diff --git a/README.md b/README.md
index 8b0e6f09d1c..b5d8078a128 100644
--- a/README.md
+++ b/README.md
@@ -44,7 +44,7 @@
 | [Mistral-7B-decode](./models/demos/wormhole/mistral7b)      |  33rd              | 32                   | 10.9 t/s/u - 349 t/s         | 13.3 t/s/u - 426 t/s        | 21 t/s/u       |
 | [Mamba-2.8B-decode](./models/demos/mamba)                   |  any               | 32                   | 9.2 t/s/u -  295 t/s         | 13.1 t/s/u - 419 t/s        | 22 t/s/u       |
 | [BERT-Large](./models/demos/metal_BERT_large_11/) (sen/s)   | any                |  8                   | 270                          | 340                         | 400            |
-| Stable Diffusion 1.4 512x512                                | coming soon        | 1                    |                              |                             |                |
+| Stable Diffusion 1.4 512x512  (seconds for denoise)                              |          | 1                    |      114s                        |    0.2s                         |                |
 
 [3] - Generating the i'th token in a sequence while the kv_cache is filled with i-1 rows.
 
diff --git a/models/demos/wormhole/stable_diffusion/README.md b/models/demos/wormhole/stable_diffusion/README.md
new file mode 100644
index 00000000000..25f90d513c4
--- /dev/null
+++ b/models/demos/wormhole/stable_diffusion/README.md
@@ -0,0 +1,32 @@
+# Stable_diffusion Model
+
+## Introduction
+Stable Diffusion is a latent text-to-image diffusion model capable of generating photo-realistic images given any text input.
+
+# Details
+The entry point to  functional_stable_diffusion model is UNet2DConditionModel in `models/demos/wormhole/stable_diffusion/tt2/ttnn_functional_unet_2d_condition_model.py`. The model picks up certain configs and weights from huggingface pretrained model. We have used `CompVis/stable-diffusion-v1-4` version from huggingface as our reference.
+
+# Inputs
+Inputs by default are provided from `input_data.json`. If you wish to change the inputs, provide a different path to test_demo.We do not recommend modifying `input_data.json` file.
+
+## How to Run
+
+To run the demo, make sure to build the project, activate the environment, and set the appropriate environment variables.
+For more information, refer [installation and build guide](https://github.com/tenstorrent/tt-metal/blob/main/INSTALLING.md).
+
+Use `pytest --disable-warnings --input-path="models/demos/wormhole/stable_diffusion/demo/input_data.json" models/demos/wormhole/stable_diffusion/demo/demo.py::test_demo` to run the demo.
+
+If you wish to run the demo with a different input use `pytest --disable-warnings --input-path="<address_to_your_json_file.json>" models/demos/wormhole/stable_diffusion/demo/demo.py::test_demo`
+
+Our second demo is designed to run poloclub/diffusiondb dataset, run this with `pytest --disable-warnings models/demos/wormhole/stable_diffusion/demo/demo.py::test_demo_diffusiondb`.
+
+If you wish to run for `num_prompts` samples and `num_inference_steps` denoising steps, use `pytest --disable-warnings models/demos/wormhole/stable_diffusion/demo/demo.py::test_demo_diffusiondb[<num_prompts>-<num_inference_steps>]`
+
+Note: ttnn stable diffusion utilizes `PNDMScheduler` and requires `num_inference_steps to be greater than or equal to 4`. [Reference](https://arxiv.org/pdf/2202.09778)
+
+# Metrics  Interpretation
+`FID Score (Fréchet Inception Distance)` evaluates the quality of generated images by measuring the similarity between their feature distributions and those of real images. A lower FID score indicates better similarity between generated and real images.
+For more information, refer [FID Score](https://lightning.ai/docs/torchmetrics/stable/image/frechet_inception_distance.html).
+
+`CLIP Score` measures the similarity between the generated images and the input prompts. Higher CLIP scores indicate better alignment between the generated images and the provided text prompts.
+For more information, refer [CLIP Score](https://lightning.ai/docs/torchmetrics/stable/multimodal/clip_score.html).
diff --git a/models/experimental/functional_stable_diffusion/custom_preprocessing.py b/models/demos/wormhole/stable_diffusion/custom_preprocessing.py
similarity index 100%
rename from models/experimental/functional_stable_diffusion/custom_preprocessing.py
rename to models/demos/wormhole/stable_diffusion/custom_preprocessing.py
diff --git a/models/experimental/functional_stable_diffusion/demo/demo.py b/models/demos/wormhole/stable_diffusion/demo/demo.py
similarity index 76%
rename from models/experimental/functional_stable_diffusion/demo/demo.py
rename to models/demos/wormhole/stable_diffusion/demo/demo.py
index bad67bd12c1..f904d581e7e 100644
--- a/models/experimental/functional_stable_diffusion/demo/demo.py
+++ b/models/demos/wormhole/stable_diffusion/demo/demo.py
@@ -11,24 +11,21 @@
 from loguru import logger
 from tqdm.auto import tqdm
 from datasets import load_dataset
-import os
 
 from transformers import CLIPTextModel, CLIPTokenizer
 from diffusers import (
     AutoencoderKL,
     UNet2DConditionModel,
 )
-from models.utility_functions import (
-    skip_for_grayskull,
-)
+from models.utility_functions import skip_for_grayskull
 from models.utility_functions import (
     enable_persistent_kernel_cache,
     disable_persistent_kernel_cache,
 )
 from ttnn.model_preprocessing import preprocess_model_parameters
-from models.experimental.functional_stable_diffusion.sd_pndm_scheduler import TtPNDMScheduler
-from models.experimental.functional_stable_diffusion.custom_preprocessing import custom_preprocessor
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_unet_2d_condition_model import (
+from models.demos.wormhole.stable_diffusion.sd_pndm_scheduler import TtPNDMScheduler
+from models.demos.wormhole.stable_diffusion.custom_preprocessing import custom_preprocessor
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_unet_2d_condition_model import (
     UNet2DConditionModel as UNet2D,
 )
 
@@ -65,8 +62,6 @@ def tt_guide(noise_pred, guidance_scale):  # will return latents
             noise_pred.shape[3] - 1,
         ],
     )
-
-    # noise_pred_uncond, noise_pred_text = ttnn.split(noise_pred, noise_pred.shape[0] // 2, dim=0)
     noise_pred = noise_pred_uncond + guidance_scale * (noise_pred_text - noise_pred_uncond)
     return noise_pred
 
@@ -108,6 +103,9 @@ def preprocess_images(image_paths):
 def run_demo_inference(device, reset_seeds, input_path, num_prompts, num_inference_steps, image_size=(256, 256)):
     disable_persistent_kernel_cache()
 
+    assert (
+        num_inference_steps >= 4
+    ), f"PNDMScheduler only supports num_inference_steps >= 4. Found num_inference_steps={num_inference_steps}"
     # 1. Load the autoencoder model which will be used to decode the latents into image space.
     vae = AutoencoderKL.from_pretrained("CompVis/stable-diffusion-v1-4", subfolder="vae")
 
@@ -247,93 +245,49 @@ def run_demo_inference_diffusiondb(
     device, reset_seeds, input_path, num_prompts, num_inference_steps, image_size=(256, 256)
 ):
     disable_persistent_kernel_cache()
-    device.enable_program_cache()
 
+    assert (
+        num_inference_steps >= 4
+    ), f"PNDMScheduler only supports num_inference_steps >= 4. Found num_inference_steps={num_inference_steps}"
     # 0. Load a sample prompt from the dataset
     dataset = load_dataset("poloclub/diffusiondb", "2m_random_1k")
     data_1k = dataset["train"]
 
     height, width = image_size
 
-    torch_device = "cpu"
-    # 1. Load the autoencoder model which will be used to decode the latents into image space.
-    vae = AutoencoderKL.from_pretrained("CompVis/stable-diffusion-v1-4", subfolder="vae")
-    vae.to(torch_device)
-    vae_scale_factor = 2 ** (len(vae.config.block_out_channels) - 1)
-
-    # 2. Load the tokenizer and text encoder to tokenize and encode the text.
-    tokenizer = CLIPTokenizer.from_pretrained("openai/clip-vit-large-patch14")
-    text_encoder = CLIPTextModel.from_pretrained("openai/clip-vit-large-patch14")
-
-    # 3. The UNet model for generating the latents.
-    unet = UNet2DConditionModel.from_pretrained("CompVis/stable-diffusion-v1-4", subfolder="unet")
-
-    # 4. load the K-LMS scheduler with some fitting parameters.
-    ttnn_scheduler = TtPNDMScheduler(
-        beta_start=0.00085, beta_end=0.012, beta_schedule="scaled_linear", num_train_timesteps=1000, device=device
-    )
-
-    text_encoder.to(torch_device)
-    unet.to(torch_device)
-
-    config = unet.config
-    parameters = preprocess_model_parameters(
-        initialize_model=lambda: unet, custom_preprocessor=custom_preprocessor, device=device
-    )
-    input_height = 64
-    input_width = 64
-    reader_patterns_cache = {} if height == 512 and width == 512 else None
-    model = UNet2D(device, parameters, 2, input_height, input_width, reader_patterns_cache)
-
-    guidance_scale = 7.5  # Scale for classifier-free guidance
-    generator = torch.manual_seed(174)  # 10233 Seed generator to create the inital latent noise
-    batch_size = 1
+    for i in range(num_prompts):
+        experiment_name = f"diffusiondb_{i}__{height}x{width}"
+        input_prompt = [f"{data_1k['prompt'][i]}"]
+        logger.info(f"input_prompts: {input_prompt}")
 
-    # Initial random noise
-    latents = torch.randn(
-        (batch_size, unet.config.in_channels, height // vae_scale_factor, width // vae_scale_factor),
-        generator=generator,
-    )
-    latents = latents.to(torch_device)
+        image = np.array(data_1k["image"][i])
+        ref_images = Image.fromarray(image)
+        ref_img_path = f"{experiment_name}_ref.png"
+        ref_images.save(ref_img_path)
 
-    ttnn_scheduler.set_timesteps(num_inference_steps)
+        # 1. Load the autoencoder model which will be used to decode the latents into image space.
+        vae = AutoencoderKL.from_pretrained("CompVis/stable-diffusion-v1-4", subfolder="vae")
 
-    latents = latents * ttnn_scheduler.init_noise_sigma
-    rand_latents = torch.tensor(latents)
-    rand_latents = ttnn.from_torch(rand_latents, dtype=ttnn.bfloat16, layout=ttnn.TILE_LAYOUT, device=device)
+        # 2. Load the tokenizer and text encoder to tokenize and encode the text.
+        tokenizer = CLIPTokenizer.from_pretrained("openai/clip-vit-large-patch14")
+        text_encoder = CLIPTextModel.from_pretrained("openai/clip-vit-large-patch14")
 
-    # ttnn_latents = ttnn.from_torch(ttnn_latents, dtype=ttnn.bfloat16, device=device, layout=ttnn.TILE_LAYOUT)
-    ttnn_latent_model_input = ttnn.concat([rand_latents, rand_latents], dim=0)
-    _tlist = []
-    for t in ttnn_scheduler.timesteps:
-        _t = constant_prop_time_embeddings(t, ttnn_latent_model_input, unet.time_proj)
-        _t = _t.unsqueeze(0).unsqueeze(0)
-        _t = _t.permute(2, 0, 1, 3)  # pre-permute temb
-        _t = ttnn.from_torch(_t, dtype=ttnn.bfloat16, layout=ttnn.TILE_LAYOUT, device=device)
-        _tlist.append(_t)
+        # 3. The UNet model for generating the latents.
+        unet = UNet2DConditionModel.from_pretrained("CompVis/stable-diffusion-v1-4", subfolder="unet")
 
-    time_step = ttnn_scheduler.timesteps.tolist()
+        # 4. load the K-LMS scheduler with some fitting parameters.
+        ttnn_scheduler = TtPNDMScheduler(
+            beta_start=0.00085, beta_end=0.012, beta_schedule="scaled_linear", num_train_timesteps=1000, device=device
+        )
 
-    interactive = os.environ.get("INTERACTIVE_SD_DEMO", "0") == "1"
-    i = 0
-    while i < num_prompts:
-        ttnn_scheduler.set_timesteps(num_inference_steps)
-        if interactive:
-            print("Enter the input promt, or q to exit:")
-            input_prompt = [input()]
-            if input_prompt[0] == "q":
-                break
-        else:
-            input_prompt = [f"{data_1k['prompt'][i]}"]
-
-            image = np.array(data_1k["image"][i])
-            ref_images = Image.fromarray(image)
-            ref_img_path = f"{experiment_name}_ref.png"
-            ref_images.save(ref_img_path)
-            i = i + 1
+        torch_device = "cpu"
+        vae.to(torch_device)
+        text_encoder.to(torch_device)
+        unet.to(torch_device)
 
-        experiment_name = f"diffusiondb_{i}__{height}x{width}"
-        logger.info(f"input_prompts: {input_prompt}")
+        guidance_scale = 7.5  # Scale for classifier-free guidance
+        generator = torch.manual_seed(174)  # 10233 Seed generator to create the inital latent noise
+        batch_size = len(input_prompt)
 
         ## First, we get the text_embeddings for the prompt. These embeddings will be used to condition the UNet model.
         # Tokenizer and Text Encoder
@@ -357,10 +311,44 @@ def run_demo_inference_diffusiondb(
         ttnn_text_embeddings = ttnn.from_torch(
             ttnn_text_embeddings, dtype=ttnn.bfloat16, layout=ttnn.TILE_LAYOUT, device=device
         )
+
+        vae_scale_factor = 2 ** (len(vae.config.block_out_channels) - 1)
+        # Initial random noise
+        latents = torch.randn(
+            (batch_size, unet.config.in_channels, height // vae_scale_factor, width // vae_scale_factor),
+            generator=generator,
+        )
+        latents = latents.to(torch_device)
+
+        ttnn_scheduler.set_timesteps(num_inference_steps)
+
+        latents = latents * ttnn_scheduler.init_noise_sigma
+        ttnn_latents = torch.tensor(latents)
+        ttnn_latents = ttnn.from_torch(ttnn_latents, dtype=ttnn.bfloat16, layout=ttnn.TILE_LAYOUT, device=device)
+
+        config = unet.config
+        parameters = preprocess_model_parameters(
+            initialize_model=lambda: unet, custom_preprocessor=custom_preprocessor, device=device
+        )
+        input_height = 64
+        input_width = 64
+        reader_patterns_cache = {} if height == 512 and width == 512 else None
+        # ttnn_latents = ttnn.from_torch(ttnn_latents, dtype=ttnn.bfloat16, device=device, layout=ttnn.TILE_LAYOUT)
+        ttnn_latent_model_input = ttnn.concat([ttnn_latents, ttnn_latents], dim=0)
+        _tlist = []
+        for t in ttnn_scheduler.timesteps:
+            _t = constant_prop_time_embeddings(t, ttnn_latent_model_input, unet.time_proj)
+            _t = _t.unsqueeze(0).unsqueeze(0)
+            _t = _t.permute(2, 0, 1, 3)  # pre-permute temb
+            _t = ttnn.from_torch(_t, dtype=ttnn.bfloat16, layout=ttnn.TILE_LAYOUT, device=device)
+            _tlist.append(_t)
+
+        time_step = ttnn_scheduler.timesteps.tolist()
+
+        model = UNet2D(device, parameters, 2, input_height, input_width, reader_patterns_cache)
         iter = 0
-        ttnn_latents = rand_latents
         # # Denoising loop
-        for index in tqdm(range(len(time_step))):
+        for index in range(len(time_step)):
             # expand the latents if we are doing classifier-free guidance to avoid doing two forward passes.
             ttnn_latent_model_input = ttnn.concat([ttnn_latents, ttnn_latents], dim=0)
             _t = _tlist[index]
@@ -377,12 +365,12 @@ def run_demo_inference_diffusiondb(
                     return_dict=True,
                     config=config,
                 )
+            print(f"Sample: {iter}")
 
             # perform guidance
             noise_pred = tt_guide(ttnn_output, guidance_scale)
             ttnn_latents = ttnn_scheduler.step(noise_pred, t, ttnn_latents).prev_sample
-            if not interactive:
-                _save_image_and_latents(ttnn_latents, iter, vae, pre_fix=f"{experiment_name}_tt", pre_fix2="")
+            _save_image_and_latents(ttnn_latents, iter, vae, pre_fix=f"{experiment_name}_tt", pre_fix2="")
 
             iter += 1
             enable_persistent_kernel_cache()
@@ -401,15 +389,15 @@ def run_demo_inference_diffusiondb(
         ttnn_output_path = f"{experiment_name}_ttnn.png"
         pil_images.save(ttnn_output_path)
 
+        ref_paths = [ref_img_path, ref_img_path]
         ttnn_paths = [ttnn_output_path, ttnn_output_path]
+
+        ref_images = preprocess_images(ref_paths)
         ttnn_images = preprocess_images(ttnn_paths)
-        if not interactive:
-            ref_paths = [ref_img_path, ref_img_path]
-            ref_images = preprocess_images(ref_paths)
 
-            # Calculate FID scores
-            fid_score_ref_ttnn = calculate_fid_score(ref_images, ttnn_images)
-            logger.info(f"FID Score (Reference vs TTNN): {fid_score_ref_ttnn}")
+        # Calculate FID scores
+        fid_score_ref_ttnn = calculate_fid_score(ref_images, ttnn_images)
+        logger.info(f"FID Score (Reference vs TTNN): {fid_score_ref_ttnn}")
 
         # calculate Clip score
         clip_score = CLIPScore(model_name_or_path="openai/clip-vit-base-patch16")
@@ -420,13 +408,14 @@ def run_demo_inference_diffusiondb(
 
 
 @skip_for_grayskull()
+@pytest.mark.parametrize("device_l1_small_size", [32768], indirect=True)
 @pytest.mark.parametrize(
     "num_prompts",
     ((1),),
 )
 @pytest.mark.parametrize(
     "num_inference_steps",
-    ((2),),
+    ((4),),
 )
 @pytest.mark.parametrize(
     "image_size",
@@ -444,7 +433,7 @@ def test_demo(device, reset_seeds, input_path, num_prompts, num_inference_steps,
 )
 @pytest.mark.parametrize(
     "num_inference_steps",
-    ((30),),
+    ((4),),
 )
 @pytest.mark.parametrize(
     "image_size",
diff --git a/models/experimental/functional_stable_diffusion/demo/input_data.json b/models/demos/wormhole/stable_diffusion/demo/input_data.json
similarity index 100%
rename from models/experimental/functional_stable_diffusion/demo/input_data.json
rename to models/demos/wormhole/stable_diffusion/demo/input_data.json
diff --git a/models/experimental/functional_stable_diffusion/sd_helper_funcs.py b/models/demos/wormhole/stable_diffusion/sd_helper_funcs.py
similarity index 100%
rename from models/experimental/functional_stable_diffusion/sd_helper_funcs.py
rename to models/demos/wormhole/stable_diffusion/sd_helper_funcs.py
diff --git a/models/experimental/functional_stable_diffusion/sd_pndm_scheduler.py b/models/demos/wormhole/stable_diffusion/sd_pndm_scheduler.py
similarity index 100%
rename from models/experimental/functional_stable_diffusion/sd_pndm_scheduler.py
rename to models/demos/wormhole/stable_diffusion/sd_pndm_scheduler.py
diff --git a/models/experimental/functional_stable_diffusion/tt/ttnn_functional_basic_transformer_block.py b/models/demos/wormhole/stable_diffusion/tt/ttnn_functional_basic_transformer_block.py
similarity index 94%
rename from models/experimental/functional_stable_diffusion/tt/ttnn_functional_basic_transformer_block.py
rename to models/demos/wormhole/stable_diffusion/tt/ttnn_functional_basic_transformer_block.py
index e7d612dfdb4..027df72fbf3 100644
--- a/models/experimental/functional_stable_diffusion/tt/ttnn_functional_basic_transformer_block.py
+++ b/models/demos/wormhole/stable_diffusion/tt/ttnn_functional_basic_transformer_block.py
@@ -3,8 +3,8 @@
 # SPDX-License-Identifier: Apache-2.0
 
 import ttnn
-from models.experimental.functional_stable_diffusion.tt.ttnn_functional_cross_attention import cross_attention
-from models.experimental.functional_stable_diffusion.tt.ttnn_functional_feedforward import feedforward
+from models.demos.wormhole.stable_diffusion.tt.ttnn_functional_cross_attention import cross_attention
+from models.demos.wormhole.stable_diffusion.tt.ttnn_functional_feedforward import feedforward
 
 
 def basic_transformer_block(
diff --git a/models/experimental/functional_stable_diffusion/tt/ttnn_functional_cross_attention.py b/models/demos/wormhole/stable_diffusion/tt/ttnn_functional_cross_attention.py
similarity index 100%
rename from models/experimental/functional_stable_diffusion/tt/ttnn_functional_cross_attention.py
rename to models/demos/wormhole/stable_diffusion/tt/ttnn_functional_cross_attention.py
diff --git a/models/experimental/functional_stable_diffusion/tt/ttnn_functional_cross_attention_down_block_2d.py b/models/demos/wormhole/stable_diffusion/tt/ttnn_functional_cross_attention_down_block_2d.py
similarity index 90%
rename from models/experimental/functional_stable_diffusion/tt/ttnn_functional_cross_attention_down_block_2d.py
rename to models/demos/wormhole/stable_diffusion/tt/ttnn_functional_cross_attention_down_block_2d.py
index 7b3d6cee0e4..f4ab72a3130 100644
--- a/models/experimental/functional_stable_diffusion/tt/ttnn_functional_cross_attention_down_block_2d.py
+++ b/models/demos/wormhole/stable_diffusion/tt/ttnn_functional_cross_attention_down_block_2d.py
@@ -3,9 +3,9 @@
 # SPDX-License-Identifier: Apache-2.0
 
 import ttnn
-from models.experimental.functional_stable_diffusion.tt.ttnn_functional_resnetblock2d import resnetBlock2D
-from models.experimental.functional_stable_diffusion.tt.ttnn_functional_transformer_2d import transformer_2d_model
-from models.experimental.functional_stable_diffusion.tt.ttnn_functional_downsample_2d import downsample_2d
+from models.demos.wormhole.stable_diffusion.tt.ttnn_functional_resnetblock2d import resnetBlock2D
+from models.demos.wormhole.stable_diffusion.tt.ttnn_functional_transformer_2d import transformer_2d_model
+from models.demos.wormhole.stable_diffusion.tt.ttnn_functional_downsample_2d import downsample_2d
 
 
 def cross_attention_down_block_2d(
diff --git a/models/experimental/functional_stable_diffusion/tt/ttnn_functional_cross_attn_upblock.py b/models/demos/wormhole/stable_diffusion/tt/ttnn_functional_cross_attn_upblock.py
similarity index 92%
rename from models/experimental/functional_stable_diffusion/tt/ttnn_functional_cross_attn_upblock.py
rename to models/demos/wormhole/stable_diffusion/tt/ttnn_functional_cross_attn_upblock.py
index 7334014f772..1bacb05a2f9 100644
--- a/models/experimental/functional_stable_diffusion/tt/ttnn_functional_cross_attn_upblock.py
+++ b/models/demos/wormhole/stable_diffusion/tt/ttnn_functional_cross_attn_upblock.py
@@ -5,9 +5,9 @@
 import torch
 import ttnn
 from typing import Optional, Dict
-from models.experimental.functional_stable_diffusion.tt.ttnn_functional_upsample_2d import upsample2d
-from models.experimental.functional_stable_diffusion.tt.ttnn_functional_resnetblock2d import resnetBlock2D
-from models.experimental.functional_stable_diffusion.tt.ttnn_functional_transformer_2d import transformer_2d_model
+from models.demos.wormhole.stable_diffusion.tt.ttnn_functional_upsample_2d import upsample2d
+from models.demos.wormhole.stable_diffusion.tt.ttnn_functional_resnetblock2d import resnetBlock2D
+from models.demos.wormhole.stable_diffusion.tt.ttnn_functional_transformer_2d import transformer_2d_model
 
 
 def torch_to_ttnn(input, device, layout=ttnn.TILE_LAYOUT):
diff --git a/models/experimental/functional_stable_diffusion/tt/ttnn_functional_downblock_2d.py b/models/demos/wormhole/stable_diffusion/tt/ttnn_functional_downblock_2d.py
similarity index 91%
rename from models/experimental/functional_stable_diffusion/tt/ttnn_functional_downblock_2d.py
rename to models/demos/wormhole/stable_diffusion/tt/ttnn_functional_downblock_2d.py
index 49d76f5002b..626a25efd68 100644
--- a/models/experimental/functional_stable_diffusion/tt/ttnn_functional_downblock_2d.py
+++ b/models/demos/wormhole/stable_diffusion/tt/ttnn_functional_downblock_2d.py
@@ -5,8 +5,8 @@
 import ttnn
 import torch
 from typing import Optional
-from models.experimental.functional_stable_diffusion.tt.ttnn_functional_resnetblock2d import resnetBlock2D
-from models.experimental.functional_stable_diffusion.tt.ttnn_functional_downsample_2d import downsample_2d
+from models.demos.wormhole.stable_diffusion.tt.ttnn_functional_resnetblock2d import resnetBlock2D
+from models.demos.wormhole.stable_diffusion.tt.ttnn_functional_downsample_2d import downsample_2d
 
 
 def downblock2d(
diff --git a/models/experimental/functional_stable_diffusion/tt/ttnn_functional_downsample_2d.py b/models/demos/wormhole/stable_diffusion/tt/ttnn_functional_downsample_2d.py
similarity index 98%
rename from models/experimental/functional_stable_diffusion/tt/ttnn_functional_downsample_2d.py
rename to models/demos/wormhole/stable_diffusion/tt/ttnn_functional_downsample_2d.py
index cb3c1037bf1..79f75783ba3 100644
--- a/models/experimental/functional_stable_diffusion/tt/ttnn_functional_downsample_2d.py
+++ b/models/demos/wormhole/stable_diffusion/tt/ttnn_functional_downsample_2d.py
@@ -9,7 +9,7 @@
 import torch.nn as nn
 from tt_lib.fallback_ops import fallback_ops
 from models.utility_functions import torch_to_tt_tensor_rm, tt_to_torch_tensor
-from models.experimental.functional_stable_diffusion.tt.ttnn_functional_utility_functions import (
+from models.demos.wormhole.stable_diffusion.tt.ttnn_functional_utility_functions import (
     run_ttnn_conv_with_pre_and_post_tensor_formatting,
 )
 import math
diff --git a/models/experimental/functional_stable_diffusion/tt/ttnn_functional_embeddings.py b/models/demos/wormhole/stable_diffusion/tt/ttnn_functional_embeddings.py
similarity index 100%
rename from models/experimental/functional_stable_diffusion/tt/ttnn_functional_embeddings.py
rename to models/demos/wormhole/stable_diffusion/tt/ttnn_functional_embeddings.py
diff --git a/models/experimental/functional_stable_diffusion/tt/ttnn_functional_feedforward.py b/models/demos/wormhole/stable_diffusion/tt/ttnn_functional_feedforward.py
similarity index 80%
rename from models/experimental/functional_stable_diffusion/tt/ttnn_functional_feedforward.py
rename to models/demos/wormhole/stable_diffusion/tt/ttnn_functional_feedforward.py
index b98c8ee19ce..dd7f492d470 100644
--- a/models/experimental/functional_stable_diffusion/tt/ttnn_functional_feedforward.py
+++ b/models/demos/wormhole/stable_diffusion/tt/ttnn_functional_feedforward.py
@@ -3,7 +3,7 @@
 # SPDX-License-Identifier: Apache-2.0
 
 import ttnn
-from models.experimental.functional_stable_diffusion.tt.ttnn_functional_geglu import geglu
+from models.demos.wormhole.stable_diffusion.tt.ttnn_functional_geglu import geglu
 
 
 def feedforward(config, hidden_states, parameters, device=None):
diff --git a/models/experimental/functional_stable_diffusion/tt/ttnn_functional_geglu.py b/models/demos/wormhole/stable_diffusion/tt/ttnn_functional_geglu.py
similarity index 100%
rename from models/experimental/functional_stable_diffusion/tt/ttnn_functional_geglu.py
rename to models/demos/wormhole/stable_diffusion/tt/ttnn_functional_geglu.py
diff --git a/models/experimental/functional_stable_diffusion/tt/ttnn_functional_resnetblock2d.py b/models/demos/wormhole/stable_diffusion/tt/ttnn_functional_resnetblock2d.py
similarity index 99%
rename from models/experimental/functional_stable_diffusion/tt/ttnn_functional_resnetblock2d.py
rename to models/demos/wormhole/stable_diffusion/tt/ttnn_functional_resnetblock2d.py
index 1cd667ab5e4..3bc86323f03 100644
--- a/models/experimental/functional_stable_diffusion/tt/ttnn_functional_resnetblock2d.py
+++ b/models/demos/wormhole/stable_diffusion/tt/ttnn_functional_resnetblock2d.py
@@ -6,7 +6,7 @@
 
 import torch
 from typing import Optional, Dict
-from models.experimental.functional_stable_diffusion.tt.ttnn_functional_utility_functions import (
+from models.demos.wormhole.stable_diffusion.tt.ttnn_functional_utility_functions import (
     run_ttnn_conv_with_pre_and_post_tensor_formatting,
     pre_process_input,
     post_process_output,
diff --git a/models/experimental/functional_stable_diffusion/tt/ttnn_functional_transformer_2d.py b/models/demos/wormhole/stable_diffusion/tt/ttnn_functional_transformer_2d.py
similarity index 98%
rename from models/experimental/functional_stable_diffusion/tt/ttnn_functional_transformer_2d.py
rename to models/demos/wormhole/stable_diffusion/tt/ttnn_functional_transformer_2d.py
index b65b066dac6..a33ca84059c 100644
--- a/models/experimental/functional_stable_diffusion/tt/ttnn_functional_transformer_2d.py
+++ b/models/demos/wormhole/stable_diffusion/tt/ttnn_functional_transformer_2d.py
@@ -8,10 +8,10 @@
 
 from tt_lib.fallback_ops import fallback_ops
 from models.utility_functions import torch_to_tt_tensor_rm, tt_to_torch_tensor
-from models.experimental.functional_stable_diffusion.tt.ttnn_functional_basic_transformer_block import (
+from models.demos.wormhole.stable_diffusion.tt.ttnn_functional_basic_transformer_block import (
     basic_transformer_block,
 )
-from models.experimental.functional_stable_diffusion.tt.ttnn_functional_utility_functions import (
+from models.demos.wormhole.stable_diffusion.tt.ttnn_functional_utility_functions import (
     run_ttnn_conv_with_pre_and_post_tensor_formatting,
     post_process_output,
 )
diff --git a/models/experimental/functional_stable_diffusion/tt/ttnn_functional_unet_2d_condition_model.py b/models/demos/wormhole/stable_diffusion/tt/ttnn_functional_unet_2d_condition_model.py
similarity index 96%
rename from models/experimental/functional_stable_diffusion/tt/ttnn_functional_unet_2d_condition_model.py
rename to models/demos/wormhole/stable_diffusion/tt/ttnn_functional_unet_2d_condition_model.py
index ecbe8786d05..375b20f474f 100644
--- a/models/experimental/functional_stable_diffusion/tt/ttnn_functional_unet_2d_condition_model.py
+++ b/models/demos/wormhole/stable_diffusion/tt/ttnn_functional_unet_2d_condition_model.py
@@ -16,19 +16,19 @@
 from tt_lib.fallback_ops import fallback_ops
 from models.utility_functions import is_grayskull
 
-from models.experimental.functional_stable_diffusion.tt.ttnn_functional_embeddings import TtTimestepEmbedding
-from models.experimental.functional_stable_diffusion.tt.ttnn_functional_unet_mid_block_2d_cross_attn import (
+from models.demos.wormhole.stable_diffusion.tt.ttnn_functional_embeddings import TtTimestepEmbedding
+from models.demos.wormhole.stable_diffusion.tt.ttnn_functional_unet_mid_block_2d_cross_attn import (
     unet_mid_block_2d_cross_attn,
 )
-from models.experimental.functional_stable_diffusion.tt.ttnn_functional_cross_attention_down_block_2d import (
+from models.demos.wormhole.stable_diffusion.tt.ttnn_functional_cross_attention_down_block_2d import (
     cross_attention_down_block_2d,
 )
-from models.experimental.functional_stable_diffusion.tt.ttnn_functional_cross_attn_upblock import (
+from models.demos.wormhole.stable_diffusion.tt.ttnn_functional_cross_attn_upblock import (
     cross_attention_upblock2d,
 )
-from models.experimental.functional_stable_diffusion.tt.ttnn_functional_downblock_2d import downblock2d
-from models.experimental.functional_stable_diffusion.tt.ttnn_functional_upblock_2d import upblock_2d
-from models.experimental.functional_stable_diffusion.tt.ttnn_functional_utility_functions import (
+from models.demos.wormhole.stable_diffusion.tt.ttnn_functional_downblock_2d import downblock2d
+from models.demos.wormhole.stable_diffusion.tt.ttnn_functional_upblock_2d import upblock_2d
+from models.demos.wormhole.stable_diffusion.tt.ttnn_functional_utility_functions import (
     run_ttnn_conv_with_pre_and_post_tensor_formatting,
 )
 
diff --git a/models/experimental/functional_stable_diffusion/tt/ttnn_functional_unet_mid_block_2d_cross_attn.py b/models/demos/wormhole/stable_diffusion/tt/ttnn_functional_unet_mid_block_2d_cross_attn.py
similarity index 93%
rename from models/experimental/functional_stable_diffusion/tt/ttnn_functional_unet_mid_block_2d_cross_attn.py
rename to models/demos/wormhole/stable_diffusion/tt/ttnn_functional_unet_mid_block_2d_cross_attn.py
index 671e7f36815..fc762f5adbb 100644
--- a/models/experimental/functional_stable_diffusion/tt/ttnn_functional_unet_mid_block_2d_cross_attn.py
+++ b/models/demos/wormhole/stable_diffusion/tt/ttnn_functional_unet_mid_block_2d_cross_attn.py
@@ -2,8 +2,8 @@
 
 # SPDX-License-Identifier: Apache-2.0
 
-from models.experimental.functional_stable_diffusion.tt.ttnn_functional_resnetblock2d import resnetBlock2D
-from models.experimental.functional_stable_diffusion.tt.ttnn_functional_transformer_2d import transformer_2d_model
+from models.demos.wormhole.stable_diffusion.tt.ttnn_functional_resnetblock2d import resnetBlock2D
+from models.demos.wormhole.stable_diffusion.tt.ttnn_functional_transformer_2d import transformer_2d_model
 
 
 def unet_mid_block_2d_cross_attn(
diff --git a/models/experimental/functional_stable_diffusion/tt/ttnn_functional_upblock_2d.py b/models/demos/wormhole/stable_diffusion/tt/ttnn_functional_upblock_2d.py
similarity index 91%
rename from models/experimental/functional_stable_diffusion/tt/ttnn_functional_upblock_2d.py
rename to models/demos/wormhole/stable_diffusion/tt/ttnn_functional_upblock_2d.py
index ba0ec8e8a98..b32f7184e46 100644
--- a/models/experimental/functional_stable_diffusion/tt/ttnn_functional_upblock_2d.py
+++ b/models/demos/wormhole/stable_diffusion/tt/ttnn_functional_upblock_2d.py
@@ -5,8 +5,8 @@
 import torch
 import ttnn
 
-from models.experimental.functional_stable_diffusion.tt.ttnn_functional_resnetblock2d import resnetBlock2D
-from models.experimental.functional_stable_diffusion.tt.ttnn_functional_upsample_2d import upsample2d
+from models.demos.wormhole.stable_diffusion.tt.ttnn_functional_resnetblock2d import resnetBlock2D
+from models.demos.wormhole.stable_diffusion.tt.ttnn_functional_upsample_2d import upsample2d
 
 
 def upblock_2d(
diff --git a/models/experimental/functional_stable_diffusion/tt/ttnn_functional_upsample_2d.py b/models/demos/wormhole/stable_diffusion/tt/ttnn_functional_upsample_2d.py
similarity index 94%
rename from models/experimental/functional_stable_diffusion/tt/ttnn_functional_upsample_2d.py
rename to models/demos/wormhole/stable_diffusion/tt/ttnn_functional_upsample_2d.py
index 4b3cab44569..20e4a16d3fa 100644
--- a/models/experimental/functional_stable_diffusion/tt/ttnn_functional_upsample_2d.py
+++ b/models/demos/wormhole/stable_diffusion/tt/ttnn_functional_upsample_2d.py
@@ -10,9 +10,9 @@
     tt_to_torch_tensor,
 )
 
-from models.experimental.functional_stable_diffusion.tt.ttnn_functional_upsample_nearest_2d import upsample_nearest2d
+from models.demos.wormhole.stable_diffusion.tt.ttnn_functional_upsample_nearest_2d import upsample_nearest2d
 from tt_lib.fallback_ops import fallback_ops
-from models.experimental.functional_stable_diffusion.tt.ttnn_functional_utility_functions import (
+from models.demos.wormhole.stable_diffusion.tt.ttnn_functional_utility_functions import (
     run_ttnn_conv_with_pre_and_post_tensor_formatting,
 )
 
diff --git a/models/experimental/functional_stable_diffusion/tt/ttnn_functional_upsample_nearest_2d.py b/models/demos/wormhole/stable_diffusion/tt/ttnn_functional_upsample_nearest_2d.py
similarity index 100%
rename from models/experimental/functional_stable_diffusion/tt/ttnn_functional_upsample_nearest_2d.py
rename to models/demos/wormhole/stable_diffusion/tt/ttnn_functional_upsample_nearest_2d.py
diff --git a/models/experimental/functional_stable_diffusion/tt/ttnn_functional_utility_functions.py b/models/demos/wormhole/stable_diffusion/tt/ttnn_functional_utility_functions.py
similarity index 100%
rename from models/experimental/functional_stable_diffusion/tt/ttnn_functional_utility_functions.py
rename to models/demos/wormhole/stable_diffusion/tt/ttnn_functional_utility_functions.py
diff --git a/models/experimental/functional_stable_diffusion/tt2/ttnn_functional_basic_transformer_block.py b/models/demos/wormhole/stable_diffusion/tt2/ttnn_functional_basic_transformer_block.py
similarity index 97%
rename from models/experimental/functional_stable_diffusion/tt2/ttnn_functional_basic_transformer_block.py
rename to models/demos/wormhole/stable_diffusion/tt2/ttnn_functional_basic_transformer_block.py
index ccb00791766..7182dabff5c 100644
--- a/models/experimental/functional_stable_diffusion/tt2/ttnn_functional_basic_transformer_block.py
+++ b/models/demos/wormhole/stable_diffusion/tt2/ttnn_functional_basic_transformer_block.py
@@ -4,8 +4,8 @@
 
 import ttnn
 import tt_lib as ttl
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_cross_attention import cross_attention
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_feedforward import feedforward
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_cross_attention import cross_attention
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_feedforward import feedforward
 import torch
 
 
diff --git a/models/experimental/functional_stable_diffusion/tt2/ttnn_functional_cross_attention.py b/models/demos/wormhole/stable_diffusion/tt2/ttnn_functional_cross_attention.py
similarity index 99%
rename from models/experimental/functional_stable_diffusion/tt2/ttnn_functional_cross_attention.py
rename to models/demos/wormhole/stable_diffusion/tt2/ttnn_functional_cross_attention.py
index 6553ee81949..e5c5a2ca40f 100644
--- a/models/experimental/functional_stable_diffusion/tt2/ttnn_functional_cross_attention.py
+++ b/models/demos/wormhole/stable_diffusion/tt2/ttnn_functional_cross_attention.py
@@ -8,7 +8,7 @@
 import os
 import tt_lib as ttl
 from ttnn.operations.core import squeeze, unsqueeze_to_4D
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_utility_functions import (
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_utility_functions import (
     is_tile_dim_alligned,
     round_up_to_tile_dim,
     dealloc_input,
diff --git a/models/experimental/functional_stable_diffusion/tt2/ttnn_functional_cross_attention_down_block_2d.py b/models/demos/wormhole/stable_diffusion/tt2/ttnn_functional_cross_attention_down_block_2d.py
similarity index 92%
rename from models/experimental/functional_stable_diffusion/tt2/ttnn_functional_cross_attention_down_block_2d.py
rename to models/demos/wormhole/stable_diffusion/tt2/ttnn_functional_cross_attention_down_block_2d.py
index 7a5601c4449..cf38db7cdf5 100644
--- a/models/experimental/functional_stable_diffusion/tt2/ttnn_functional_cross_attention_down_block_2d.py
+++ b/models/demos/wormhole/stable_diffusion/tt2/ttnn_functional_cross_attention_down_block_2d.py
@@ -3,9 +3,9 @@
 # SPDX-License-Identifier: Apache-2.0
 
 import ttnn
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_resnetblock2d import resnetBlock2D
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_transformer_2d import transformer_2d_model
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_downsample_2d import downsample_2d
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_resnetblock2d import resnetBlock2D
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_transformer_2d import transformer_2d_model
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_downsample_2d import downsample_2d
 
 
 class cross_attention_down_block_2d:
diff --git a/models/experimental/functional_stable_diffusion/tt2/ttnn_functional_cross_attn_upblock.py b/models/demos/wormhole/stable_diffusion/tt2/ttnn_functional_cross_attn_upblock.py
similarity index 94%
rename from models/experimental/functional_stable_diffusion/tt2/ttnn_functional_cross_attn_upblock.py
rename to models/demos/wormhole/stable_diffusion/tt2/ttnn_functional_cross_attn_upblock.py
index 9ed707664a5..47e3c9406a7 100644
--- a/models/experimental/functional_stable_diffusion/tt2/ttnn_functional_cross_attn_upblock.py
+++ b/models/demos/wormhole/stable_diffusion/tt2/ttnn_functional_cross_attn_upblock.py
@@ -5,10 +5,10 @@
 import torch
 import ttnn
 from typing import Optional, Dict
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_upsample_2d import upsample2d
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_resnetblock2d import resnetBlock2D
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_transformer_2d import transformer_2d_model
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_utility_functions import dealloc_input
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_upsample_2d import upsample2d
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_resnetblock2d import resnetBlock2D
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_transformer_2d import transformer_2d_model
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_utility_functions import dealloc_input
 
 
 def torch_to_ttnn(input, device, layout=ttnn.TILE_LAYOUT):
diff --git a/models/experimental/functional_stable_diffusion/tt2/ttnn_functional_downblock_2d.py b/models/demos/wormhole/stable_diffusion/tt2/ttnn_functional_downblock_2d.py
similarity index 93%
rename from models/experimental/functional_stable_diffusion/tt2/ttnn_functional_downblock_2d.py
rename to models/demos/wormhole/stable_diffusion/tt2/ttnn_functional_downblock_2d.py
index 180f9c1171c..57077af2da9 100644
--- a/models/experimental/functional_stable_diffusion/tt2/ttnn_functional_downblock_2d.py
+++ b/models/demos/wormhole/stable_diffusion/tt2/ttnn_functional_downblock_2d.py
@@ -5,8 +5,8 @@
 import ttnn
 import torch
 from typing import Optional
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_resnetblock2d import resnetBlock2D
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_downsample_2d import downsample_2d
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_resnetblock2d import resnetBlock2D
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_downsample_2d import downsample_2d
 
 
 class downblock2d:
diff --git a/models/experimental/functional_stable_diffusion/tt2/ttnn_functional_downsample_2d.py b/models/demos/wormhole/stable_diffusion/tt2/ttnn_functional_downsample_2d.py
similarity index 97%
rename from models/experimental/functional_stable_diffusion/tt2/ttnn_functional_downsample_2d.py
rename to models/demos/wormhole/stable_diffusion/tt2/ttnn_functional_downsample_2d.py
index ebfbd2e424c..cc7fbccc6b0 100644
--- a/models/experimental/functional_stable_diffusion/tt2/ttnn_functional_downsample_2d.py
+++ b/models/demos/wormhole/stable_diffusion/tt2/ttnn_functional_downsample_2d.py
@@ -9,7 +9,7 @@
 import torch.nn as nn
 from tt_lib.fallback_ops import fallback_ops
 from models.utility_functions import torch_to_tt_tensor_rm, tt_to_torch_tensor
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_utility_functions import (
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_utility_functions import (
     run_ttnn_conv_with_pre_and_post_tensor_formatting,
 )
 import math
diff --git a/models/experimental/functional_stable_diffusion/tt2/ttnn_functional_embeddings.py b/models/demos/wormhole/stable_diffusion/tt2/ttnn_functional_embeddings.py
similarity index 100%
rename from models/experimental/functional_stable_diffusion/tt2/ttnn_functional_embeddings.py
rename to models/demos/wormhole/stable_diffusion/tt2/ttnn_functional_embeddings.py
diff --git a/models/experimental/functional_stable_diffusion/tt2/ttnn_functional_feedforward.py b/models/demos/wormhole/stable_diffusion/tt2/ttnn_functional_feedforward.py
similarity index 95%
rename from models/experimental/functional_stable_diffusion/tt2/ttnn_functional_feedforward.py
rename to models/demos/wormhole/stable_diffusion/tt2/ttnn_functional_feedforward.py
index f9c3fda3174..0d3ae6d714f 100644
--- a/models/experimental/functional_stable_diffusion/tt2/ttnn_functional_feedforward.py
+++ b/models/demos/wormhole/stable_diffusion/tt2/ttnn_functional_feedforward.py
@@ -3,8 +3,8 @@
 # SPDX-License-Identifier: Apache-2.0
 
 import ttnn
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_geglu import geglu
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_utility_functions import (
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_geglu import geglu
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_utility_functions import (
     determine_largest_subblock_size,
 )
 import tt_lib as ttl
diff --git a/models/experimental/functional_stable_diffusion/tt2/ttnn_functional_geglu.py b/models/demos/wormhole/stable_diffusion/tt2/ttnn_functional_geglu.py
similarity index 98%
rename from models/experimental/functional_stable_diffusion/tt2/ttnn_functional_geglu.py
rename to models/demos/wormhole/stable_diffusion/tt2/ttnn_functional_geglu.py
index b95bde681d2..6995053123f 100644
--- a/models/experimental/functional_stable_diffusion/tt2/ttnn_functional_geglu.py
+++ b/models/demos/wormhole/stable_diffusion/tt2/ttnn_functional_geglu.py
@@ -6,7 +6,7 @@
 import torch
 import math
 import tt_lib as ttl
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_utility_functions import (
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_utility_functions import (
     determine_largest_subblock_size,
     determine_blocking,
 )
diff --git a/models/experimental/functional_stable_diffusion/tt2/ttnn_functional_resnetblock2d.py b/models/demos/wormhole/stable_diffusion/tt2/ttnn_functional_resnetblock2d.py
similarity index 99%
rename from models/experimental/functional_stable_diffusion/tt2/ttnn_functional_resnetblock2d.py
rename to models/demos/wormhole/stable_diffusion/tt2/ttnn_functional_resnetblock2d.py
index e06371061f2..f83114d256b 100644
--- a/models/experimental/functional_stable_diffusion/tt2/ttnn_functional_resnetblock2d.py
+++ b/models/demos/wormhole/stable_diffusion/tt2/ttnn_functional_resnetblock2d.py
@@ -12,7 +12,7 @@
 import os
 import torch
 from typing import Optional, Dict
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_utility_functions import (
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_utility_functions import (
     pre_process_input,
     post_process_output,
     permute_conv_parameters,
diff --git a/models/experimental/functional_stable_diffusion/tt2/ttnn_functional_resnetblock2d_new_conv.py b/models/demos/wormhole/stable_diffusion/tt2/ttnn_functional_resnetblock2d_new_conv.py
similarity index 99%
rename from models/experimental/functional_stable_diffusion/tt2/ttnn_functional_resnetblock2d_new_conv.py
rename to models/demos/wormhole/stable_diffusion/tt2/ttnn_functional_resnetblock2d_new_conv.py
index 198a69e0bc2..730711fb166 100644
--- a/models/experimental/functional_stable_diffusion/tt2/ttnn_functional_resnetblock2d_new_conv.py
+++ b/models/demos/wormhole/stable_diffusion/tt2/ttnn_functional_resnetblock2d_new_conv.py
@@ -12,14 +12,14 @@
 import os
 import torch
 from typing import Optional, Dict
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_utility_functions import (
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_utility_functions import (
     pre_process_input,
     post_process_output,
     permute_conv_parameters,
     weight_to_bfp8,
 )
 import time
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_utility_functions import conv_cache
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_utility_functions import conv_cache
 
 
 def torch_to_ttnn(input, device, layout=ttnn.TILE_LAYOUT):
diff --git a/models/experimental/functional_stable_diffusion/tt2/ttnn_functional_transformer_2d.py b/models/demos/wormhole/stable_diffusion/tt2/ttnn_functional_transformer_2d.py
similarity index 98%
rename from models/experimental/functional_stable_diffusion/tt2/ttnn_functional_transformer_2d.py
rename to models/demos/wormhole/stable_diffusion/tt2/ttnn_functional_transformer_2d.py
index c2de409cd34..704063da273 100644
--- a/models/experimental/functional_stable_diffusion/tt2/ttnn_functional_transformer_2d.py
+++ b/models/demos/wormhole/stable_diffusion/tt2/ttnn_functional_transformer_2d.py
@@ -9,10 +9,10 @@
 import os
 from tt_lib.fallback_ops import fallback_ops
 from models.utility_functions import torch_to_tt_tensor_rm, tt_to_torch_tensor
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_basic_transformer_block import (
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_basic_transformer_block import (
     basic_transformer_block,
 )
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_utility_functions import (
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_utility_functions import (
     pre_process_input,
     pad_group_norm_weight,
     permute_conv_parameters,
diff --git a/models/experimental/functional_stable_diffusion/tt2/ttnn_functional_unet_2d_condition_model.py b/models/demos/wormhole/stable_diffusion/tt2/ttnn_functional_unet_2d_condition_model.py
similarity index 97%
rename from models/experimental/functional_stable_diffusion/tt2/ttnn_functional_unet_2d_condition_model.py
rename to models/demos/wormhole/stable_diffusion/tt2/ttnn_functional_unet_2d_condition_model.py
index fef608fa980..3e92c26dc5b 100644
--- a/models/experimental/functional_stable_diffusion/tt2/ttnn_functional_unet_2d_condition_model.py
+++ b/models/demos/wormhole/stable_diffusion/tt2/ttnn_functional_unet_2d_condition_model.py
@@ -18,19 +18,19 @@
 from tt_lib.fallback_ops import fallback_ops
 from models.utility_functions import is_grayskull
 
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_embeddings import TtTimestepEmbedding
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_unet_mid_block_2d_cross_attn import (
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_embeddings import TtTimestepEmbedding
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_unet_mid_block_2d_cross_attn import (
     unet_mid_block_2d_cross_attn,
 )
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_cross_attention_down_block_2d import (
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_cross_attention_down_block_2d import (
     cross_attention_down_block_2d,
 )
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_cross_attn_upblock import (
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_cross_attn_upblock import (
     cross_attention_upblock2d,
 )
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_downblock_2d import downblock2d
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_upblock_2d import upblock_2d
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_utility_functions import (
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_downblock_2d import downblock2d
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_upblock_2d import upblock_2d
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_utility_functions import (
     pad_group_norm_weight,
     pre_process_input,
 )
diff --git a/models/experimental/functional_stable_diffusion/tt2/ttnn_functional_unet_mid_block_2d_cross_attn.py b/models/demos/wormhole/stable_diffusion/tt2/ttnn_functional_unet_mid_block_2d_cross_attn.py
similarity index 94%
rename from models/experimental/functional_stable_diffusion/tt2/ttnn_functional_unet_mid_block_2d_cross_attn.py
rename to models/demos/wormhole/stable_diffusion/tt2/ttnn_functional_unet_mid_block_2d_cross_attn.py
index 5c768ef2b1d..4ffa5038e10 100644
--- a/models/experimental/functional_stable_diffusion/tt2/ttnn_functional_unet_mid_block_2d_cross_attn.py
+++ b/models/demos/wormhole/stable_diffusion/tt2/ttnn_functional_unet_mid_block_2d_cross_attn.py
@@ -2,8 +2,8 @@
 
 # SPDX-License-Identifier: Apache-2.0
 
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_resnetblock2d import resnetBlock2D
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_transformer_2d import transformer_2d_model
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_resnetblock2d import resnetBlock2D
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_transformer_2d import transformer_2d_model
 
 
 class unet_mid_block_2d_cross_attn:
diff --git a/models/experimental/functional_stable_diffusion/tt2/ttnn_functional_upblock_2d.py b/models/demos/wormhole/stable_diffusion/tt2/ttnn_functional_upblock_2d.py
similarity index 95%
rename from models/experimental/functional_stable_diffusion/tt2/ttnn_functional_upblock_2d.py
rename to models/demos/wormhole/stable_diffusion/tt2/ttnn_functional_upblock_2d.py
index 5c4a168beec..e549828a35e 100644
--- a/models/experimental/functional_stable_diffusion/tt2/ttnn_functional_upblock_2d.py
+++ b/models/demos/wormhole/stable_diffusion/tt2/ttnn_functional_upblock_2d.py
@@ -5,8 +5,8 @@
 import torch
 import ttnn
 
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_resnetblock2d import resnetBlock2D
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_upsample_2d import upsample2d
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_resnetblock2d import resnetBlock2D
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_upsample_2d import upsample2d
 
 
 class upblock_2d:
diff --git a/models/experimental/functional_stable_diffusion/tt2/ttnn_functional_upsample_2d.py b/models/demos/wormhole/stable_diffusion/tt2/ttnn_functional_upsample_2d.py
similarity index 92%
rename from models/experimental/functional_stable_diffusion/tt2/ttnn_functional_upsample_2d.py
rename to models/demos/wormhole/stable_diffusion/tt2/ttnn_functional_upsample_2d.py
index f1dcb473c82..3f0ee9ed738 100644
--- a/models/experimental/functional_stable_diffusion/tt2/ttnn_functional_upsample_2d.py
+++ b/models/demos/wormhole/stable_diffusion/tt2/ttnn_functional_upsample_2d.py
@@ -10,12 +10,12 @@
     tt_to_torch_tensor,
 )
 
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_upsample_nearest_2d import upsample_nearest2d
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_upsample_nearest_2d import upsample_nearest2d
 from tt_lib.fallback_ops import fallback_ops
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_utility_functions import (
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_utility_functions import (
     run_ttnn_conv_with_pre_and_post_tensor_formatting,
 )
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_utility_functions import (
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_utility_functions import (
     permute_conv_parameters,
 )
 
diff --git a/models/experimental/functional_stable_diffusion/tt2/ttnn_functional_upsample_nearest_2d.py b/models/demos/wormhole/stable_diffusion/tt2/ttnn_functional_upsample_nearest_2d.py
similarity index 96%
rename from models/experimental/functional_stable_diffusion/tt2/ttnn_functional_upsample_nearest_2d.py
rename to models/demos/wormhole/stable_diffusion/tt2/ttnn_functional_upsample_nearest_2d.py
index 11fb8c23ca4..b73f0b97722 100644
--- a/models/experimental/functional_stable_diffusion/tt2/ttnn_functional_upsample_nearest_2d.py
+++ b/models/demos/wormhole/stable_diffusion/tt2/ttnn_functional_upsample_nearest_2d.py
@@ -7,7 +7,7 @@
 
 import math
 
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_utility_functions import reshard_to
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_utility_functions import reshard_to
 
 
 class upsample_nearest2d:
diff --git a/models/experimental/functional_stable_diffusion/tt2/ttnn_functional_utility_functions.py b/models/demos/wormhole/stable_diffusion/tt2/ttnn_functional_utility_functions.py
similarity index 100%
rename from models/experimental/functional_stable_diffusion/tt2/ttnn_functional_utility_functions.py
rename to models/demos/wormhole/stable_diffusion/tt2/ttnn_functional_utility_functions.py
diff --git a/models/experimental/functional_stable_diffusion/tt2_multiple_iteration.py b/models/demos/wormhole/stable_diffusion/tt2_multiple_iteration.py
similarity index 97%
rename from models/experimental/functional_stable_diffusion/tt2_multiple_iteration.py
rename to models/demos/wormhole/stable_diffusion/tt2_multiple_iteration.py
index 8482e83e5e1..f4eb958e7a5 100644
--- a/models/experimental/functional_stable_diffusion/tt2_multiple_iteration.py
+++ b/models/demos/wormhole/stable_diffusion/tt2_multiple_iteration.py
@@ -25,8 +25,8 @@
 )
 from models.utility_functions import skip_for_wormhole_b0
 from ttnn.model_preprocessing import preprocess_model_parameters
-from models.experimental.functional_stable_diffusion.custom_preprocessing import custom_preprocessor
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_unet_2d_condition_model import (
+from models.demos.wormhole.stable_diffusion.custom_preprocessing import custom_preprocessor
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_unet_2d_condition_model import (
     UNet2DConditionModel as UNet2D,
 )
 
diff --git a/models/experimental/functional_stable_diffusion/README.md b/models/experimental/functional_stable_diffusion/README.md
deleted file mode 100644
index ce76dccf772..00000000000
--- a/models/experimental/functional_stable_diffusion/README.md
+++ /dev/null
@@ -1,28 +0,0 @@
-## functional_stable_diffusion Demo
-## How to Run
-
-To run the demo, make sure to build the project, activate the environment, and set the appropriate environment variables.
-For more information, refer [installation and build guide](https://tenstorrent.github.io/tt-metal/latest/get_started/get_started.html#install-and-build).
-
-Use `pytest --disable-warnings --input-path="models/experimental/functional_stable_diffusion/demo/input_data.json" models/experimental/functional_stable_diffusion/demo/demo.py::test_demo` to run the demo.
-
-If you wish to run the demo with a different input use `pytest --disable-warnings --input-path="<address_to_your_json_file.json>" models/experimental/functional_stable_diffusion/demo/demo.py::test_demo`
-
-Our second demo is designed to run poloclub/diffusiondb dataset, run this with `pytest --disable-warnings models/experimental/functional_stable_diffusion/demo/demo.py::test_demo_diffusiondb`.
-
-If you wish to run for `num_prompts` samples and `num_inference_steps` denoising steps, use `pytest --disable-warnings models/experimental/functional_stable_diffusion/demo/demo.py::test_demo_diffusiondb[<num_prompts>-<num_inference_steps>]`
-
-# Inputs
-Inputs by default are provided from `input_data.json`. If you wish you to change the inputs, provide a different path to test_demo.
-
-We do not recommend modifying `input_data.json` file.
-
-# Details
-The entry point to  functional_stable_diffusion model is UNet2DConditionModel in `models/experimental/functional_stable_diffusion/tt/ttnn_functional_unet_2d_condition_model.py`. The model picks up certain configs and weights from huggingface pretrained model. We have used `CompVis/stable-diffusion-v1-4` version from huggingface as our reference.
-
-# Metrics  Interpretation
-`FID Score (Fréchet Inception Distance)` evaluates the quality of generated images by measuring the similarity between their feature distributions and those of real images. A lower FID score indicates better similarity between generated and real images.
-For more information, refer [FID Score](https://lightning.ai/docs/torchmetrics/stable/image/frechet_inception_distance.html).
-
-`CLIP Score` measures the similarity between the generated images and the input prompts. Higher CLIP scores indicate better alignment between the generated images and the provided text prompts.
-For more information, refer [CLIP Score](https://lightning.ai/docs/torchmetrics/stable/multimodal/clip_score.html).
diff --git a/models/experimental/functional_stable_diffusion/tests/test_perf_stable_diffusion.py b/tests/device_perf_tests/stable_diffusion/test_perf_stable_diffusion.py
similarity index 82%
rename from models/experimental/functional_stable_diffusion/tests/test_perf_stable_diffusion.py
rename to tests/device_perf_tests/stable_diffusion/test_perf_stable_diffusion.py
index 179908c72d8..52470af49fc 100644
--- a/models/experimental/functional_stable_diffusion/tests/test_perf_stable_diffusion.py
+++ b/tests/device_perf_tests/stable_diffusion/test_perf_stable_diffusion.py
@@ -30,9 +30,10 @@
 )
 from ttnn.model_preprocessing import preprocess_model_parameters
 from ttnn.operations.core import unsqueeze_to_4D
-from models.experimental.functional_stable_diffusion.sd_helper_funcs import TtLMSDiscreteScheduler
-from models.experimental.functional_stable_diffusion.custom_preprocessing import custom_preprocessor
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_unet_2d_condition_model import (
+from models.demos.wormhole.stable_diffusion.sd_pndm_scheduler import TtPNDMScheduler
+from models.demos.wormhole.stable_diffusion.sd_helper_funcs import TtLMSDiscreteScheduler
+from models.demos.wormhole.stable_diffusion.custom_preprocessing import custom_preprocessor
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_unet_2d_condition_model import (
     UNet2DConditionModel as UNet2D,
 )
 
@@ -52,9 +53,9 @@ def ttnn_to_torch(input):
     return input
 
 
-def constant_prop_time_embeddings(timesteps, batch_size, time_proj):
+def constant_prop_time_embeddings(timesteps, sample, time_proj):
     timesteps = timesteps[None]
-    timesteps = timesteps.expand(batch_size)
+    timesteps = timesteps.expand(sample.shape[0])
     t_emb = time_proj(timesteps)
     return t_emb
 
@@ -78,13 +79,16 @@ def unsqueeze_all_params_to_4d(params):
 @pytest.mark.parametrize(
     "batch_size, num_inference_steps, expected_compile_time, expected_inference_time",
     [
-        (2, 2, 3600, 0.28),  # Issue 7816 Inference time
+        (2, 4, 3600, 0.28),  # Issue 7816 Inference time
     ],
 )
 def test_stable_diffusion_perf(device, batch_size, num_inference_steps, expected_compile_time, expected_inference_time):
     device.enable_program_cache()
     # disable_persistent_kernel_cache()
 
+    assert (
+        num_inference_steps >= 4
+    ), f"PNDMScheduler only supports num_inference_steps >= 4. Found num_inference_steps={num_inference_steps}"
     # Clear global profiler state before starting measurements
     profiler.clear()
 
@@ -111,13 +115,10 @@ def test_stable_diffusion_perf(device, batch_size, num_inference_steps, expected
     config = model.config
 
     # setup scheduler
-    scheduler = LMSDiscreteScheduler(
-        beta_start=0.00085,
-        beta_end=0.012,
-        beta_schedule="scaled_linear",
-        num_train_timesteps=1000,
+    ttnn_scheduler = TtPNDMScheduler(
+        beta_start=0.00085, beta_end=0.012, beta_schedule="scaled_linear", num_train_timesteps=1000, device=device
     )
-    scheduler.set_timesteps(1)
+    ttnn_scheduler.set_timesteps(4)
 
     parameters = preprocess_model_parameters(
         model_name=model_name, initialize_model=lambda: model, custom_preprocessor=custom_preprocessor, device=device
@@ -135,21 +136,24 @@ def test_stable_diffusion_perf(device, batch_size, num_inference_steps, expected
 
     hidden_states_shape = [batch_size, in_channels, input_height, input_width]
 
-    input = torch.randn(hidden_states_shape)
-    timestep = [i for i in tqdm(scheduler.timesteps)][0]
-    ttnn_timestep = constant_prop_time_embeddings(timestep, batch_size, model.time_proj)
-    ttnn_timestep = ttnn_timestep.unsqueeze(0).unsqueeze(0)
+    input_pt = torch.randn(hidden_states_shape)
+
     encoder_hidden_states = torch.randn(encoder_hidden_states_shape)
 
-    torch_output = model(input, timestep=timestep, encoder_hidden_states=encoder_hidden_states.squeeze(0)).sample
-    input = ttnn.from_torch(input, ttnn.bfloat16)
+    input = ttnn.from_torch(input_pt, ttnn.bfloat16)
     input = ttnn.to_device(input, device, memory_config=ttnn.L1_MEMORY_CONFIG)
     input = ttnn.to_layout(input, ttnn.TILE_LAYOUT, dtype=ttnn.bfloat16)
 
-    ttnn_timestep = ttnn_timestep.permute(2, 0, 1, 3)  # pre-permute temb
-    ttnn_timestep = ttnn.from_torch(ttnn_timestep, ttnn.bfloat16)
-    ttnn_timestep = ttnn.to_device(ttnn_timestep, device, memory_config=ttnn.L1_MEMORY_CONFIG)
-    ttnn_timestep = ttnn.to_layout(ttnn_timestep, ttnn.TILE_LAYOUT, dtype=ttnn.bfloat8_b)
+    _tlist = []
+    for t in ttnn_scheduler.timesteps:
+        _t = constant_prop_time_embeddings(t, input, model.time_proj)
+        _t = _t.unsqueeze(0).unsqueeze(0)
+        _t = _t.permute(2, 0, 1, 3)  # pre-permute temb
+        _t = ttnn.from_torch(_t, dtype=ttnn.bfloat16, layout=ttnn.TILE_LAYOUT, device=device)
+        _tlist.append(_t)
+
+    time_step = ttnn_scheduler.timesteps.tolist()
+    torch_output = model(input_pt, timestep=time_step[0], encoder_hidden_states=encoder_hidden_states.squeeze(0)).sample
 
     encoder_hidden_states = torch.nn.functional.pad(encoder_hidden_states, (0, 0, 0, 19))
     encoder_hidden_states = ttnn.from_torch(
@@ -166,7 +170,7 @@ def test_stable_diffusion_perf(device, batch_size, num_inference_steps, expected
         profiler.start(f"model_run_for_inference_{i}")
         ttnn_output = model(
             input,
-            timestep=ttnn_timestep,
+            timestep=_tlist[i],
             encoder_hidden_states=encoder_hidden_states,
             class_labels=class_labels,
             attention_mask=attention_mask,
diff --git a/tests/scripts/run_performance.sh b/tests/scripts/run_performance.sh
index 084654efd35..23cc2d0d0ba 100755
--- a/tests/scripts/run_performance.sh
+++ b/tests/scripts/run_performance.sh
@@ -48,7 +48,7 @@ run_perf_models_cnn_javelin() {
     local test_marker=$2
 
     # Run tests
-    env WH_ARCH_YAML=wormhole_b0_80_arch_eth_dispatch.yaml pytest models/experimental/functional_stable_diffusion/tests -m $test_marker
+    env WH_ARCH_YAML=wormhole_b0_80_arch_eth_dispatch.yaml pytest tests/device_perf_tests/stable_diffusion -m $test_marker
     #env WH_ARCH_YAML=wormhole_b0_80_arch_eth_dispatch.yaml pytest models/experimental/functional_unet/tests -m $test_marker
 
     ## Merge all the generated reports
@@ -58,7 +58,7 @@ run_perf_models_cnn_javelin() {
 run_device_perf_models() {
     local test_marker=$1
 
-    env pytest models/experimental/functional_stable_diffusion/tests -m $test_marker
+    env pytest tests/device_perf_tests/stable_diffusion -m $test_marker
 
     if [ "$tt_arch" == "grayskull" ]; then
         #TODO(MO): Until #6560 is fixed, GS device profiler test are grouped with
diff --git a/tests/ttnn/integration_tests/stable_diffusion/test_basic_transformer_block.py b/tests/ttnn/integration_tests/stable_diffusion/test_basic_transformer_block.py
index 29573812dc3..b9469cdd5aa 100644
--- a/tests/ttnn/integration_tests/stable_diffusion/test_basic_transformer_block.py
+++ b/tests/ttnn/integration_tests/stable_diffusion/test_basic_transformer_block.py
@@ -8,16 +8,16 @@
 from diffusers import StableDiffusionPipeline
 import ttnn
 import tt_lib as ttl
-from models.experimental.functional_stable_diffusion.tt.ttnn_functional_basic_transformer_block import (
+from models.demos.wormhole.stable_diffusion.tt.ttnn_functional_basic_transformer_block import (
     basic_transformer_block as ttnn_basic_transformer_block,
 )
-from models.experimental.functional_stable_diffusion.custom_preprocessing import custom_preprocessor
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_basic_transformer_block import (
+from models.demos.wormhole.stable_diffusion.custom_preprocessing import custom_preprocessor
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_basic_transformer_block import (
     basic_transformer_block as tt2_ttnn_basic_transformer_block,
 )
 from ttnn.model_preprocessing import preprocess_model_parameters
 from tests.ttnn.utils_for_testing import assert_with_pcc
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_utility_functions import (
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_utility_functions import (
     pre_process_input,
     post_process_output,
 )
diff --git a/tests/ttnn/integration_tests/stable_diffusion/test_cross_attention.py b/tests/ttnn/integration_tests/stable_diffusion/test_cross_attention.py
index d5265ddc05d..1e4d7feee97 100644
--- a/tests/ttnn/integration_tests/stable_diffusion/test_cross_attention.py
+++ b/tests/ttnn/integration_tests/stable_diffusion/test_cross_attention.py
@@ -7,11 +7,11 @@
 from diffusers import StableDiffusionPipeline
 import ttnn
 
-from models.experimental.functional_stable_diffusion.tt.ttnn_functional_cross_attention import (
+from models.demos.wormhole.stable_diffusion.tt.ttnn_functional_cross_attention import (
     cross_attention as ttnn_cross_attention,
 )
-from models.experimental.functional_stable_diffusion.custom_preprocessing import custom_preprocessor
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_cross_attention import (
+from models.demos.wormhole.stable_diffusion.custom_preprocessing import custom_preprocessor
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_cross_attention import (
     cross_attention as tt2_ttnn_cross_attention,
 )
 from ttnn.model_preprocessing import preprocess_model_parameters
diff --git a/tests/ttnn/integration_tests/stable_diffusion/test_cross_attn_up_block_2d.py b/tests/ttnn/integration_tests/stable_diffusion/test_cross_attn_up_block_2d.py
index 2a43937a933..ea5f7740465 100644
--- a/tests/ttnn/integration_tests/stable_diffusion/test_cross_attn_up_block_2d.py
+++ b/tests/ttnn/integration_tests/stable_diffusion/test_cross_attn_up_block_2d.py
@@ -11,20 +11,20 @@
 
 from models.utility_functions import tt_to_torch_tensor, torch_random
 from tests.ttnn.utils_for_testing import assert_with_pcc
-from models.experimental.functional_stable_diffusion.tt.ttnn_functional_cross_attn_upblock import (
+from models.demos.wormhole.stable_diffusion.tt.ttnn_functional_cross_attn_upblock import (
     cross_attention_upblock2d as ttnn_cross_attention_upblock2d,
 )
 from models.utility_functions import (
     skip_for_grayskull,
 )
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_cross_attn_upblock import (
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_cross_attn_upblock import (
     cross_attention_upblock2d as tt2_ttnn_cross_attention_upblock2d,
 )
 
-from models.experimental.functional_stable_diffusion.custom_preprocessing import custom_preprocessor
+from models.demos.wormhole.stable_diffusion.custom_preprocessing import custom_preprocessor
 
 from ttnn.model_preprocessing import preprocess_model_parameters
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_utility_functions import (
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_utility_functions import (
     pre_process_input,
     weight_to_bfp8,
     post_process_output,
diff --git a/tests/ttnn/integration_tests/stable_diffusion/test_demo.py b/tests/ttnn/integration_tests/stable_diffusion/test_demo.py
new file mode 100644
index 00000000000..4bd7a971ba2
--- /dev/null
+++ b/tests/ttnn/integration_tests/stable_diffusion/test_demo.py
@@ -0,0 +1,49 @@
+# SPDX-FileCopyrightText: © 2023 Tenstorrent Inc.
+
+# SPDX-License-Identifier: Apache-2.0
+
+import pytest
+from models.utility_functions import skip_for_grayskull
+from models.demos.wormhole.stable_diffusion.demo.demo import test_demo as demo
+from models.demos.wormhole.stable_diffusion.demo.demo import test_demo_diffusiondb as demo_db
+
+
+@skip_for_grayskull()
+@pytest.mark.parametrize("device_l1_small_size", [32768], indirect=True)
+@pytest.mark.parametrize(
+    "input_path",
+    (("models/demos/wormhole/stable_diffusion/demo/input_data.json"),),
+    ids=["default_input"],
+)
+@pytest.mark.parametrize(
+    "num_prompts",
+    ((1),),
+)
+@pytest.mark.parametrize(
+    "num_inference_steps",
+    ((5),),
+)
+@pytest.mark.parametrize(
+    "image_size",
+    ((512, 512),),
+)
+def test_demo_sd(device, reset_seeds, input_path, num_prompts, num_inference_steps, image_size):
+    demo(device, reset_seeds, input_path, num_prompts, num_inference_steps, image_size)
+
+
+@skip_for_grayskull()
+@pytest.mark.parametrize("device_l1_small_size", [32768], indirect=True)
+@pytest.mark.parametrize(
+    "num_prompts",
+    ((1),),
+)
+@pytest.mark.parametrize(
+    "num_inference_steps",
+    ((5),),
+)
+@pytest.mark.parametrize(
+    "image_size",
+    ((512, 512),),
+)
+def test_demo_sd_db(device, reset_seeds, input_path, num_prompts, num_inference_steps, image_size):
+    demo_db(device, reset_seeds, input_path, num_prompts, num_inference_steps, image_size)
diff --git a/tests/ttnn/integration_tests/stable_diffusion/test_down_block_2d.py b/tests/ttnn/integration_tests/stable_diffusion/test_down_block_2d.py
index c79b3e44c21..f258bc72e4c 100644
--- a/tests/ttnn/integration_tests/stable_diffusion/test_down_block_2d.py
+++ b/tests/ttnn/integration_tests/stable_diffusion/test_down_block_2d.py
@@ -12,14 +12,14 @@
 from models.utility_functions import (
     skip_for_grayskull,
 )
-from models.experimental.functional_stable_diffusion.custom_preprocessing import custom_preprocessor
-from models.experimental.functional_stable_diffusion.tt.ttnn_functional_downblock_2d import (
+from models.demos.wormhole.stable_diffusion.custom_preprocessing import custom_preprocessor
+from models.demos.wormhole.stable_diffusion.tt.ttnn_functional_downblock_2d import (
     downblock2d as ttnn_downblock2d,
 )
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_downblock_2d import (
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_downblock_2d import (
     downblock2d as tt2_ttnn_downblock2d,
 )
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_utility_functions import (
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_utility_functions import (
     pre_process_input,
     post_process_output,
 )
diff --git a/tests/ttnn/integration_tests/stable_diffusion/test_downsample_2d.py b/tests/ttnn/integration_tests/stable_diffusion/test_downsample_2d.py
index ccdccfd4b96..56c26a13c43 100644
--- a/tests/ttnn/integration_tests/stable_diffusion/test_downsample_2d.py
+++ b/tests/ttnn/integration_tests/stable_diffusion/test_downsample_2d.py
@@ -11,17 +11,17 @@
 from tests.ttnn.utils_for_testing import assert_with_pcc
 from ttnn.model_preprocessing import preprocess_model_parameters
 from models.utility_functions import torch_random
-from models.experimental.functional_stable_diffusion.custom_preprocessing import custom_preprocessor
-from models.experimental.functional_stable_diffusion.tt.ttnn_functional_downsample_2d import (
+from models.demos.wormhole.stable_diffusion.custom_preprocessing import custom_preprocessor
+from models.demos.wormhole.stable_diffusion.tt.ttnn_functional_downsample_2d import (
     downsample_2d as ttnn_downsample_2d,
 )
 from models.utility_functions import (
     skip_for_grayskull,
 )
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_downsample_2d import (
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_downsample_2d import (
     downsample_2d as tt2_ttnn_downsample_2d,
 )
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_utility_functions import (
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_utility_functions import (
     pre_process_input,
     post_process_output,
 )
diff --git a/tests/ttnn/integration_tests/stable_diffusion/test_embedding.py b/tests/ttnn/integration_tests/stable_diffusion/test_embedding.py
index 5a5b10df859..05020ebc3ea 100644
--- a/tests/ttnn/integration_tests/stable_diffusion/test_embedding.py
+++ b/tests/ttnn/integration_tests/stable_diffusion/test_embedding.py
@@ -13,7 +13,7 @@
 
 import ttnn
 from ttnn.model_preprocessing import preprocess_model_parameters
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_embeddings import TtTimestepEmbedding
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_embeddings import TtTimestepEmbedding
 import pytest
 
 
diff --git a/tests/ttnn/integration_tests/stable_diffusion/test_feedforward.py b/tests/ttnn/integration_tests/stable_diffusion/test_feedforward.py
index b54f44f53ee..94019851040 100644
--- a/tests/ttnn/integration_tests/stable_diffusion/test_feedforward.py
+++ b/tests/ttnn/integration_tests/stable_diffusion/test_feedforward.py
@@ -9,11 +9,11 @@
 import ttnn
 from ttnn.model_preprocessing import preprocess_model_parameters
 
-from models.experimental.functional_stable_diffusion.tt.ttnn_functional_feedforward import (
+from models.demos.wormhole.stable_diffusion.tt.ttnn_functional_feedforward import (
     feedforward as ttnn_feedforward,
 )
-from models.experimental.functional_stable_diffusion.custom_preprocessing import custom_preprocessor
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_feedforward import (
+from models.demos.wormhole.stable_diffusion.custom_preprocessing import custom_preprocessor
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_feedforward import (
     feedforward as tt2_ttnn_feedforward,
 )
 from models.utility_functions import torch_random
diff --git a/tests/ttnn/integration_tests/stable_diffusion/test_geglu.py b/tests/ttnn/integration_tests/stable_diffusion/test_geglu.py
index ee5e354fa4a..b083e4faf64 100644
--- a/tests/ttnn/integration_tests/stable_diffusion/test_geglu.py
+++ b/tests/ttnn/integration_tests/stable_diffusion/test_geglu.py
@@ -9,10 +9,10 @@
 import ttnn
 from ttnn.model_preprocessing import preprocess_model_parameters
 
-from models.experimental.functional_stable_diffusion.custom_preprocessing import custom_preprocessor
+from models.demos.wormhole.stable_diffusion.custom_preprocessing import custom_preprocessor
 
-from models.experimental.functional_stable_diffusion.tt.ttnn_functional_geglu import geglu as ttnn_geglu
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_geglu import geglu as tt2_ttnn_geglu
+from models.demos.wormhole.stable_diffusion.tt.ttnn_functional_geglu import geglu as ttnn_geglu
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_geglu import geglu as tt2_ttnn_geglu
 from models.utility_functions import torch_random, skip_for_grayskull
 
 from tests.ttnn.utils_for_testing import assert_with_pcc
diff --git a/tests/ttnn/integration_tests/stable_diffusion/test_resnet_block_2d.py b/tests/ttnn/integration_tests/stable_diffusion/test_resnet_block_2d.py
index 0a2d9440543..d25a958b204 100644
--- a/tests/ttnn/integration_tests/stable_diffusion/test_resnet_block_2d.py
+++ b/tests/ttnn/integration_tests/stable_diffusion/test_resnet_block_2d.py
@@ -13,8 +13,8 @@
 
 import ttnn
 from ttnn.model_preprocessing import preprocess_model_parameters
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_resnetblock2d import resnetBlock2D
-from models.experimental.functional_stable_diffusion.custom_preprocessing import custom_preprocessor
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_resnetblock2d import resnetBlock2D
+from models.demos.wormhole.stable_diffusion.custom_preprocessing import custom_preprocessor
 
 
 def ttnn_to_torch(input):
diff --git a/tests/ttnn/integration_tests/stable_diffusion/test_resnet_block_2d_new_conv.py b/tests/ttnn/integration_tests/stable_diffusion/test_resnet_block_2d_new_conv.py
index 93f48dc91f1..b86aba9a9a4 100644
--- a/tests/ttnn/integration_tests/stable_diffusion/test_resnet_block_2d_new_conv.py
+++ b/tests/ttnn/integration_tests/stable_diffusion/test_resnet_block_2d_new_conv.py
@@ -13,9 +13,9 @@
 
 import ttnn
 from ttnn.model_preprocessing import preprocess_model_parameters
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_resnetblock2d_new_conv import resnetBlock2D
-from models.experimental.functional_stable_diffusion.custom_preprocessing import custom_preprocessor
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_utility_functions import conv_cache
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_resnetblock2d_new_conv import resnetBlock2D
+from models.demos.wormhole.stable_diffusion.custom_preprocessing import custom_preprocessor
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_utility_functions import conv_cache
 
 
 def ttnn_to_torch(input):
diff --git a/tests/ttnn/integration_tests/stable_diffusion/test_sharded_attention.py b/tests/ttnn/integration_tests/stable_diffusion/test_sharded_attention.py
index 3b201afbc00..4704da79ff5 100644
--- a/tests/ttnn/integration_tests/stable_diffusion/test_sharded_attention.py
+++ b/tests/ttnn/integration_tests/stable_diffusion/test_sharded_attention.py
@@ -16,7 +16,7 @@
     skip_for_wormhole_b0,
     skip_for_grayskull,
 )
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_utility_functions import (
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_utility_functions import (
     determine_largest_subblock_size,
     determine_blocking,
 )
diff --git a/tests/ttnn/integration_tests/stable_diffusion/test_sharded_matmuls.py b/tests/ttnn/integration_tests/stable_diffusion/test_sharded_matmuls.py
index 292356bddc7..dc0388c7bcf 100644
--- a/tests/ttnn/integration_tests/stable_diffusion/test_sharded_matmuls.py
+++ b/tests/ttnn/integration_tests/stable_diffusion/test_sharded_matmuls.py
@@ -12,7 +12,7 @@
 from models.utility_functions import (
     skip_for_grayskull,
 )
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_utility_functions import (
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_utility_functions import (
     determine_largest_subblock_size,
     round_up_to_tile_dim,
 )
diff --git a/tests/ttnn/integration_tests/stable_diffusion/test_transformer_2d_model.py b/tests/ttnn/integration_tests/stable_diffusion/test_transformer_2d_model.py
index 7a77ca41c49..78a41510ba6 100644
--- a/tests/ttnn/integration_tests/stable_diffusion/test_transformer_2d_model.py
+++ b/tests/ttnn/integration_tests/stable_diffusion/test_transformer_2d_model.py
@@ -12,12 +12,12 @@
     skip_for_grayskull,
 )
 from ttnn.model_preprocessing import preprocess_model_parameters
-from models.experimental.functional_stable_diffusion.custom_preprocessing import custom_preprocessor
-from models.experimental.functional_stable_diffusion.tt.ttnn_functional_transformer_2d import transformer_2d_model
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_transformer_2d import (
+from models.demos.wormhole.stable_diffusion.custom_preprocessing import custom_preprocessor
+from models.demos.wormhole.stable_diffusion.tt.ttnn_functional_transformer_2d import transformer_2d_model
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_transformer_2d import (
     transformer_2d_model as transformer_2d_model_tt2,
 )
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_utility_functions import (
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_utility_functions import (
     pre_process_input,
     post_process_output,
 )
diff --git a/tests/ttnn/integration_tests/stable_diffusion/test_ttnn_cross_attention_down_block_2d.py b/tests/ttnn/integration_tests/stable_diffusion/test_ttnn_cross_attention_down_block_2d.py
index 94cd58d42bc..df210a8158e 100644
--- a/tests/ttnn/integration_tests/stable_diffusion/test_ttnn_cross_attention_down_block_2d.py
+++ b/tests/ttnn/integration_tests/stable_diffusion/test_ttnn_cross_attention_down_block_2d.py
@@ -8,7 +8,7 @@
 from diffusers import StableDiffusionPipeline
 import ttnn
 
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_cross_attention_down_block_2d import (
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_cross_attention_down_block_2d import (
     cross_attention_down_block_2d,
 )
 from ttnn.model_preprocessing import preprocess_model_parameters
@@ -16,8 +16,8 @@
 from models.utility_functions import (
     skip_for_grayskull,
 )
-from models.experimental.functional_stable_diffusion.custom_preprocessing import custom_preprocessor
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_utility_functions import (
+from models.demos.wormhole.stable_diffusion.custom_preprocessing import custom_preprocessor
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_utility_functions import (
     run_ttnn_conv_with_pre_and_post_tensor_formatting,
     pre_process_input,
     post_process_output,
diff --git a/tests/ttnn/integration_tests/stable_diffusion/test_unet_2d_condition_model.py b/tests/ttnn/integration_tests/stable_diffusion/test_unet_2d_condition_model.py
index 7ee56321f9d..1857f9b6012 100644
--- a/tests/ttnn/integration_tests/stable_diffusion/test_unet_2d_condition_model.py
+++ b/tests/ttnn/integration_tests/stable_diffusion/test_unet_2d_condition_model.py
@@ -19,15 +19,15 @@
 from diffusers import LMSDiscreteScheduler
 import ttnn
 from ttnn.model_preprocessing import preprocess_model_parameters
-from models.experimental.functional_stable_diffusion.custom_preprocessing import custom_preprocessor
-from models.experimental.functional_stable_diffusion.tt.ttnn_functional_unet_2d_condition_model import (
+from models.demos.wormhole.stable_diffusion.custom_preprocessing import custom_preprocessor
+from models.demos.wormhole.stable_diffusion.tt.ttnn_functional_unet_2d_condition_model import (
     UNet2DConditionModel,
 )
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_unet_2d_condition_model import (
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_unet_2d_condition_model import (
     UNet2DConditionModel as UNet2D,
 )
 import math
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_utility_functions import (
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_utility_functions import (
     post_process_output,
 )
 from ttnn.operations.core import unsqueeze_to_4D
diff --git a/tests/ttnn/integration_tests/stable_diffusion/test_unet_mid_block_2d_cross_attn.py b/tests/ttnn/integration_tests/stable_diffusion/test_unet_mid_block_2d_cross_attn.py
index 7fe3b66aa28..751ab3dbc54 100644
--- a/tests/ttnn/integration_tests/stable_diffusion/test_unet_mid_block_2d_cross_attn.py
+++ b/tests/ttnn/integration_tests/stable_diffusion/test_unet_mid_block_2d_cross_attn.py
@@ -13,14 +13,14 @@
     skip_for_grayskull,
 )
 from ttnn.model_preprocessing import preprocess_model_parameters
-from models.experimental.functional_stable_diffusion.custom_preprocessing import custom_preprocessor
-from models.experimental.functional_stable_diffusion.tt.ttnn_functional_unet_mid_block_2d_cross_attn import (
+from models.demos.wormhole.stable_diffusion.custom_preprocessing import custom_preprocessor
+from models.demos.wormhole.stable_diffusion.tt.ttnn_functional_unet_mid_block_2d_cross_attn import (
     unet_mid_block_2d_cross_attn as ttnn_unet_mid_block_2d_cross_attn,
 )
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_unet_mid_block_2d_cross_attn import (
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_unet_mid_block_2d_cross_attn import (
     unet_mid_block_2d_cross_attn as tt2_ttnn_unet_mid_block_2d_cross_attn,
 )
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_utility_functions import (
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_utility_functions import (
     pre_process_input,
     post_process_output,
 )
diff --git a/tests/ttnn/integration_tests/stable_diffusion/test_upblock_2d.py b/tests/ttnn/integration_tests/stable_diffusion/test_upblock_2d.py
index af783893eb6..e7d2562f05e 100644
--- a/tests/ttnn/integration_tests/stable_diffusion/test_upblock_2d.py
+++ b/tests/ttnn/integration_tests/stable_diffusion/test_upblock_2d.py
@@ -13,13 +13,13 @@
 from models.utility_functions import (
     skip_for_grayskull,
 )
-from models.experimental.functional_stable_diffusion.tt.ttnn_functional_upblock_2d import upblock_2d as ttnn_upblock_2d
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_upblock_2d import (
+from models.demos.wormhole.stable_diffusion.tt.ttnn_functional_upblock_2d import upblock_2d as ttnn_upblock_2d
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_upblock_2d import (
     upblock_2d as tt2_ttnn_upblock_2d,
 )
-from models.experimental.functional_stable_diffusion.custom_preprocessing import custom_preprocessor
+from models.demos.wormhole.stable_diffusion.custom_preprocessing import custom_preprocessor
 from ttnn.model_preprocessing import preprocess_model_parameters
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_utility_functions import (
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_utility_functions import (
     pre_process_input,
     post_process_output,
     weight_to_bfp8,
diff --git a/tests/ttnn/integration_tests/stable_diffusion/test_upsample_2d.py b/tests/ttnn/integration_tests/stable_diffusion/test_upsample_2d.py
index 80de7c705f2..acdeaf35a43 100644
--- a/tests/ttnn/integration_tests/stable_diffusion/test_upsample_2d.py
+++ b/tests/ttnn/integration_tests/stable_diffusion/test_upsample_2d.py
@@ -7,11 +7,11 @@
 import pytest
 import ttnn
 
-from models.experimental.functional_stable_diffusion.tt.ttnn_functional_upsample_2d import upsample2d as ttnn_upsample2d
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_upsample_2d import (
+from models.demos.wormhole.stable_diffusion.tt.ttnn_functional_upsample_2d import upsample2d as ttnn_upsample2d
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_upsample_2d import (
     upsample2d as tt2_ttnn_upsample2d,
 )
-from models.experimental.functional_stable_diffusion.custom_preprocessing import custom_preprocessor
+from models.demos.wormhole.stable_diffusion.custom_preprocessing import custom_preprocessor
 from tests.ttnn.utils_for_testing import assert_with_pcc
 from models.utility_functions import (
     skip_for_grayskull,
@@ -19,7 +19,7 @@
 from ttnn.model_preprocessing import preprocess_model_parameters
 
 from models.utility_functions import torch_random
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_utility_functions import (
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_utility_functions import (
     pre_process_input,
     post_process_output,
 )
diff --git a/tests/ttnn/integration_tests/stable_diffusion/test_upsample_nearest_2d.py b/tests/ttnn/integration_tests/stable_diffusion/test_upsample_nearest_2d.py
index 7cab257f797..c08aa35b345 100644
--- a/tests/ttnn/integration_tests/stable_diffusion/test_upsample_nearest_2d.py
+++ b/tests/ttnn/integration_tests/stable_diffusion/test_upsample_nearest_2d.py
@@ -6,10 +6,10 @@
 import pytest
 import ttnn
 
-from models.experimental.functional_stable_diffusion.tt.ttnn_functional_upsample_nearest_2d import (
+from models.demos.wormhole.stable_diffusion.tt.ttnn_functional_upsample_nearest_2d import (
     upsample_nearest2d as ttnn_upsample_nearest2d,
 )
-from models.experimental.functional_stable_diffusion.tt2.ttnn_functional_upsample_nearest_2d import (
+from models.demos.wormhole.stable_diffusion.tt2.ttnn_functional_upsample_nearest_2d import (
     upsample_nearest2d as tt2_ttnn_upsample_nearest2d,
 )
 from tests.ttnn.utils_for_testing import assert_with_pcc