diff --git a/ui/media/js/main.js b/ui/media/js/main.js
index 403c1252..d7a30f79 100644
--- a/ui/media/js/main.js
+++ b/ui/media/js/main.js
@@ -524,12 +524,16 @@ async function doMakeImage(task) {
                 throw new Error('Connexion with server lost.')
             }
         } while (serverState.time > (Date.now() - (10 * 1000)) && serverState.task !== renderRequest.task)
-        if (serverState.session !== 'pending' && serverState.session !== 'running' && serverState.session !== 'buffer') {
-            if (serverState.session === 'stopped') {
+        switch(serverState.session) {
+            case 'pending':
+            case 'running':
+            case 'buffer':
+            case 'error': // Still valid, Update UI with error message
+                break
+            case 'stopped':
                 return false
-            }
-
-            throw new Error('Unexpected server task state: ' + serverState.session || 'Undefined')
+            default:
+                throw new Error('Unexpected server task state: ' + serverState.session || 'Undefined')
         }
         while (serverState.task === renderRequest.task && serverState.session === 'pending') {
             // Wait for task to start on server.
diff --git a/ui/sd_internal/runtime.py b/ui/sd_internal/runtime.py
index 7ff2459d..ec6961b4 100644
--- a/ui/sd_internal/runtime.py
+++ b/ui/sd_internal/runtime.py
@@ -250,9 +250,9 @@ def load_model_gfpgan():
     if thread_data.gfpgan_file is None:
         print('load_model_gfpgan called without setting gfpgan_file')
         return
-    if thread_data.device != 'cpu' and not is_first_cuda_device(thread_data.device):
+    if not is_first_cuda_device(thread_data.device):
         #TODO Remove when fixed - A bug with GFPGANer and facexlib needs to be fixed before use on other devices.
-        raise Exception(f'Current device {torch.device(thread_data.device)} is not {torch.device(0)}.')
+        raise Exception(f'Current device {torch.device(thread_data.device)} is not {torch.device(0)}. Cannot run GFPGANer.')
     model_path = thread_data.gfpgan_file + ".pth"
     thread_data.model_gfpgan = GFPGANer(device=torch.device(thread_data.device), model_path=model_path, upscale=1, arch='clean', channel_multiplier=2, bg_upsampler=None)
     print('loaded', thread_data.gfpgan_file, 'to', thread_data.model_gfpgan.device, 'precision', thread_data.precision)
@@ -369,10 +369,10 @@ def do_mk_img(req: Request):
     if needs_model_reload:
         load_model_ckpt()
 
-    if req.use_face_correction != thread_data.gfpgan_file:
+    if req.use_face_correction is not None and req.use_face_correction != thread_data.gfpgan_file:
         thread_data.gfpgan_file = req.use_face_correction
         load_model_gfpgan()
-    if req.use_upscale != thread_data.real_esrgan_file:
+    if req.use_upscale is not None and req.use_upscale != thread_data.real_esrgan_file:
         thread_data.real_esrgan_file = req.use_upscale
         load_model_real_esrgan()
 
diff --git a/ui/sd_internal/task_manager.py b/ui/sd_internal/task_manager.py
index 10d66fd4..9348fe18 100644
--- a/ui/sd_internal/task_manager.py
+++ b/ui/sd_internal/task_manager.py
@@ -225,23 +225,18 @@ def thread_render(device):
             continue
         try: # Select a render task.
             for queued_task in tasks_queue:
-                cpu_alive = is_alive('cpu')
                 if queued_task.request.use_face_correction: #TODO Remove when fixed - A bug with GFPGANer and facexlib needs to be fixed before use on other devices.
-                    # Allows GFPGANer on cuda:0 and use cpu only when cuda:0 is not available.
-                    first_device_alive = True if is_alive(0) >= 1 else False
-                    if cpu_alive <= 0 and not first_device_alive:
-                        queued_task.request.use_face_correction = False
-                        print('cuda:0 and cpu are not available with the current config. Removed GFPGANer filter to run task.')
+                    if is_alive(0) <= 0: # Allows GFPGANer only on cuda:0.
+                        queued_task.error = Exception('cuda:0 is not available with the current config. Remove GFPGANer filter to run task.')
+                        task = queued_task
                         continue
-                    if not queued_task.request.use_cpu:
-                        if first_device_alive:
-                            if not runtime.is_first_cuda_device(runtime.thread_data.device):
-                                continue # Wait for cuda:0
-                        elif cpu_alive > 0:
-                            print('cuda:0 is not available with the current config. Forcing task requiring GFPGANer to cpu.')
-                            queued_task.request.use_cpu = True
-                            continue
-                if queued_task.request.use_cpu and runtime.thread_data.device != 'cpu' and cpu_alive > 0:
+                    if queued_task.request.use_cpu:
+                        queued_task.error = Exception('Cpu cannot be used to run this task. Remove GFPGANer filter to run task.')
+                        task = queued_task
+                        continue
+                    if not runtime.is_first_cuda_device(runtime.thread_data.device):
+                        continue # Wait for cuda:0
+                if queued_task.request.use_cpu and runtime.thread_data.device != 'cpu' and is_alive('cpu') > 0:
                     continue # CPU Tasks, Skip GPU device
                 if not queued_task.request.use_cpu and runtime.thread_data.device == 'cpu' and is_alive() > 1: # cpu is alive, so need more than one.
                     continue # GPU Tasks, don't run on CPU unless there is nothing else.
@@ -254,6 +249,11 @@ def thread_render(device):
         if task is None:
             time.sleep(1)
             continue
+        if task.error is not None:
+            print(task.error)
+            task.response = { "status": 'failed', "detail": str(task.error) }
+            task.buffer_queue.put(json.dumps(task.response))
+            continue
         #if current_model_path != task.request.use_stable_diffusion_model:
         #    preload_model(task.request.use_stable_diffusion_model)
         if current_state_error: