diff --git a/torchvision/models/quantization/mobilenetv3.py b/torchvision/models/quantization/mobilenetv3.py
index f8fe39ed195..2d18446c13f 100644
--- a/torchvision/models/quantization/mobilenetv3.py
+++ b/torchvision/models/quantization/mobilenetv3.py
@@ -140,6 +140,10 @@ def _mobilenet_v3_model(
     _replace_relu(model)
 
     if quantize:
+        # Instead of quantizing the model and then loading the quantized weights we take a different approach.
+        # We prepare the QAT model, load the QAT weights from training and then convert it.
+        # This is done to avoid extremely low accuracies observed on the specific model. This is rather a workaround
+        # for an unresolved bug on the eager quantization API detailed at: https://github.com/pytorch/vision/issues/5890
         model.fuse_model(is_qat=True)
         model.qconfig = torch.ao.quantization.get_default_qat_qconfig(backend)
         torch.ao.quantization.prepare_qat(model, inplace=True)