diff --git a/invokeai/app/invocations/grounding_dino.py b/invokeai/app/invocations/grounding_dino.py
index a7d522e784..1e3d5cea0c 100644
--- a/invokeai/app/invocations/grounding_dino.py
+++ b/invokeai/app/invocations/grounding_dino.py
@@ -1,4 +1,5 @@
 from pathlib import Path
+from typing import Literal
 
 import torch
 from PIL import Image
@@ -12,7 +13,11 @@ from invokeai.app.services.shared.invocation_context import InvocationContext
 from invokeai.backend.image_util.grounding_dino.detection_result import DetectionResult
 from invokeai.backend.image_util.grounding_dino.grounding_dino_pipeline import GroundingDinoPipeline
 
-GROUNDING_DINO_MODEL_ID = "IDEA-Research/grounding-dino-tiny"
+GroundingDinoModelKey = Literal["grounding-dino-tiny", "grounding-dino-base"]
+GROUNDING_DINO_MODEL_IDS: dict[GroundingDinoModelKey, str] = {
+    "grounding-dino-tiny": "IDEA-Research/grounding-dino-tiny",
+    "grounding-dino-base": "IDEA-Research/grounding-dino-base",
+}
 
 
 @invocation(
@@ -30,6 +35,7 @@ class GroundingDinoInvocation(BaseInvocation):
     # - https://huggingface.co/docs/transformers/v4.43.3/en/model_doc/grounding-dino#grounded-sam
     # - https://github.com/NielsRogge/Transformers-Tutorials/blob/a39f33ac1557b02ebfb191ea7753e332b5ca933f/Grounding%20DINO/GroundingDINO_with_Segment_Anything.ipynb
 
+    model: GroundingDinoModelKey = InputField(description="The Grounding DINO model to use.")
     prompt: str = InputField(description="The prompt describing the object to segment.")
     image: ImageField = InputField(description="The image to segment.")
     detection_threshold: float = InputField(
@@ -88,7 +94,7 @@ class GroundingDinoInvocation(BaseInvocation):
         labels = [label if label.endswith(".") else label + "." for label in labels]
 
         with context.models.load_remote_model(
-            source=GROUNDING_DINO_MODEL_ID, loader=GroundingDinoInvocation._load_grounding_dino
+            source=GROUNDING_DINO_MODEL_IDS[self.model], loader=GroundingDinoInvocation._load_grounding_dino
         ) as detector:
             assert isinstance(detector, GroundingDinoPipeline)
             return detector.detect(image=image, candidate_labels=labels, threshold=threshold)
diff --git a/invokeai/app/invocations/segment_anything.py b/invokeai/app/invocations/segment_anything.py
index 6240dd6946..b49b1a39e3 100644
--- a/invokeai/app/invocations/segment_anything.py
+++ b/invokeai/app/invocations/segment_anything.py
@@ -15,7 +15,12 @@ from invokeai.app.services.shared.invocation_context import InvocationContext
 from invokeai.backend.image_util.segment_anything.mask_refinement import mask_to_polygon, polygon_to_mask
 from invokeai.backend.image_util.segment_anything.segment_anything_pipeline import SegmentAnythingPipeline
 
-SEGMENT_ANYTHING_MODEL_ID = "facebook/sam-vit-base"
+SegmentAnythingModelKey = Literal["segment-anything-base", "segment-anything-large", "segment-anything-huge"]
+SEGMENT_ANYTHING_MODEL_IDS: dict[SegmentAnythingModelKey, str] = {
+    "segment-anything-base": "facebook/sam-vit-base",
+    "segment-anything-large": "facebook/sam-vit-large",
+    "segment-anything-huge": "facebook/sam-vit-huge",
+}
 
 
 @invocation(
@@ -33,6 +38,7 @@ class SegmentAnythingInvocation(BaseInvocation):
     # - https://huggingface.co/docs/transformers/v4.43.3/en/model_doc/grounding-dino#grounded-sam
     # - https://github.com/NielsRogge/Transformers-Tutorials/blob/a39f33ac1557b02ebfb191ea7753e332b5ca933f/Grounding%20DINO/GroundingDINO_with_Segment_Anything.ipynb
 
+    model: SegmentAnythingModelKey = InputField(description="The Segment Anything model to use.")
     image: ImageField = InputField(description="The image to segment.")
     bounding_boxes: list[BoundingBoxField] = InputField(description="The bounding boxes to prompt the SAM model with.")
     apply_polygon_refinement: bool = InputField(
@@ -88,7 +94,7 @@ class SegmentAnythingInvocation(BaseInvocation):
 
         with (
             context.models.load_remote_model(
-                source=SEGMENT_ANYTHING_MODEL_ID, loader=SegmentAnythingInvocation._load_sam_model
+                source=SEGMENT_ANYTHING_MODEL_IDS[self.model], loader=SegmentAnythingInvocation._load_sam_model
             ) as sam_pipeline,
         ):
             assert isinstance(sam_pipeline, SegmentAnythingPipeline)