diff --git a/extensions-builtin/Lora/lora_patches.py b/extensions-builtin/Lora/lora_patches.py
index 680ed4d0d..12986e8f9 100644
--- a/extensions-builtin/Lora/lora_patches.py
+++ b/extensions-builtin/Lora/lora_patches.py
@@ -1,4 +1,3 @@
-import os
 import torch
 import networks
 from modules import patches, shared
@@ -19,7 +18,7 @@ class LoraPatches:
         self.MultiheadAttention_load_state_dict = None
 
     def apply(self):
-        if self.active or os.environ.get('SD_LORA_DIFFUSERS', None): # OpenVINO only works with Diffusers LoRa loading
+        if self.active or (shared.opts.cuda_compile and shared.opts.cuda_compile_backend == "openvino_fx"): # OpenVINO only works with Diffusers LoRa loading
             return
         self.Linear_forward = patches.patch(__name__, torch.nn.Linear, 'forward', networks.network_Linear_forward)
         self.Linear_load_state_dict = patches.patch(__name__, torch.nn.Linear, '_load_from_state_dict', networks.network_Linear_load_state_dict)
@@ -37,7 +36,7 @@ class LoraPatches:
         self.active = True
 
     def undo(self):
-        if not self.active or os.environ.get('SD_LORA_DIFFUSERS', None): # OpenVINO only works with Diffusers LoRa loading
+        if not self.active or (shared.opts.cuda_compile and shared.opts.cuda_compile_backend == "openvino_fx"): # OpenVINO only works with Diffusers LoRa loading
             return
         self.Linear_forward = patches.undo(__name__, torch.nn.Linear, 'forward') # pylint: disable=E1128
         self.Linear_load_state_dict = patches.undo(__name__, torch.nn.Linear, '_load_from_state_dict') # pylint: disable=E1128
diff --git a/extensions-builtin/Lora/networks.py b/extensions-builtin/Lora/networks.py
index afd9d0796..015d2cece 100644
--- a/extensions-builtin/Lora/networks.py
+++ b/extensions-builtin/Lora/networks.py
@@ -166,10 +166,12 @@ def load_networks(names, te_multipliers=None, unet_multipliers=None, dyn_dims=No
             try:
                 if recompile_model:
                     shared.compiled_model_state.lora_model.append(f"{name}:{te_multipliers[i] if te_multipliers else 1.0}")
-                if shared.backend == shared.Backend.DIFFUSERS and (os.environ.get('SD_LORA_DIFFUSERS', None) # OpenVINO only works with Diffusers LoRa loading.
+                if shared.backend == shared.Backend.DIFFUSERS and (os.environ.get('SD_LORA_DIFFUSERS', None)
                                                                    or getattr(network_on_disk, 'shorthash', '').lower() == 'aaebf6360f7d' # sd15-lcm
                                                                    or getattr(network_on_disk, 'shorthash', '').lower() == '3d18b05e4f56' # sdxl-lcm
-                                                                   or getattr(network_on_disk, 'shorthash', '').lower() == '813ea5fb1c67'): # turbo sdxl-turbo
+                                                                   or getattr(network_on_disk, 'shorthash', '').lower() == '813ea5fb1c67' # turbo sdxl-turbo
+                                                                   or (shared.opts.cuda_compile and shared.opts.cuda_compile_backend == "openvino_fx")):
+                    # OpenVINO only works with Diffusers LoRa loading.
                     net = load_diffusers(name, network_on_disk, lora_scale=te_multipliers[i] if te_multipliers else 1.0)
                 else:
                     net = load_network(name, network_on_disk)
diff --git a/installer.py b/installer.py
index d7f069af9..7529f6cea 100644
--- a/installer.py
+++ b/installer.py
@@ -518,7 +518,6 @@ def check_torch():
         install('openvino==2023.2.0', 'openvino')
         install('onnxruntime-openvino', 'onnxruntime-openvino', ignore=True) # TODO openvino: numpy version conflicts with tensorflow and doesn't support Python 3.11
         os.environ.setdefault('PYTORCH_TRACING_MODE', 'TORCHFX')
-        os.environ.setdefault('SD_LORA_DIFFUSERS', '1')
         os.environ.setdefault('NEOReadDebugKeys', '1')
         os.environ.setdefault('ClDeviceGlobalMemSizeAvailablePercent', '100')
     if args.profile: