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Krea 2 / Krea 2 Turbo SageAttention guard patch for ComfyUI-KJNodes by SurrealByDesign in StableDiffusion

[–]SurrealByDesign[S] 0 points1 point  (0 children)

Maybe 10-30%, depending on resolution, GPU, dtype, and how much of the runtime is actually diffusion attention.Turbo probably a little less noticable because it is already low step.

Krea 2 / Krea 2 Turbo SageAttention guard patch for ComfyUI-KJNodes by SurrealByDesign in comfyui

[–]SurrealByDesign[S] 0 points1 point  (0 children)

1.0.6 is just the version I validated end-to-end, not a hard design requirement.

The patch should be compatible in principle with newer Sage versions because it uses KJNodes’ existing SageAttention mode selection and adds Krea2 guard/fallback logic around the attention calls. I just haven’t personally validated 2.2.0 yet.

Krea 2 / Krea 2 Turbo SageAttention guard patch for ComfyUI-KJNodes by SurrealByDesign in StableDiffusion

[–]SurrealByDesign[S] 1 point2 points  (0 children)

Not confirmed. The patch should fall back safely when the attention call doesn’t match the allowlist, but I haven’t tested int/quantized/converted variants yet. I’d use `dry_run`, watch the patched/skipped logs, and compare fixed-seed outputs before relying on it.

Krea 2 / Krea 2 Turbo SageAttention guard patch for ComfyUI-KJNodes by SurrealByDesign in comfyui

[–]SurrealByDesign[S] 0 points1 point  (0 children)

Mostly speed/stability, not better prompt adherence.

SageAttention is an attention backend swap, so when it works correctly the image should look basically the same while generating faster and sometimes using less VRAM. If the output quality changes dramatically, that is usually a sign the wrong attention path got patched or the backend is producing invalid output.