diff --git a/docs/docs/configuration/face_recognition.md b/docs/docs/configuration/face_recognition.md
index af6fd1eff..88749159f 100644
--- a/docs/docs/configuration/face_recognition.md
+++ b/docs/docs/configuration/face_recognition.md
@@ -23,14 +23,14 @@ Frigate needs to first detect a `face` before it can recognize a face.
 
 Frigate has support for two face recognition model types:
 
-- **small**: Frigate will use CV2 Local Binary Pattern Face Recognizer to recognize faces, which runs locally on the CPU. This model is optimized for efficiency and is not as accurate.
-- **large**: Frigate will run a face embedding model, this model is optimized for accuracy. It is only recommended to be run when an integrated or dedicated GPU is available.
+- **small**: Frigate will run a small FaceNet embedding model, which runs locally on the CPU. This model is optimized for efficiency and is not as accurate.
+- **large**: Frigate will run a large ArcFace embedding model, this model is optimized for accuracy. It is only recommended to be run when an integrated or dedicated GPU is available.
 
 In both cases a lightweight face landmark detection model is also used to align faces before running the recognition model.
 
 ## Minimum System Requirements
 
-The `small` model is optimized for efficiency and runs on the CPU, there are no significantly different system requirements.
+The `small` model is optimized for efficiency and runs on the CPU, there are no significantly different system requirements, though users on ultra efficient systems may see CPU spikes.
 The `large` model is optimized for accuracy and an integrated or discrete GPU is highly recommended.
 
 ## Configuration
diff --git a/web/public/locales/en/views/settings.json b/web/public/locales/en/views/settings.json
index ffb2434ff..5b404b173 100644
--- a/web/public/locales/en/views/settings.json
+++ b/web/public/locales/en/views/settings.json
@@ -113,11 +113,11 @@
         "desc": "The size of the model used for face recognition.",
         "small": {
           "title": "small",
-          "desc": "Using <em>small</em> employs a Local Binary Pattern Histogram model via OpenCV that runs efficiently on most CPUs."
+          "desc": "Using <em>small</em> employs a FaceNet face embedding that runs efficiently on most CPUs."
         },
         "large": {
           "title": "large",
-          "desc": "Using <em>large</em> employs an ArcFace Face embedding model and will automatically run on the GPU if applicable."
+          "desc": "Using <em>large</em> employs an ArcFace face embedding model and will automatically run on the GPU if applicable."
         }
       }
     },