diff --git a/modelopt/torch/quantization/model_calib.py b/modelopt/torch/quantization/model_calib.py
index 0077d8666..7171a2bf7 100644
--- a/modelopt/torch/quantization/model_calib.py
+++ b/modelopt/torch/quantization/model_calib.py
@@ -245,10 +245,10 @@ def mse_calibrate(
         step_size: Step size for amax search (default: 0.1).
         start_multiplier: Starting multiplier for amax search (default: 0.25).
         stop_multiplier: Ending multiplier for amax search (default: 4.0).
-        fp8_scale_sweep: If True, sweep over all 128 possible FP8 E4M3 scale values
+        fp8_scale_sweep: If True, sweep over all 126 valid FP8 E4M3 scale values
             for NVFP4 per-block quantization instead of using multipliers.
             This is specifically designed for optimizing the FP8-quantized
-            per-block scales in NVFP4 format (default: False).
+            per-block scales in NVFP4 format.
 
     See :class:`MseCalibConfig <modelopt.torch.quantization.config.MseCalibConfig>` for
     details on the remaining arguments.
diff --git a/modelopt/torch/quantization/nn/modules/tensor_quantizer.py b/modelopt/torch/quantization/nn/modules/tensor_quantizer.py
index e004cf0e7..145fc5217 100644
--- a/modelopt/torch/quantization/nn/modules/tensor_quantizer.py
+++ b/modelopt/torch/quantization/nn/modules/tensor_quantizer.py
@@ -768,7 +768,7 @@ def _fake_quantize(self, inputs):
                 inputs,
                 None,  # scale
                 None,  # scale_fp8_quant_amax
-                False,  # skip_scale_quant
+                True,  # skip_scale_quant
                 inputs.dtype,  # out_dtype
                 self._pass_through_bwd,  # pass_through_bwd
                 amax,  # amax