diff --git a/docs/data/object_detectors_models.yaml b/docs/data/object_detectors_models.yaml
index 7ed95c07f5..87251d6bc4 100644
--- a/docs/data/object_detectors_models.yaml
+++ b/docs/data/object_detectors_models.yaml
@@ -1272,17 +1272,17 @@ axengine:
 axelera:
   title: Axelera Metis
   models:
-    - key: yolov8n
-      label: YOLOv8n
+    - key: yoloxs
+      label: YOLOX-S
       recommended: true
       download: |-
-        The **yolov8n-coco** model is a Voyager SDK model-zoo preset, so no download or compilation is needed. To use a custom model, compile your ONNX model with the SDK compiler (`axcompile`) or build from the model zoo (`axzoo build yolov8n_coco --backend axrelay --cal-source repr`), then point `model.path` at the compiled model or its URL (e.g. hosted on Hugging Face).
+        The **yolox-s-coco** model is a Voyager SDK model-zoo preset (Megvii YOLOX, Apache-2.0 licensed), so no download or compilation is needed. To use a custom model, compile your ONNX model with the SDK compiler (`axcompile`) or build from the model zoo (`axzoo build yolox_s_coco --backend axrelay --cal-source repr`), then point `model.path` at the compiled model or its URL (e.g. hosted on Hugging Face).
       ui: |-
         Navigate to **Settings > System > Detectors and model** and select **Axelera Metis NPU** from the detector type dropdown and click **Add**. Then on the same page, in the **Custom Model** tab, configure:
 
         | Field                                    | Value                   |
         | ---------------------------------------- | ----------------------- |
-        | **Custom object detector model path**    | `yolov8n-coco`          |
+        | **Custom object detector model path**    | `yolox-s-coco`           |
         | **Label map for custom object detector** | `/labelmap/coco-80.txt` |
         | **Object detection model input width**   | `640`                   |
         | **Object detection model input height**  | `640`                   |
@@ -1296,7 +1296,7 @@ axelera:
             type: axelera
 
         model:
-          path: yolov8n-coco
+          path: yolox-s-coco
           model_type: yolo-generic
           width: 640
           height: 640
diff --git a/docs/docs/configuration/object_detectors.md b/docs/docs/configuration/object_detectors.md
index f2ca936a2f..83c74ff4fd 100644
--- a/docs/docs/configuration/object_detectors.md
+++ b/docs/docs/configuration/object_detectors.md
@@ -797,7 +797,7 @@ See the [installation docs](../frigate/installation.md#axelera-metis) for inform
 
 ### Configuration {#configuration-axelera}
 
-The integration runs inference through a single stream created with `create_inference_stream(network=...)`, which accepts a compiled model as a URL (downloaded into the model cache), a local file path, or an SDK model-zoo preset name. When no model is specified, the compiled default model is downloaded from Hugging Face into the model cache on first startup; the SDK model-zoo preset `yolox-s-coco` can be selected explicitly with `model.path: yolox-s-coco`.
+The integration runs inference through a single stream created with `create_inference_stream(network=...)`, which accepts a compiled model as a URL (downloaded into the model cache), a local file path, or an SDK model-zoo preset name. When no model is specified, the SDK model-zoo preset `yolox-s-coco` is used (no download); it can also be selected explicitly with `model.path: yolox-s-coco`.
 
 <ModelConfigDropdown detectorTitle="Axelera Metis" models={objectDetectorsModels.axelera.models} />