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Stable Diffusion Sparse Attention Optimization Prompt Template

Prompt Edit here before copy/try — source content is unchanged

When using the sparse attention optimization node, please note the following parameter settings:
- Attention density: It is recommended to maintain a higher density (>0.5) in early steps to ensure the accuracy of the generation trajectory; in middle/later steps, the density can be appropriately reduced (0.1-0.3) to reduce computation.
- Sparsity ratio: The default is 0.9, meaning 90% of the information is discarded and 10% is retained. This can be adjusted according to requirements, but note that too low a retention rate will affect generation quality.
- Memory optimization: After enabling sparse attention, VRAM usage is expected to be reduced by about 500MB.
- Speed optimization: The attention computation speed is expected to increase by 5-20%, depending on the hardware configuration.

Notes:
- This optimization is based on ComfyUI 0.33.0 and above.
- It has only been tested with comfy pruned_int8_convrot weights; other versions may require additional adjustments.
- Sparse attention is not a free performance boost; the density setting affects the balance between generation quality and speed.

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Usage & requirements

Load the sparse attention optimization node in ComfyUI and adjust the attention density and sparsity ratio parameters according to generation requirements.

Tools: ComfyUI Stable Diffusion
Variables: attention_density sparsity_ratio VRAM speed
Source: r/StableDiffusion ↗

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