diff --git a/machine-learning/app/main.py b/machine-learning/app/main.py
index 49436977bf..e59d0d8382 100644
--- a/machine-learning/app/main.py
+++ b/machine-learning/app/main.py
@@ -27,13 +27,10 @@ app = FastAPI()
 @app.on_event("startup")
 async def startup_event() -> None:
     app.state.model_cache = ModelCache(ttl=settings.model_ttl, revalidate=True)
-    same_clip = settings.clip_image_model == settings.clip_text_model
-    app.state.clip_vision_type = ModelType.CLIP if same_clip else ModelType.CLIP_VISION
-    app.state.clip_text_type = ModelType.CLIP if same_clip else ModelType.CLIP_TEXT
     models = [
         (settings.classification_model, ModelType.IMAGE_CLASSIFICATION),
-        (settings.clip_image_model, app.state.clip_vision_type),
-        (settings.clip_text_model, app.state.clip_text_type),
+        (settings.clip_image_model, ModelType.CLIP),
+        (settings.clip_text_model, ModelType.CLIP),
         (settings.facial_recognition_model, ModelType.FACIAL_RECOGNITION),
     ]
 
@@ -87,9 +84,7 @@ async def image_classification(
 async def clip_encode_image(
     image: Image.Image = Depends(dep_pil_image),
 ) -> list[float]:
-    model = await app.state.model_cache.get(
-        settings.clip_image_model, app.state.clip_vision_type
-    )
+    model = await app.state.model_cache.get(settings.clip_image_model, ModelType.CLIP)
     embedding = model.predict(image)
     return embedding
 
@@ -100,9 +95,7 @@ async def clip_encode_image(
     status_code=200,
 )
 async def clip_encode_text(payload: TextModelRequest) -> list[float]:
-    model = await app.state.model_cache.get(
-        settings.clip_text_model, app.state.clip_text_type
-    )
+    model = await app.state.model_cache.get(settings.clip_text_model, ModelType.CLIP)
     embedding = model.predict(payload.text)
     return embedding
 
diff --git a/machine-learning/app/models/__init__.py b/machine-learning/app/models/__init__.py
index b646135053..e5b5aa7599 100644
--- a/machine-learning/app/models/__init__.py
+++ b/machine-learning/app/models/__init__.py
@@ -1,3 +1,3 @@
-from .clip import CLIPSTTextEncoder, CLIPSTVisionEncoder
+from .clip import CLIPSTEncoder
 from .facial_recognition import FaceRecognizer
 from .image_classification import ImageClassifier
diff --git a/machine-learning/app/models/base.py b/machine-learning/app/models/base.py
index 122f3627e6..0ef3173ce8 100644
--- a/machine-learning/app/models/base.py
+++ b/machine-learning/app/models/base.py
@@ -1,6 +1,6 @@
 from __future__ import annotations
 
-from abc import abstractmethod, ABC
+from abc import ABC, abstractmethod
 from pathlib import Path
 from typing import Any
 
diff --git a/machine-learning/app/models/clip.py b/machine-learning/app/models/clip.py
index 51731f790e..9e55b28d57 100644
--- a/machine-learning/app/models/clip.py
+++ b/machine-learning/app/models/clip.py
@@ -25,13 +25,3 @@ class CLIPSTEncoder(InferenceModel):
 
     def predict(self, image_or_text: Image | str) -> list[float]:
         return self.model.encode(image_or_text).tolist()
-
-
-# stubs to allow different behavior between the two in the future
-# and handle loading different image and text clip models
-class CLIPSTVisionEncoder(CLIPSTEncoder):
-    _model_type = ModelType.CLIP_VISION
-
-
-class CLIPSTTextEncoder(CLIPSTEncoder):
-    _model_type = ModelType.CLIP_TEXT
diff --git a/machine-learning/app/schemas.py b/machine-learning/app/schemas.py
index db6b7b50bc..16618faa68 100644
--- a/machine-learning/app/schemas.py
+++ b/machine-learning/app/schemas.py
@@ -61,6 +61,4 @@ class FaceResponse(BaseModel):
 class ModelType(Enum):
     IMAGE_CLASSIFICATION = "image-classification"
     CLIP = "clip"
-    CLIP_VISION = "clip-vision"
-    CLIP_TEXT = "clip-text"
     FACIAL_RECOGNITION = "facial-recognition"