diff --git a/ui/sd_internal/runtime.py b/ui/sd_internal/runtime.py
index f278ec5f..34bb8c7a 100644
--- a/ui/sd_internal/runtime.py
+++ b/ui/sd_internal/runtime.py
@@ -351,23 +351,14 @@ def do_mk_img(req: Request):
         thread_data.ckpt_file = req.use_stable_diffusion_model
         needs_model_reload = True
 
-    if req.use_cpu:
-        if thread_data.device != 'cpu':
-            thread_data.device = 'cpu'
-            if thread_data.model_is_half:
-                load_model_ckpt()
-                needs_model_reload = False
+    if thread_data.has_valid_gpu:
+        if (thread_data.precision == 'autocast' and (req.use_full_precision or not thread_data.model_is_half)) or \
+            (thread_data.precision == 'full' and not req.use_full_precision and not thread_data.force_full_precision):
+            thread_data.precision = 'full' if req.use_full_precision else 'autocast'
+            load_model_ckpt()
             load_model_gfpgan()
             load_model_real_esrgan()
-    else:
-        if thread_data.has_valid_gpu:
-            if (thread_data.precision == 'autocast' and (req.use_full_precision or not thread_data.model_is_half)) or \
-                (thread_data.precision == 'full' and not req.use_full_precision and not thread_data.force_full_precision):
-                thread_data.precision = 'full' if req.use_full_precision else 'autocast'
-                load_model_ckpt()
-                load_model_gfpgan()
-                load_model_real_esrgan()
-                needs_model_reload = False
+            needs_model_reload = False
 
     if needs_model_reload:
         load_model_ckpt()
@@ -593,7 +584,8 @@ def do_mk_img(req: Request):
                     move_fs_to_cpu()
                     gc()
                     del x_samples, x_samples_ddim, x_sample
-                    print(f'memory_final = {round(torch.cuda.memory_allocated(thread_data.device) / 1e6, 2)}Mo')
+                    if thread_data.device != 'cpu':
+                        print(f'memory_final = {round(torch.cuda.memory_allocated(thread_data.device) / 1e6, 2)}Mo')
 
     print('Task completed')
 
diff --git a/ui/server.py b/ui/server.py
index 60d37693..68d22ac5 100644
--- a/ui/server.py
+++ b/ui/server.py
@@ -346,21 +346,21 @@ async def check_status(): # Task to Validate user config shortly after startup.
     # Issues found, try to fix and warn the user.
     device_count = 0
     for i in range(10): # Wait for devices to register and/or change names.
+        await asyncio.sleep(3)
         new_count = task_manager.is_alive()
         if device_count == new_count: break;
         device_count = new_count
-        await asyncio.sleep(3)
 
     if 'render_devices' in config and task_manager.is_alive() <= 0: # No running devices, probably invalid user config. Try to apply defaults.
         task_manager.start_render_thread('auto') # Detect best device for renders
         task_manager.start_render_thread('cpu') # Allow CPU to be used for renders
-        await asyncio.sleep(10) # delay message after thread start.
+        await asyncio.sleep(3) # delay message after thread start.
 
     display_warning = False
     if not 'render_devices' in config and task_manager.is_alive(0) <= 0: # No config set, is on auto mode and without cuda:0
         task_manager.start_render_thread('cuda') # An other cuda device is better and cuda:0 is missing, start it...
         display_warning = True # And warn user to update settings...
-        await asyncio.sleep(10) # delay message after thread start.
+        await asyncio.sleep(3) # delay message after thread start.
 
     if display_warning or task_manager.is_alive(0) <= 0:
         print('WARNING: GFPGANer only works on CPU or GPU:0, use CUDA_VISIBLE_DEVICES if GFPGANer is needed on a specific GPU.')
@@ -378,8 +378,7 @@ if 'render_devices' in config: # Start a new thread for each device.
     for device in config['render_devices']:
         task_manager.start_render_thread(device)
 else:
-    # Select best device GPU device using free memory if more than one device.
-    #task_manager.start_render_thread('cuda') # Starts silently on cuda:0
+    # Select best GPU device using free memory, if more than one device.
     task_manager.start_render_thread('auto') # Detect best device for renders
     task_manager.start_render_thread('cpu') # Allow CPU to be used for renders