diff --git a/caikit_computer_vision/data_model/tasks.py b/caikit_computer_vision/data_model/tasks.py
index b6fdc17..91bfe3a 100644
--- a/caikit_computer_vision/data_model/tasks.py
+++ b/caikit_computer_vision/data_model/tasks.py
@@ -26,7 +26,7 @@
 from .image_classification import ImageClassificationResult
 from .image_segmentation import ImageSegmentationResult
 from .object_detection import ObjectDetectionResult
-from .text_to_image import TextToImageResult
+from .text_to_image import CaptionedImage
 
 
 # TODO - add support for image DM primitives
@@ -66,7 +66,7 @@ class ImageSegmentationTask(TaskBase):
 
 @task(
     required_parameters={"inputs": str},
-    output_type=TextToImageResult,
+    output_type=CaptionedImage,
 )
 class TextToImageTask(TaskBase):
     """The text to image task is responsible for taking an input text prompt, along with
diff --git a/caikit_computer_vision/data_model/text_to_image.py b/caikit_computer_vision/data_model/text_to_image.py
index dcd1c14..544b586 100644
--- a/caikit_computer_vision/data_model/text_to_image.py
+++ b/caikit_computer_vision/data_model/text_to_image.py
@@ -14,9 +14,6 @@
 """Data structures for text to image."""
 
 
-# Standard
-from typing import List
-
 # Third Party
 from py_to_proto.dataclass_to_proto import Annotated, FieldNumber
 
@@ -30,7 +27,7 @@
 
 
 @dataobject(package="caikit_data_model.caikit_computer_vision")
-class TextToImageResult(DataObjectBase):
-    # TODO: Align on the output format
+class CaptionedImage(DataObjectBase):
     output: Annotated[caikit_dm.Image, FieldNumber(1)]
-    producer_id: Annotated[ProducerId, FieldNumber(2)]
+    caption: Annotated[str, FieldNumber(2)]
+    producer_id: Annotated[ProducerId, FieldNumber(3)]
diff --git a/caikit_computer_vision/modules/text_to_image/tti_stub.py b/caikit_computer_vision/modules/text_to_image/tti_stub.py
index 098f278..cab805b 100644
--- a/caikit_computer_vision/modules/text_to_image/tti_stub.py
+++ b/caikit_computer_vision/modules/text_to_image/tti_stub.py
@@ -26,7 +26,7 @@
 import alog
 
 # Local
-from ...data_model import TextToImageResult
+from ...data_model import CaptionedImage
 from ...data_model.tasks import TextToImageTask
 
 log = alog.use_channel("TTI_STUB")
@@ -64,13 +64,14 @@ def save(self, model_path: str):
         with saver:
             saver.update_config({"model_name": self.model_name})
 
-    def run(self, inputs: str, height: int, width: int) -> TextToImageResult:
+    def run(self, inputs: str, height: int, width: int) -> CaptionedImage:
         """Generates an image matching the provided height and width."""
         log.debug("STUB - running text to image inference")
         r_channel = np.full((height, width), 0, dtype=np.uint8)
         g_channel = np.full((height, width), 100, dtype=np.uint8)
         b_channel = np.full((height, width), 200, dtype=np.uint8)
         img = np.stack((r_channel, g_channel, b_channel), axis=2)
-        return TextToImageResult(
+        return CaptionedImage(
             output=caikit_dm.Image(img),
+            caption=inputs,
         )
diff --git a/tests/modules/text_to_image/test_tti_stub.py b/tests/modules/text_to_image/test_tti_stub.py
index 0d62e64..4e4f7f5 100644
--- a/tests/modules/text_to_image/test_tti_stub.py
+++ b/tests/modules/text_to_image/test_tti_stub.py
@@ -29,6 +29,8 @@ def test_tti_stub():
 
     # Make sure we can run a fake inference on it
     pred = model.run("This is a prompt", height=500, width=550)
+    assert isinstance(pred, caikit_computer_vision.data_model.CaptionedImage)
+    assert pred.caption == "This is a prompt"
     pil_img = pred.output.as_pil()
     assert pil_img.width == 550
     assert pil_img.height == 500