diff --git a/comfy/model_base.py b/comfy/model_base.py
index 8274c7dea..8006f6dfc 100644
--- a/comfy/model_base.py
+++ b/comfy/model_base.py
@@ -134,7 +134,7 @@ class BaseModel(torch.nn.Module):
         if not unet_config.get("disable_unet_model_creation", False):
             if model_config.custom_operations is None:
                 fp8 = model_config.optimizations.get("fp8", False)
-                operations = comfy.ops.pick_operations(unet_config.get("dtype", None), self.manual_cast_dtype, fp8_optimizations=fp8, scaled_fp8=model_config.scaled_fp8)
+                operations = comfy.ops.pick_operations(unet_config.get("dtype", None), self.manual_cast_dtype, fp8_optimizations=fp8, scaled_fp8=model_config.scaled_fp8, scaled_fp8_activation=model_config.scaled_fp8_activation)
             else:
                 operations = model_config.custom_operations
             self.diffusion_model = unet_model(**unet_config, device=device, operations=operations)
diff --git a/comfy/model_detection.py b/comfy/model_detection.py
index 141f1e164..8ac50efc7 100644
--- a/comfy/model_detection.py
+++ b/comfy/model_detection.py
@@ -697,9 +697,9 @@ def model_config_from_unet(state_dict, unet_key_prefix, use_base_if_no_match=Fal
         if model_config.scaled_fp8 == torch.float32:
             model_config.scaled_fp8 = torch.float8_e4m3fn
         if scaled_fp8_weight.nelement() == 2:
-            model_config.optimizations["fp8"] = False
+            model_config.scaled_fp8_activation = False
         else:
-            model_config.optimizations["fp8"] = True
+            model_config.scaled_fp8_activation = True
 
     return model_config
 
diff --git a/comfy/ops.py b/comfy/ops.py
index 934e21261..38ad52dbf 100644
--- a/comfy/ops.py
+++ b/comfy/ops.py
@@ -423,8 +423,7 @@ def scaled_fp8_ops(fp8_matrix_mult=False, scale_input=False, override_dtype=None
 
                 if not scale_input:
                     self.scale_input = None
-
-                if not hasattr(self, 'scale_input'):
+                elif not hasattr(self, 'scale_input'):
                     self.scale_input = torch.nn.parameter.Parameter(data=torch.ones((), device=self.weight.device, dtype=torch.float32), requires_grad=False)
                 return None
 
@@ -478,16 +477,17 @@ if CUBLAS_IS_AVAILABLE:
             def forward(self, *args, **kwargs):
                 return super().forward(*args, **kwargs)
 
-def pick_operations(weight_dtype, compute_dtype, load_device=None, disable_fast_fp8=False, fp8_optimizations=False, scaled_fp8=None):
+def pick_operations(weight_dtype, compute_dtype, load_device=None, disable_fast_fp8=False, fp8_optimizations=False, scaled_fp8=None, scaled_fp8_activation=False):
     fp8_compute = comfy.model_management.supports_fp8_compute(load_device)
-    if scaled_fp8 is not None:
-        return scaled_fp8_ops(fp8_matrix_mult=fp8_compute and fp8_optimizations, scale_input=fp8_optimizations, override_dtype=scaled_fp8)
-
-    if (
+    fp8_optimizations = (
         fp8_compute and
-        (fp8_optimizations or PerformanceFeature.Fp8MatrixMultiplication in args.fast) and
-        not disable_fast_fp8
-    ):
+        (fp8_optimizations or PerformanceFeature.Fp8MatrixMultiplication in args.fast)
+        and not disable_fast_fp8
+    )
+    if scaled_fp8 is not None:
+        return scaled_fp8_ops(fp8_matrix_mult=fp8_optimizations, scale_input=scaled_fp8_activation, override_dtype=scaled_fp8)
+
+    if fp8_optimizations:
         return fp8_ops
 
     if (
diff --git a/comfy/supported_models_base.py b/comfy/supported_models_base.py
index 54573abb1..d4b2e09c2 100644
--- a/comfy/supported_models_base.py
+++ b/comfy/supported_models_base.py
@@ -50,6 +50,7 @@ class BASE:
     manual_cast_dtype = None
     custom_operations = None
     scaled_fp8 = None
+    scaled_fp8_activation = None
     optimizations = {"fp8": False}
 
     @classmethod