diff --git a/backends/exllamav2/model.py b/backends/exllamav2/model.py
index 989c80a9..987da9ae 100644
--- a/backends/exllamav2/model.py
+++ b/backends/exllamav2/model.py
@@ -128,6 +128,7 @@ def progress(loaded_modules: int, total_modules: int,
         # Turn off GPU split if the user is using 1 GPU
         gpu_count = torch.cuda.device_count()
         gpu_split_auto = unwrap(kwargs.get("gpu_split_auto"), True)
+        gpu_device_list = list(range(0, gpu_count))
 
         if gpu_count > 1 and gpu_split_auto:
             # Auto GPU split parameters
@@ -141,6 +142,12 @@ def progress(loaded_modules: int, total_modules: int,
             # Manual GPU split
             self.gpu_split = kwargs.get("gpu_split")
             self.gpu_split_auto = False
+
+            gpu_device_list = [
+                device_idx
+                for device_idx, memory in enumerate(self.gpu_split)
+                if memory > 0
+            ]
         else:
             # One GPU setup
             self.gpu_split_auto = False
@@ -185,6 +192,27 @@ def progress(loaded_modules: int, total_modules: int,
         # Enable fasttensors loading if present
         self.config.fasttensors = unwrap(kwargs.get("fasttensors"), False)
 
+        # Disable paged mode if the user's min GPU isn't supported (ampere and up)
+        min_compute_capability = min(
+            torch.cuda.get_device_capability(device=device_idx)[0]
+            for device_idx in gpu_device_list
+        )
+
+        # Compute capability < 8 is not supported by FA2
+        # AMD is also unsupported until ROCm updates its FA2 fork
+        if torch.version.hip or min_compute_capability < 8:
+            logger.warning(
+                "An unsupported GPU is found in this configuration. "
+                "Switching to compatibility mode. \n"
+                "This disables parallel batching "
+                "and features that rely on it (ex. CFG). \n"
+                "To disable compatability mode, all GPUs must be ampere "
+                "(30 series) or newer. AMD GPUs are not supported."
+            )
+            self.config.no_flash_attn = True
+            self.paged = False
+            self.max_batch_size = 1
+
         # Try to set prompt template
         self.prompt_template = self.find_prompt_template(
             kwargs.get("prompt_template"), model_directory
@@ -397,31 +425,6 @@ async def load_gen(self, progress_callback=None, **kwargs):
             async for value in iterate_in_threadpool(model_load_generator):
                 yield value
 
-            # Disable paged mode if the user's min GPU isn't supported (ampere and up)
-            device_list = {
-                module.device_idx
-                for module in self.model.modules
-                if module.device_idx >= 0
-            }
-            min_compute_capability = min(
-                torch.cuda.get_device_capability(device=device)[0]
-                for device in device_list
-            )
-
-            # Compute capability < 8 is not supported by FA2
-            # AMD is also unsupported until ROCm updates its FA2 fork
-            if torch.version.hip or min_compute_capability < 8:
-                logger.warning(
-                    "An unsupported GPU is found in this configuration. "
-                    "Switching to compatibility mode. \n"
-                    "This disables parallel batching "
-                    "and features that rely on it (ex. CFG). \n"
-                    "To disable compatability mode, all GPUs must be ampere "
-                    "(30 series) or newer. AMD GPUs are not supported."
-                )
-                self.paged = False
-                self.max_batch_size = 1
-
             # Create async generator
             self.generator = ExLlamaV2DynamicGeneratorAsync(
                 model=self.model,