diff --git a/docker/support/tensorrt_detector/rootfs/etc/s6-rc.d/trt-model-prepare/run b/docker/support/tensorrt_detector/rootfs/etc/s6-rc.d/trt-model-prepare/run
index 0656b126b..0db10b25e 100755
--- a/docker/support/tensorrt_detector/rootfs/etc/s6-rc.d/trt-model-prepare/run
+++ b/docker/support/tensorrt_detector/rootfs/etc/s6-rc.d/trt-model-prepare/run
@@ -4,7 +4,7 @@
 
 set -o errexit -o nounset -o pipefail
 
-OUTPUT_FOLDER?=/media/frigate/model_cache/tensorrt
+OUTPUT_FOLDER?=/config/model_cache/tensorrt
 
 # Create output folder
 mkdir -p ${OUTPUT_FOLDER}
diff --git a/docs/docs/configuration/detectors.md b/docs/docs/configuration/detectors.md
index f91a0ae13..b6291124b 100644
--- a/docs/docs/configuration/detectors.md
+++ b/docs/docs/configuration/detectors.md
@@ -192,7 +192,7 @@ There are improved capabilities in newer GPU architectures that TensorRT can ben
 
 The model used for TensorRT must be preprocessed on the same hardware platform that they will run on. This means that each user must run additional setup to generate a model file for the TensorRT library. A script is included that will build several common models.
 
-The Frigate image will generate model files during startup if the specified model is not found.  Processed models are stored in the `/media/frigate/model_cache` folder.  Typically the `/media/frigate` path is mapped to a directory on the host already and the `model_cache` does not need to be mapped separately unless the user wants to store it in a different location on the host.
+The Frigate image will generate model files during startup if the specified model is not found.  Processed models are stored in the `/config/model_cache` folder.  Typically the `/config` path is mapped to a directory on the host already and the `model_cache` does not need to be mapped separately unless the user wants to store it in a different location on the host.
 
 To by default, the `yolov7-tiny-416` model will be generated, but this can be overridden by specifying the `YOLO_MODELS` environment variable in Docker.  One or more models may be listed in a comma-separated format, and each one will be generated.  To select no model generation, set the variable to an empty string, `YOLO_MODELS=""`.  Models will only be generated if the corresponding `{model}.trt` file is not present in the `model_cache` folder, so you can force a model to be regenerated by deleting it from your Frigate data folder.
 
@@ -241,7 +241,7 @@ frigate:
 
 The TensorRT detector can be selected by specifying `tensorrt` as the model type. The GPU will need to be passed through to the docker container using the same methods described in the [Hardware Acceleration](hardware_acceleration.md#nvidia-gpu) section. If you pass through multiple GPUs, you can select which GPU is used for a detector with the `device` configuration parameter. The `device` parameter is an integer value of the GPU index, as shown by `nvidia-smi` within the container.
 
-The TensorRT detector uses `.trt` model files that are located in `/media/frigate/model_cache/tensorrt` by default. These model path and dimensions used will depend on which model you have generated.
+The TensorRT detector uses `.trt` model files that are located in `/config/model_cache/tensorrt` by default. These model path and dimensions used will depend on which model you have generated.
 
 ```yaml
 detectors:
@@ -250,7 +250,7 @@ detectors:
     device: 0 #This is the default, select the first GPU
 
 model:
-  path: /media/frigate/model_cache/tensorrt/yolov7-tiny-416.trt
+  path: /config/model_cache/tensorrt/yolov7-tiny-416.trt
   input_tensor: nchw
   input_pixel_format: rgb
   width: 416