diff --git a/modules/sdnq/quant_utils.py b/modules/sdnq/quant_utils.py
index 54f74e2f9..38c6b46f6 100644
--- a/modules/sdnq/quant_utils.py
+++ b/modules/sdnq/quant_utils.py
@@ -102,7 +102,7 @@ def build_hadamard_n4(n: int, dtype: torch.dtype | None = None, device: torch.de
 def build_hadamard(n: int, dtype: torch.dtype | None = None, device: torch.device | None = None) -> torch.FloatTensor:
     if math.log(n, 4).is_integer():
         return build_hadamard_n4(n, device=device, dtype=dtype)
-    elif math.log(n, 2).is_integer():
+    elif math.log2(n).is_integer():
         return build_hadamard_n2(n, device=device, dtype=dtype)
     else:
         raise RuntimeError("Hadamard Group Size must be a power of 2.")
@@ -151,7 +151,7 @@ def apply_hadamard(weight: torch.Tensor, group_size: int = 256, hadamard: torch.
         channel_size = weight.shape[1]
     else:
         channel_size = weight.shape[-1]
-    group_size = min(group_size, channel_size)
+    group_size = min(group_size, 2 ** int(math.log2(group_size)))
     if channel_size % group_size != 0:
         hadamard_pow2 = int(math.log2(group_size))
         while channel_size % group_size != 0:
diff --git a/modules/shared_items.py b/modules/shared_items.py
index 6999875c2..a8e8e55ec 100644
--- a/modules/shared_items.py
+++ b/modules/shared_items.py
@@ -179,5 +179,5 @@ def get_repo(model):
         return None
 
 
-sdnq_quant_modes = ["int8", "uint8", "int6", "uint6", "uint5", "uint4", "uint3", "uint2", "float8_e4m3fn", "float8_e3m4fn", "float6_e3m2fn", "float5_e2m2fn", "float4_e2m1fn", "float3_e1m1fn", "float2_e1m0fn"]
+sdnq_quant_modes = ["int8", "uint8", "int6", "uint6", "uint5", "uint4", "uint3", "uint2", "float8_e4m3fn", "float8_e3m4fn", "float6_e3m2fn", "float5_e2m2fn", "float4_e2m1fn", "float3_e1m1fn", "float2_e1m0fn", "int16", "uint16", "float16"]
 sdnq_matmul_modes = ["auto", "int8", "uint8", "float8_e4m3fn", "float16"]