFloat16, dim: int) -> TFloatOrBFloat16:
     return result
 
 
+@torch_op("aten::sort", traceable=True)
 def aten_sort(
-    self: TensorType, dim: int = -1, descending: bool = False
-) -> tuple[TensorType, TensorType]:
+    self: TReal, dim: INT64 = -1, descending: bool = False
+) -> tuple[TReal, INT64]:
     """sort(Tensor self, int dim=-1, bool descending=False) -> (Tensor values, Tensor indices)"""
 
-    raise NotImplementedError()
+    self_is_scalar = IsScalar(self)
+    if self_is_scalar:
+        self = op.Unsqueeze(self, op.Constant(value_ints=[0]))
+    shape = op.Shape(self)
+    dim_size = op.Gather(shape, dim, axis=0)
+    dim_size = op.Reshape(op.Cast(dim_size, to=INT64.dtype), op.Constant(value_ints=[1]))
+    values, indices = op.TopK(self, dim_size, axis=dim, largest=not descending, sorted=sorted)
+    if self_is_scalar:
+        values = op.Squeeze(values, op.Constant(value_ints=[0]))
+        indices = op.Squeeze(indices, op.Constant(value_ints=[0]))
+    return values, indices
 
 
 def aten_sparse_dim(self: TensorType) -> int:
diff --git a/tests/function_libs/torch_lib/ops_test_data.py b/tests/function_libs/torch_lib/ops_test_data.py
index 0a180bc483..8db28096ba 100644
--- a/tests/function_libs/torch_lib/ops_test_data.py
+++ b/tests/function_libs/torch_lib/ops_test_data.py
@@ -1440,6 +1440,7 @@ def _where_input_wrangler(
         reason="fixme: ORT failed. https://github.com/microsoft/onnxruntime/issues/16449",
         test_class_name="TestOutputConsistencyEager",
     ),
+    TorchLibOpInfo("sort", core_ops.aten_sort),
     TorchLibOpInfo(
         "split_with_sizes",
         core_ops.aten_split_with_sizes,