diff --git a/docsrc/index.rst b/docsrc/index.rst
index 1c0c9a0d9e..946407433c 100644
--- a/docsrc/index.rst
+++ b/docsrc/index.rst
@@ -110,6 +110,7 @@ Tutorials
tutorials/_rendered_examples/dynamo/torch_compile_resnet_example
tutorials/_rendered_examples/dynamo/torch_compile_transformers_example
tutorials/_rendered_examples/dynamo/torch_compile_advanced_usage
+ tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion
Python API Documenation
------------------------
@@ -206,4 +207,4 @@ Legacy Further Information (TorchScript)
* `GTC 2021 Fall Talk `_
* `PyTorch Ecosystem Day 2021 `_
* `PyTorch Developer Conference 2021 `_
-* `PyTorch Developer Conference 2022 `_
\ No newline at end of file
+* `PyTorch Developer Conference 2022 `_
diff --git a/docsrc/tutorials/images/majestic_castle.png b/docsrc/tutorials/images/majestic_castle.png
new file mode 100644
index 0000000000..bac6073a90
Binary files /dev/null and b/docsrc/tutorials/images/majestic_castle.png differ
diff --git a/examples/dynamo/README.rst b/examples/dynamo/README.rst
index fa863952e7..d895cc0113 100644
--- a/examples/dynamo/README.rst
+++ b/examples/dynamo/README.rst
@@ -9,3 +9,4 @@ a number of ways you can leverage this backend to accelerate inference.
* :ref:`torch_compile_resnet`: Compiling a ResNet model using the Torch Compile Frontend for ``torch_tensorrt.compile``
* :ref:`torch_compile_transformer`: Compiling a Transformer model using ``torch.compile``
* :ref:`torch_compile_advanced_usage`: Advanced usage including making a custom backend to use directly with the ``torch.compile`` API
+* :ref:`torch_compile_stable_diffusion`: Compiling a Stable Diffusion model using ``torch.compile``
diff --git a/examples/dynamo/torch_compile_stable_diffusion.py b/examples/dynamo/torch_compile_stable_diffusion.py
new file mode 100644
index 0000000000..0511e5a363
--- /dev/null
+++ b/examples/dynamo/torch_compile_stable_diffusion.py
@@ -0,0 +1,55 @@
+"""
+.. _torch_compile_stable_diffusion:
+
+Torch Compile Stable Diffusion
+======================================================
+
+This interactive script is intended as a sample of the Torch-TensorRT workflow with `torch.compile` on a Stable Diffusion model. A sample output is featured below:
+
+.. image:: /tutorials/images/majestic_castle.png
+ :width: 512px
+ :height: 512px
+ :scale: 50 %
+ :align: right
+"""
+
+# %%
+# Imports and Model Definition
+# ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+import torch
+from diffusers import DiffusionPipeline
+
+import torch_tensorrt
+
+model_id = "CompVis/stable-diffusion-v1-4"
+device = "cuda:0"
+
+# Instantiate Stable Diffusion Pipeline with FP16 weights
+pipe = DiffusionPipeline.from_pretrained(
+ model_id, revision="fp16", torch_dtype=torch.float16
+)
+pipe = pipe.to(device)
+
+backend = "torch_tensorrt"
+
+# Optimize the UNet portion with Torch-TensorRT
+pipe.unet = torch.compile(
+ pipe.unet,
+ backend=backend,
+ options={
+ "truncate_long_and_double": True,
+ "precision": torch.float16,
+ },
+ dynamic=False,
+)
+
+# %%
+# Inference
+# ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+prompt = "a majestic castle in the clouds"
+image = pipe(prompt).images[0]
+
+image.save("images/majestic_castle.png")
+image.show()