diff --git a/modelopt/torch/export/quant_utils.py b/modelopt/torch/export/quant_utils.py
index eee13dc51..224164765 100755
--- a/modelopt/torch/export/quant_utils.py
+++ b/modelopt/torch/export/quant_utils.py
@@ -231,6 +231,25 @@ def get_scaling_factor(quantizer: TensorQuantizer) -> torch.Tensor:
     return scaling_factor
 
 
+def _ensure_weight_quantizer_calibrated(
+    weight_quantizer: TensorQuantizer, weight: torch.Tensor
+) -> None:
+    """Calibrate weight quantizer if amax is not set.
+
+    This is a lazy calibration pattern used during export when weight quantizers
+    may not have been calibrated during the main calibration phase.
+
+    Args:
+        weight_quantizer: The weight quantizer to calibrate
+        weight: The weight tensor to use for calibration
+    """
+    if not hasattr(weight_quantizer, "_amax") or weight_quantizer._amax is None:
+        weight_quantizer.reset_amax()
+        enable_stats_collection(weight_quantizer)
+        weight_quantizer(weight)
+        finish_stats_collection(weight_quantizer)
+
+
 def get_activation_scaling_factor(
     module: nn.Module, input_quantizer_name: str = "input_quantizer"
 ) -> torch.Tensor:
@@ -272,6 +291,9 @@ def get_weight_scaling_factor(module: nn.Module, weight_name: str = "weight") ->
         QUANTIZATION_NVFP4_AWQ,
         QUANTIZATION_W4A8_NVFP4_FP8,
     ]:
+        # Calibrate weight quantizer if amax is not set
+        _ensure_weight_quantizer_calibrated(weight_quantizer, weight)
+
         if quantization_format == QUANTIZATION_W4A8_NVFP4_FP8:
             # weight_scaling_factor_2 for w4a8 needs to be amax/448, so that the wsf is in range 448/6.
             # This is because the kernel dequantizes weight to fp8, which is in range 448.
@@ -304,10 +326,16 @@ def get_weight_scaling_factor_2(module: nn.Module, weight_name: str = "weight")
         QUANTIZATION_NVFP4,
         QUANTIZATION_NVFP4_AWQ,
     ]:
+        # Calibrate weight quantizer if amax is not set
+        weight = getattr(module, weight_name)
+        _ensure_weight_quantizer_calibrated(weight_quantizer, weight)
         return NVFP4QTensor.get_weights_scaling_factor_2_from_quantizer(weight_quantizer)
     elif get_quantization_format(module) == QUANTIZATION_W4A8_NVFP4_FP8:
         # weight_scaling_factor_2 for w4a8 needs to be amax/448, so that the wsf is in range 448/6.
         # This is because the kernel dequantizes weight to fp8, which is in range 448.
+        # Calibrate weight quantizer if amax is not set
+        weight = getattr(module, weight_name)
+        _ensure_weight_quantizer_calibrated(weight_quantizer, weight)
         return weight_quantizer._amax.float() / 448.0
 
     # SequentialQuantizer is required