diff --git a/invokeai/app/invocations/segment_anything.py b/invokeai/app/invocations/segment_anything.py
index 3516f22687..7b9adf584a 100644
--- a/invokeai/app/invocations/segment_anything.py
+++ b/invokeai/app/invocations/segment_anything.py
@@ -55,7 +55,7 @@ class SegmentAnythingInvocation(BaseInvocation):
                 raise RuntimeError("Unable to load segmentation models")
 
             grounding_dino = GroundingSegmentAnythingDetector.build_grounding_dino(
-                cast(Dict[str, torch.Tensor], grounding_dino_state_dict)
+                cast(Dict[str, torch.Tensor], grounding_dino_state_dict), TorchDevice.choose_torch_device()
             )
             segment_anything = GroundingSegmentAnythingDetector.build_segment_anything(
                 cast(Dict[str, torch.Tensor], segment_anything_state_dict), TorchDevice.choose_torch_device()
diff --git a/invokeai/backend/image_util/grounding_segment_anything/gsa.py b/invokeai/backend/image_util/grounding_segment_anything/gsa.py
index 3102091bef..aa07e0218b 100644
--- a/invokeai/backend/image_util/grounding_segment_anything/gsa.py
+++ b/invokeai/backend/image_util/grounding_segment_anything/gsa.py
@@ -1,5 +1,5 @@
 import pathlib
-from typing import Dict, List, Optional
+from typing import Any, Dict, List, Optional
 
 import numpy as np
 import supervision as sv
@@ -18,13 +18,14 @@ class GroundingSegmentAnythingDetector:
         self.segment_anything_model: Optional[SamPredictor] = segment_anything_model
 
     @staticmethod
-    def build_grounding_dino(grounding_dino_state_dict: Dict[str, torch.Tensor]):
+    def build_grounding_dino(grounding_dino_state_dict: Dict[str, torch.Tensor], device: torch.device):
         grounding_dino_config = pathlib.Path(
             "./invokeai/backend/image_util/grounding_segment_anything/groundingdino/config/GroundingDINO_SwinT_OGC.py"
         )
         return Model(
             model_state_dict=grounding_dino_state_dict,
             model_config_path=grounding_dino_config.as_posix(),
+            device=device.type,
         )
 
     @staticmethod
@@ -35,12 +36,15 @@ class GroundingSegmentAnythingDetector:
 
     def detect_objects(
         self,
-        image: np.ndarray,
+        image: np.ndarray[Any, Any],
         prompts: List[str],
         box_threshold: float = 0.5,
         text_threshold: float = 0.5,
         nms_threshold: float = 0.8,
     ):
+        if not self.grounding_dino_model:
+            raise RuntimeError("GroundingDINO model could not load.")
+
         detections = self.grounding_dino_model.predict_with_classes(
             image=image, classes=prompts, box_threshold=box_threshold, text_threshold=text_threshold
         )
@@ -52,15 +56,18 @@ class GroundingSegmentAnythingDetector:
             .numpy()
             .tolist()
         )
-
         detections.xyxy = detections.xyxy[nms_idx]
         detections.confidence = detections.confidence[nms_idx]
         detections.class_id = detections.class_id[nms_idx]
+
         return detections
 
     def segment_detections(
-        self, image: np.ndarray, detections: sv.Detections, prompts: List[str]
-    ) -> Dict[str, np.ndarray]:
+        self, image: np.ndarray[Any, Any], detections: sv.Detections, prompts: List[str]
+    ) -> Dict[str, np.ndarray[Any, Any]]:
+        if not self.segment_anything_model:
+            raise RuntimeError("Segment Anything model could not be loaded")
+
         self.segment_anything_model.set_image(image)
         result_masks = {}
         for box, class_id in zip(detections.xyxy, detections.class_id):