diff --git a/modules/doc/content/getting_started/installation/install_libtorch.md b/modules/doc/content/getting_started/installation/install_libtorch.md
index 132ca7bb1a08..9afd9a0edacc 100644
--- a/modules/doc/content/getting_started/installation/install_libtorch.md
+++ b/modules/doc/content/getting_started/installation/install_libtorch.md
@@ -4,7 +4,11 @@ The way one enables LibTorch [!cite](paszke2019pytorch) capabilities in MOOSE de
 the operating system (Linux or Mac) and if we use HPC or just a local workstation.
 
 !alert! note
-Before we review the main approaches, it is important to emphasize that
+Before trying to install MOOSE with libtorch make sure to check out the [compatibility matrix]
+(https://github.com/pytorch/pytorch/blob/main/RELEASE.md#release-compatibility-matrix)
+which will tell you if the required packages are compatible with the ones required by MOOSE.
+
+Furthermore, it is important to emphasize that
 linking MOOSE with libtorch on +Linux machines+ is not supported if the compiler stack has been built
 using a `libc` version below 2.27 (for `libtorch v 1.8+`)
 or 2.23 (for `libtorch v1.4-1.8`). Furthermore, we do not support `libtorch` versions below
@@ -27,11 +31,10 @@ The user can choose from three alternatives when it comes to installing `libtorc
 
 - +Install using conda:+
 
-  For ARM and Intel Mac workstations the user can install libtorch using conda together
-  with the MOOSE packages:
+  For ARM and Intel Mac workstations the user can install libtorch using conda within the `moose` environment:
 
   ```bash
-  conda create -n moose-torch moose-dev pytorch
+  conda install pytorch
   ```
 
   This will provide the headers and libraries needed to use libtorch.
@@ -39,7 +42,7 @@ The user can choose from three alternatives when it comes to installing `libtorc
   !alert! note
 
   The same process works for Linux workstations if the user requires CPU support only.
-  For notes on the GPU support, navigate to the bottom of this site.
+  For notes on the GPU support, [click here](gpu-notes).
 
   !alert-end!
 
@@ -51,7 +54,7 @@ The user can choose from three alternatives when it comes to installing `libtorc
   ./scripts/setup_libtorch.sh
   ```
 
-  which downloads `libtorch` from the official site and sets it up in the `framework\contrib`
+  which downloads `libtorch` from the official site and sets it up in the `framework/contrib`
   directory.
 
   !alert! note
@@ -71,7 +74,7 @@ The user can choose from three alternatives when it comes to installing `libtorc
   ```
 
   Note that we do not support `libtorch` below a version of 1.4. The default
-  version downloaded by the script is 1.10.
+  version downloaded by the script is 2.1.
 
   !alert-end!
 
@@ -107,16 +110,20 @@ by the `setup_libtorch.sh` script.
 For conda-based installations the user can link to the conda-based libtorch libraries
 using the approach above (using a typical installation path within conda):
 
-
-./configure --with-libtorch=/yourcondadirector/mambaforge3/envs/moose-torch/lib/python3.10/site-packages/torch
-
 ```bash
-./configure --with-libtorch=${CONDA_PREFIX}/lib/python3.10/site-packages/torch
+./configure --with-libtorch=${CONDA_PREFIX}/lib/python[!package!minimum_python]/site-packages/torch
 ```
 
 !alert! note
+
 The python version can be different depending on the distribution, so make sure you double-check if
 the directory you point to actually exists!
+An easy way to find if the library exists within the conda package is running the following command in the terminal:
+
+```bash
+find ${CONDA_PREFIX} -type d -name torch
+```
+
 !alert-end!
 
 ## Build MOOSE with libtorch
@@ -137,7 +144,7 @@ serves as a good example on how to achieve this for applications.
 
 !alert-end!
 
-## GPU Support
+## GPU Support id=gpu-notes
 
 When using ARM Macs the conda-based installation supports both CPU and GPU devices.
 For GPU acceleration through Metal, users need to select MPS as a device when writing source code.