diff --git a/invokeai/app/invocations/compel.py b/invokeai/app/invocations/compel.py
index fffb09e6549..db7612eaa0c 100644
--- a/invokeai/app/invocations/compel.py
+++ b/invokeai/app/invocations/compel.py
@@ -85,7 +85,7 @@ def _lora_loader() -> Iterator[Tuple[LoRAModelRaw, float]]:
             ModelPatcher.apply_lora_text_encoder(
                 text_encoder,
                 loras=_lora_loader(),
-                model_state_dict=model_state_dict,
+                model_state_dict=None if context.config.get().disable_lora_patching_opt else model_state_dict,
             ),
             # Apply CLIP Skip after LoRA to prevent LoRA application from failing on skipped layers.
             ModelPatcher.apply_clip_skip(text_encoder, self.clip.skipped_layers),
@@ -181,7 +181,7 @@ def _lora_loader() -> Iterator[Tuple[LoRAModelRaw, float]]:
                 text_encoder,
                 loras=_lora_loader(),
                 prefix=lora_prefix,
-                model_state_dict=state_dict,
+                model_state_dict=None if context.config.get().disable_lora_patching_opt else state_dict,
             ),
             # Apply CLIP Skip after LoRA to prevent LoRA application from failing on skipped layers.
             ModelPatcher.apply_clip_skip(text_encoder, clip_field.skipped_layers),
diff --git a/invokeai/app/invocations/denoise_latents.py b/invokeai/app/invocations/denoise_latents.py
index 7ccf9068939..a0fb6722743 100644
--- a/invokeai/app/invocations/denoise_latents.py
+++ b/invokeai/app/invocations/denoise_latents.py
@@ -762,7 +762,7 @@ def _lora_loader() -> Iterator[Tuple[LoRAModelRaw, float]]:
             ModelPatcher.apply_lora_unet(
                 unet,
                 loras=_lora_loader(),
-                model_state_dict=model_state_dict,
+                model_state_dict=None if context.config.get().disable_lora_patching_opt else model_state_dict,
             ),
         ):
             assert isinstance(unet, UNet2DConditionModel)
diff --git a/invokeai/app/services/config/config_default.py b/invokeai/app/services/config/config_default.py
index 6c39760bdc8..82da4348c55 100644
--- a/invokeai/app/services/config/config_default.py
+++ b/invokeai/app/services/config/config_default.py
@@ -113,6 +113,7 @@ class InvokeAIAppConfig(BaseSettings):
         pil_compress_level: The compress_level setting of PIL.Image.save(), used for PNG encoding. All settings are lossless. 0 = no compression, 1 = fastest with slightly larger filesize, 9 = slowest with smallest filesize. 1 is typically the best setting.
         max_queue_size: Maximum number of items in the session queue.
         clear_queue_on_startup: Empties session queue on startup.
+        disable_lora_patching_opt: Disable LoRA patching optimization.
         allow_nodes: List of nodes to allow. Omit to allow all.
         deny_nodes: List of nodes to deny. Omit to deny none.
         node_cache_size: How many cached nodes to keep in memory.
@@ -186,6 +187,7 @@ class InvokeAIAppConfig(BaseSettings):
     pil_compress_level:             int = Field(default=1,                  description="The compress_level setting of PIL.Image.save(), used for PNG encoding. All settings are lossless. 0 = no compression, 1 = fastest with slightly larger filesize, 9 = slowest with smallest filesize. 1 is typically the best setting.")
     max_queue_size:                 int = Field(default=10000, gt=0,        description="Maximum number of items in the session queue.")
     clear_queue_on_startup:        bool = Field(default=False,              description="Empties session queue on startup.")
+    disable_lora_patching_opt:     bool = Field(default=False,              description="Disable LoRA patching optimization.")
 
     # NODES
     allow_nodes:    Optional[list[str]] = Field(default=None,               description="List of nodes to allow. Omit to allow all.")