diff --git a/modules/sdnq/common.py b/modules/sdnq/common.py
index fa121416b..04fc6ee4d 100644
--- a/modules/sdnq/common.py
+++ b/modules/sdnq/common.py
@@ -6,7 +6,7 @@ import torch
 
 from modules import shared, devices
 
-sdnq_version = "0.1.9"
+sdnq_version = "0.2.0"
 sdnq_keys = {"weight", "scale", "zero_point", "svd_up", "svd_down"}
 
 torch_version = torch.__version__[:4]
diff --git a/modules/sdnq/quant_utils.py b/modules/sdnq/quant_utils.py
index a8789f84e..d286e46c8 100644
--- a/modules/sdnq/quant_utils.py
+++ b/modules/sdnq/quant_utils.py
@@ -105,7 +105,7 @@ def get_hadamard(n: int, dtype: torch.dtype | None = None, device: torch.device
 
 
 @devices.inference_context()
-def rotate_hadamard(weight: torch.Tensor, group_size: int = 128, hadamard: torch.Tensor | None = None, is_conv: bool = False) -> torch.Tensor:
+def rotate_hadamard(weight: torch.Tensor, group_size: int = 128, hadamard: torch.FloatTensor | None = None, is_conv: bool = False) -> torch.Tensor:
     if hadamard is None:
         hadamard = get_hadamard(group_size, dtype=weight.dtype, device=weight.device)
     else:
@@ -122,7 +122,7 @@ def rotate_hadamard(weight: torch.Tensor, group_size: int = 128, hadamard: torch
 
 
 @devices.inference_context()
-def apply_hadamard(weight: torch.Tensor, group_size: int = 128, hadamard: torch.Tensor | None = None, layer_class_name: str | None = None) -> torch.Tensor:
+def apply_hadamard(weight: torch.Tensor, group_size: int = 128, hadamard: torch.FloatTensor | None = None, layer_class_name: str | None = None) -> torch.Tensor:
     is_conv = False
     use_hadamard = True
     if layer_class_name in conv_types or layer_class_name in conv_transpose_types:
@@ -138,7 +138,7 @@ def apply_hadamard(weight: torch.Tensor, group_size: int = 128, hadamard: torch.
     if group_size < 4:
         use_hadamard = False
     if use_hadamard:
-        weight = rotate_hadamard(weight, group_size=group_size, is_conv=is_conv)
+        weight = rotate_hadamard(weight, group_size=group_size, hadamard=hadamard, is_conv=is_conv)
     return weight, use_hadamard, group_size
 
 
diff --git a/modules/sdnq/quantizer.py b/modules/sdnq/quantizer.py
index e2e4045e1..fd3d7005b 100644
--- a/modules/sdnq/quantizer.py
+++ b/modules/sdnq/quantizer.py
@@ -181,7 +181,6 @@ def sdnq_quantize_layer_weight(weight, layer_class_name=None, weights_dtype="int
         else:
             group_size = -1
 
-
     cast_scale = True
     transpose_weights = False
     re_quantize_for_matmul = re_quantize_for_matmul or num_of_groups > 1
@@ -434,6 +433,7 @@ def sdnq_post_load_quant(
 ):
     quantization_config = SDNQConfig(
         weights_dtype=weights_dtype,
+        quantized_matmul_dtype=quantized_matmul_dtype,
         hadamard_group_size=hadamard_group_size,
         group_size=group_size,
         svd_rank=svd_rank,