diff --git a/invokeai/app/services/model_install/model_install_default.py b/invokeai/app/services/model_install/model_install_default.py
index 6a3117bcb8..32b31f744c 100644
--- a/invokeai/app/services/model_install/model_install_default.py
+++ b/invokeai/app/services/model_install/model_install_default.py
@@ -43,7 +43,6 @@ from invokeai.backend.model_manager.metadata.metadata_base import HuggingFaceMet
 from invokeai.backend.model_manager.probe import ModelProbe
 from invokeai.backend.model_manager.search import ModelSearch
 from invokeai.backend.util import InvokeAILogger
-from invokeai.backend.util.devices import TorchDevice
 
 from .model_install_base import (
     MODEL_SOURCE_TO_TYPE_MAP,
@@ -637,7 +636,7 @@ class ModelInstallService(ModelInstallServiceBase):
 
     def _guess_variant(self) -> Optional[ModelRepoVariant]:
         """Guess the best HuggingFace variant type to download."""
-        precision = TorchDevice.choose_torch_dtype()
+        precision = torch.float16 if self._app_config.precision == "auto" else torch.dtype(self._app_config.precision)
         return ModelRepoVariant.FP16 if precision == torch.float16 else None
 
     def _import_local_model(self, source: LocalModelSource, config: Optional[Dict[str, Any]]) -> ModelInstallJob:
diff --git a/invokeai/backend/util/devices.py b/invokeai/backend/util/devices.py
index c7db33a667..745c128099 100644
--- a/invokeai/backend/util/devices.py
+++ b/invokeai/backend/util/devices.py
@@ -59,13 +59,7 @@ class TorchDevice:
     def choose_torch_device(cls) -> torch.device:
         """Return the torch.device to use for accelerated inference."""
         if cls._model_cache:
-            try:
-                return cls._model_cache.get_execution_device()
-            except ValueError as e:  # May happen if no gpu was reserved. Return a generic device.
-                if str(e).startswith("No GPU has been reserved"):
-                    pass
-                else:
-                    raise e
+            return cls._model_cache.get_execution_device()
         app_config = get_config()
         if app_config.device != "auto":
             device = torch.device(app_config.device)