diff --git a/tests/_test_utils/torch/quantization/tensor_quant_common.py b/tests/_test_utils/torch/quantization/tensor_quant_common.py
index 5119519ed02..7205e0c79c5 100644
--- a/tests/_test_utils/torch/quantization/tensor_quant_common.py
+++ b/tests/_test_utils/torch/quantization/tensor_quant_common.py
@@ -36,6 +36,7 @@ def test_simple_run(self):
 
     def test_per_tensor_scale(self):
         """Tensor_quant matches quantization"""
+        torch.manual_seed(123)  # an element on a rounding tie rounds differently in the reference
         x = torch.randn(31).to(self.device)
         quant_x_ref = quant(
             x,
diff --git a/tests/_test_utils/torch/quantization/tensor_quantizer_common.py b/tests/_test_utils/torch/quantization/tensor_quantizer_common.py
index 77d3acb7df3..c7ec0c2e53d 100644
--- a/tests/_test_utils/torch/quantization/tensor_quantizer_common.py
+++ b/tests/_test_utils/torch/quantization/tensor_quantizer_common.py
@@ -45,6 +45,7 @@ def test_simple_run(self):
 
     def test_per_tensor_scale(self):
         """Quantizer performs expected quantization"""
+        torch.manual_seed(123)  # an element on a rounding tie rounds differently in the reference
         x = torch.randn(31).to(self.device)
 
         quant_x = quant(x, torch.max(torch.abs(x)), fake=True)
@@ -54,6 +55,7 @@ def test_per_tensor_scale(self):
 
     def test_per_channel_scale(self):
         """Quantizer performs per channel scaling"""
+        torch.manual_seed(123)  # an element on a rounding tie rounds differently in the reference
         x = torch.randn(5, 5, 4, 8).to(self.device)
 
         # Pytorch filter layout seems to be KCRS, reduce max to shape [K, 1, 1, 1] to test per channel scale