Create first optimized workflow masters
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# Z-Image Turbo 3070 Inpaint Start
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## Summary
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Best current `Z-Image` edit starter for inpainting on tighter VRAM.
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This master is a curated hold of the community inpainting workflow because it gives us a real edit path while still staying more plausible on a `3070` than heavier image stacks.
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## Status
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- `best-current`
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- `not-yet-tested-on-chris-box`
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## Workflow asset
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- `workflow.json`
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## Built from
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- `models/zimage/z-image-turbo-inpainting-community/`
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## Why this is the current master
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- It is the strongest actual `Z-Image Turbo` edit workflow we have right now.
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- Editing matters more than toy text-to-image wins for practical day-to-day use.
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- The graph is specific enough to be useful without being a giant kitchen-sink workflow.
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## What I intentionally kept
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- inpainting-focused graph shape
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- existing `ZImageFunControlnet` route
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- community sampler path that is already wired for edit work
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## What I intentionally did not add yet
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- control-union extras from the separate community workflow
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- any manual sampler surgery before real testing
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- any claim that this is better than `FLUX.2-klein` for edits
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## Required models
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- `models/text_encoders/qwen_3_4b.safetensors`
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- `models/diffusion_models/z_image_turbo_bf16.safetensors`
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- `models/vae/ae.safetensors`
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## Required custom nodes
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- `rgthree-comfy`
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- the package that provides `LanPaint_KSampler`
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- the package that provides `ZImageFunControlnet`
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## Monday test checklist
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- Confirm missing custom nodes first.
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- Check whether masked edits are stable enough to keep.
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- Compare it directly against the `flux2klein` edit master on the same input.
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## Next optimization candidates
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- reduce custom-node dependency count if the graph is good but fragile
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- borrow only the useful control ideas from the community control-union workflow
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