diff --git a/tests/brevitas/graph/test_calibration.py b/tests/brevitas/graph/test_calibration.py
index b22994275..52819c22f 100644
--- a/tests/brevitas/graph/test_calibration.py
+++ b/tests/brevitas/graph/test_calibration.py
@@ -12,6 +12,7 @@
 from brevitas.graph.calibrate import bias_correction_mode
 from brevitas.graph.calibrate import calibration_mode
 from brevitas.graph.calibrate import load_quant_model_mode
+from brevitas.inject.enum import RestrictValueType
 import brevitas.nn as qnn
 from brevitas.quant import Int8ActPerTensorFixedPoint
 from brevitas.quant.experimental.float import Fp8e4m3ActPerTensorFloat
@@ -27,7 +28,9 @@
 BATCH = 1
 REFERENCE_SCALES = {
     'int_quant': (0.00935234408825635910, 0.01362917013466358185),
-    'fp_quant': (0.00249395845457911491, 0.00363444536924362183)}
+    'fp_quant': (0.00249395845457911491, 0.00363444536924362183),
+    'int_po2_quant': (0.015625, 0.015625),
+    'fp_po2_quant': (0.001953125, 0.00390625),}
 REFERENCE_INP = torch.tensor([[-1.8645, -0.4071, 1.1971]])
 REFERENCE_WEIGHTS = torch.tensor([[1.0023, 0.0205, 1.4604], [-0.2918, -1.8218, -0.7010],
                                   [1.4573, -0.9074, -0.2708]])
@@ -75,7 +78,15 @@ def forward(self, x):
     assert torch.allclose(expected_scale, scale)
 
 
-QUANTS = {'int_quant': Int8ActPerTensorFloat, 'fp_quant': Fp8e4m3ActPerTensorFloat}
+class Fp8e4m3ActPerTensorFixedPoint(Fp8e4m3ActPerTensorFloat):
+    restrict_scaling_type = RestrictValueType.POWER_OF_TWO
+
+
+QUANTS = {
+    'int_quant': Int8ActPerTensorFloat,
+    'fp_quant': Fp8e4m3ActPerTensorFloat,
+    'int_po2_quant': Int8ActPerTensorFixedPoint,
+    'fp_po2_quant': Fp8e4m3ActPerTensorFixedPoint}
 
 
 @pytest_cases.parametrize("act_quant", QUANTS.items(), ids=QUANTS.keys())