diff --git a/test/test_foreach.py b/test/test_foreach.py
index 567d09cff02d..99d4cbe5ec00 100644
--- a/test/test_foreach.py
+++ b/test/test_foreach.py
@@ -90,7 +90,7 @@ def __call__(self, inputs, is_cuda, expect_fastpath, **kwargs):
             mta_called = any("multi_tensor_apply_kernel" in k for k in keys)
             assert mta_called == (
                 expect_fastpath and (not zero_size)
-            ), f"{mta_called=}, {expect_fastpath=}, {zero_size=}"
+            ), f"{mta_called=}, {expect_fastpath=}, {zero_size=}, {self.func.__name__=}, {keys=}"
         else:
             actual = self.func(*inputs, **kwargs)
         if self.is_inplace:
@@ -205,7 +205,6 @@ def test_all_zero_size_tensors_do_not_launch_kernel(self, device, dtype, op):
         "failing flakily on non sm86 cuda jobs",
     )
     def test_parity(self, device, dtype, op, noncontiguous, inplace):
-        torch.manual_seed(2024)
         if inplace:
             _, _, func, ref = self._get_funcs(op)
         else:
@@ -585,7 +584,6 @@ def test_binary_op_scalar_with_different_tensor_dtypes(self, device, dtype, op):
         "failing flakily on non sm86 cuda jobs, ex https://github.com/pytorch/pytorch/issues/125035",
     )
     def test_binary_op_list_error_cases(self, device, dtype, op):
-        torch.manual_seed(202406)
         foreach_op, foreach_op_, ref, ref_ = (
             op.method_variant,
             op.inplace_variant,
@@ -680,7 +678,6 @@ def test_binary_op_list_error_cases(self, device, dtype, op):
         "failing flakily on non sm86 cuda jobs, ex https://github.com/pytorch/pytorch/issues/125775",
     )
     def test_binary_op_list_slow_path(self, device, dtype, op):
-        torch.manual_seed(20240607)
         foreach_op, native_op, foreach_op_, native_op_ = self._get_funcs(op)
         # 0-strides
         tensor1 = make_tensor((10, 10), dtype=dtype, device=device)
@@ -799,7 +796,6 @@ def test_binary_op_list_slow_path(self, device, dtype, op):
         "failing flakily on non sm86 cuda jobs",
     )
     def test_binary_op_float_inf_nan(self, device, dtype, op):
-        torch.manual_seed(2024)
         inputs = (
             [
                 torch.tensor([float("inf")], device=device, dtype=dtype),
@@ -869,9 +865,6 @@ def test_unary_op_tensors_on_different_devices(self, device, dtype, op):
         "failing flakily on non sm86 cuda jobs",
     )
     def test_binary_op_tensors_on_different_devices(self, device, dtype, op):
-        torch.manual_seed(202406)
-        # `tensors1`: ['cuda', 'cpu']
-        # `tensors2`: ['cuda', 'cpu']
         _cuda_tensors = next(
             iter(op.sample_inputs(device, dtype, num_input_tensors=[2], same_size=True))
         ).input