Let's start with a baseline. Disable reduced precision and the [`scaled_dot_product_attention` (SDPA)](../optimization/torch2.0#scaled-dot-product-attention) function which is automatically used by Diffusers:  
```python
from diffusers import StableDiffusionXLPipeline

# Load the pipeline in full-precision and place its model components on CUDA.
pipe = StableDiffusionXLPipeline.from_pretrained(
"stabilityai/stable-diffusion-xl-base-1.0"
).to("cuda")

# Run the attention ops without SDPA.
pipe.unet.set_default_attn_processor()
pipe.vae.set_default_attn_processor()

prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt, num_inference_steps=30).images[0]
```  
This default setup takes 7.36 seconds.  
<div class="flex justify-center">
<img src="https://huggingface.co/datasets/sayakpaul/sample-datasets/resolve/main/progressive-acceleration-sdxl/SDXL%2C_Batch_Size%3A_1%2C_Steps%3A_30_0.png" width=500>
</div>
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/tutorials/fast_diffusion.md