Create first optimized workflow masters
This commit is contained in:
@@ -26,6 +26,14 @@ These workflows are intended to become the practical default choices for each ca
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- `text-to-video/`
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- `upscale-restoration/`
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## Current best-current masters
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- `text-to-image/zimage-turbo-3070-fast-start/`
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- `image-edit/zimage-turbo-3070-inpaint-start/`
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- `image-edit/flux2klein-9b-fp8-edit-master/`
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- `image-to-video/ltx23-3070-simple-master/`
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- `text-to-video/minimax-h3-3070-turbo-master/`
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## Workflow format
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Each optimized workflow should have its own folder and usually include:
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@@ -1,3 +1,8 @@
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# Image Edit Masters
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Home for maintained category masters focused on image editing, inpainting, outpainting, and reference-driven edits.
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## Current masters
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- `zimage-turbo-3070-inpaint-start`
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- `flux2klein-9b-fp8-edit-master`
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@@ -0,0 +1,61 @@
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# FLUX.2-klein 9B FP8 Edit Master
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## Summary
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Best current `FLUX.2-klein` image-edit master for your setup.
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This is built from the official `9B distilled` template because it matches your `9B fp8` preference while still leaning toward practicality rather than the heavier `base` route.
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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/flux2klein/image-edit-9b-distilled/`
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## Why this is the current master
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- Matches your default family: `FLUX.2-klein 9B fp8`
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- Official Comfy template is a safer foundation than community pages with weak provenance.
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- Distilled is the most sensible first optimization bias for a `3070`.
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## What I intentionally kept
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- official Comfy node layout
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- official `9B fp8` model path
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- official text-encoder pairing
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- speed-first distilled route
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## What I intentionally did not add yet
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- community `GGUF` ideas
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- KV-cache experimentation
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- extra custom-node edits with unclear payoff
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- a fake outpainting claim before we prove it on your machine
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## Required models
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- `models/diffusion_models/flux-2-klein-9b-fp8.safetensors`
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- `models/text_encoders/qwen_3_8b_fp8mixed.safetensors`
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- `models/vae/flux2-vae.safetensors`
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## Required custom nodes
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- none beyond current official Comfy support for the template nodes
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## Monday test checklist
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- Confirm the model paths line up with your local layout.
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- Test a plain edit, then an expand-canvas outpaint attempt.
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- Compare `9B distilled` behavior against any `4B distilled` outpaint workflow you already trust.
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## Next optimization candidates
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- clone this into a dedicated outpaint master if the graph behaves well
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- borrow only proven community prompt or graph hygiene improvements
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File diff suppressed because it is too large
Load Diff
@@ -0,0 +1,61 @@
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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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File diff suppressed because it is too large
Load Diff
@@ -1,3 +1,7 @@
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# Image-to-Video Masters
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Home for maintained category masters focused on image-to-video generation.
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## Current masters
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- `ltx23-3070-simple-master`
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@@ -0,0 +1,56 @@
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# LTX 2.3 3070 Simple Master
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## Summary
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Best current `LTX 2.3` low-complexity starter for local video work.
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This master uses the simple single-pass workflow instead of the more ambitious first-last-frame or character-sheet variants because your `3070` needs a realistic first foothold, not the fanciest graph on paper.
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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/ltx/ltx23-i2v-t2v-simple-single-pass/`
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## Why this is the current master
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- Most plausible `LTX` starting point on tighter VRAM
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- Simpler graph means less time chasing broken helper nodes
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- Supports both `image-to-video` and `text-to-video` style experimentation from one baseline
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## What I intentionally kept
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- single-pass graph shape
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- split-model assumption from the source pack
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- lighter starting complexity than the bigger RuneXX graphs
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## What I intentionally did not add yet
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- first-last-frame complexity
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- character-sheet consistency branches
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- extra memory-efficiency gadgets unless needed
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## Required custom nodes
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- `ComfyUI-KJNodes`
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- `rgthree-comfy`
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- `easy use` / `easy showAnything`
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- optional `ComfyUI-GGUF` support remains present in the source graph
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## Monday test checklist
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- Confirm whether it loads at all on the `3070`.
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- Check whether preview/decode settings feel like the real bottleneck.
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- If it works, then try the heavier first-last-frame workflow second.
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## Next optimization candidates
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- strip unused optional loader paths if they create confusion
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- create a separate `first-last-frame` master only if the simple master proves viable
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File diff suppressed because it is too large
Load Diff
@@ -11,3 +11,12 @@ Use it to capture:
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- what should be ignored next time
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These notes exist so future review passes do not have to re-trawl every collected workflow from scratch.
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## Current note files
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- `flux.md`
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- `flux2klein.md`
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- `ltx.md`
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- `minimax.md`
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- `zimage.md`
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- `reviews/`
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@@ -0,0 +1,35 @@
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# LTX Notes
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## Current default assumptions
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- Low-VRAM practicality matters more than graph sophistication.
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- The first question is whether `LTX 2.3` is usable at all on Chris's `3070`.
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## Strong current source workflows
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- `models/ltx/ltx23-i2v-t2v-simple-single-pass/`
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- `models/ltx/ltx23-t2v-simple-single-pass/`
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- `models/ltx/ltx23-first-last-frame/`
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- `models/ltx/ltx23-character-sheet-best-face-id/`
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## Strong current heuristics
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- Start with simple single-pass before trying larger consistency graphs.
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- Prefer split-model and extracted-model routes when the source pack says they are easier locally.
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- Treat first-last-frame and character-sheet workflows as second-wave tests, not the baseline.
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## Current weak areas
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- No real proof yet for what is genuinely practical on Chris's box.
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- Community packs bundle lots of helper nodes, which raises import fragility.
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## Best current optimization direction
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- Keep `optimized/image-to-video/ltx23-3070-simple-master/` as the first `LTX` default.
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- Only promote first-last-frame or character-sheet variants after the simple master proves viable.
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## What needs Monday proof
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- whether the simple master loads and runs at all on the `3070`
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- whether preview/decode or the core model path is the real bottleneck
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- whether `LTX` has any realistic chance of displacing `MiniMax` for local use
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@@ -0,0 +1,35 @@
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# MiniMax Notes
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## Current default assumptions
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- `MiniMax H3` is promising, but brute-force paths are too heavy to be the first bet on a `3070`.
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- Speed-first and low-VRAM community workflows matter more than official purity for the first real test.
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## Strong current source workflows
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- `models/minimax/minimax-h3-official-t2v/`
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- `models/minimax/minimax-h3-official-i2v/`
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- `models/minimax/minimax-h3-turbo-lora-community/`
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- `models/minimax/minimax-h3-int8-r2v-community/`
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## Strong current heuristics
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- Prefer Turbo LoRA for the first `text-to-video` attempt.
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- Prefer INT8-based community workflows for `reference-to-video` exploration.
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- Keep attention and memory-efficiency helpers if they are already integrated and well documented.
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## Current weak areas
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- No proof yet that MiniMax is truly practical on Chris's box.
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- Custom-node stack is more fragile than the current `flux2klein` path.
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## Best current optimization direction
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- Keep `optimized/text-to-video/minimax-h3-3070-turbo-master/` as the first MiniMax default.
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- Keep the INT8 reference-video workflow as the next donor for future low-VRAM optimization.
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## What needs Monday proof
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- whether the Turbo LoRA workflow is just technically possible or actually usable
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- whether the source-recommended `8`-step path holds up in quality
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- whether MiniMax feels like a real challenger to `LTX` locally
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@@ -13,7 +13,7 @@
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2. `zimage`
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3. `ltx`
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4. `minimax`
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4. category masters in:
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5. category masters in:
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- `image-edit`
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- `image-to-video`
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- `text-to-video`
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@@ -0,0 +1,42 @@
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# Optimization Review 2026-08-08
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## Scope
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First manual optimization pass before the Sunday cadence has enough historical material to build from.
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## Created masters
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- `optimized/text-to-image/zimage-turbo-3070-fast-start/`
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- `optimized/image-edit/zimage-turbo-3070-inpaint-start/`
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- `optimized/image-edit/flux2klein-9b-fp8-edit-master/`
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- `optimized/image-to-video/ltx23-3070-simple-master/`
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- `optimized/text-to-video/minimax-h3-3070-turbo-master/`
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## Source workflows used
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- `models/zimage/z-image-turbo-official-example/`
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- `models/zimage/z-image-turbo-inpainting-community/`
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- `models/flux2klein/image-edit-9b-distilled/`
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- `models/ltx/ltx23-i2v-t2v-simple-single-pass/`
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- `models/minimax/minimax-h3-turbo-lora-community/`
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## What was optimized in this pass
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- Chose low-complexity or speed-first baselines instead of heavier graphs.
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- Aligned `flux2klein` with Chris's `9B fp8` preference.
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- Treated `LTX` and `MiniMax` as "prove viability first" families.
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- Added durable notes so future passes can build on judgments instead of re-reading everything.
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## What was deliberately not done
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- no graph surgery without testing
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- no blind node removal
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- no fake "one workflow to rule them all" claims
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- no promotion of first-last-frame or INT8 reference-video paths to default status yet
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## Monday proof needed
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- whether the two `Z-Image` masters are actually lighter and pleasant to use
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- whether `flux2klein 9B distilled` behaves well enough for edit/outpaint work
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- whether the `LTX` simple master is viable on a `3070`
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- whether `MiniMax Turbo` is practically usable or still too tight
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@@ -1,3 +1,7 @@
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# Text-to-Image Masters
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Home for maintained category masters focused on text-to-image generation.
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## Current masters
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- `zimage-turbo-3070-fast-start`
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@@ -0,0 +1,61 @@
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# Z-Image Turbo 3070 Fast Start
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## Summary
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Best current `text-to-image` starter for a lighter local box.
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This master stays close to the official `Z-Image Turbo` example because that is still the cleanest and most portable `Z-Image` graph in the repo.
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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.png`
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- Load it by dragging the PNG into ComfyUI.
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## Built from
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- `models/zimage/z-image-turbo-official-example/`
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## Why this is the current master
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- Official source beats community guesswork for a first baseline.
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- `Z-Image Turbo` looks like one of the strongest fast-image candidates for a `3070`.
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- The graph is simple enough to troubleshoot without drowning in custom-node noise.
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## What I intentionally kept
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||||
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- Official model wiring
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- Official `qwen_3_4b` text encoder path
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- Embedded PNG workflow format for easy import
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## What I intentionally did not add yet
|
||||
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- community patch nodes
|
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- extra control branches
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- reference-image complexity
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- "magic" speed hacks without proof
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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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||||
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||||
- none beyond current official Comfy support
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## Monday test checklist
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||||
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||||
- Confirm it imports cleanly from PNG on your current Comfy build.
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- Check whether it really feels lighter than your usual FLUX path.
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- Check whether prompt adherence is good enough to justify keeping it as the `fast-start` master.
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## Next optimization candidates
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- merge in useful edit/reference ideas from the community `Z-Image` graphs
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- build a stronger prompt preset if the base graph is good but inconsistent
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Binary file not shown.
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@@ -1,3 +1,7 @@
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# Text-to-Video Masters
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Home for maintained category masters focused on text-to-video generation.
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||||
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||||
## Current masters
|
||||
|
||||
- `minimax-h3-3070-turbo-master`
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# MiniMax H3 3070 Turbo Master
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||||
## Summary
|
||||
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||||
Best current `MiniMax H3` speed-first starter for local text-to-video tests.
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||||
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||||
This master is built from the community Turbo LoRA workflow because standard MiniMax paths are too expensive to be the first serious attempt on a `3070`.
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||||
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## Status
|
||||
|
||||
- `best-current`
|
||||
- `not-yet-tested-on-chris-box`
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||||
|
||||
## Workflow asset
|
||||
|
||||
- `workflow.json`
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|
||||
## Built from
|
||||
|
||||
- `models/minimax/minimax-h3-turbo-lora-community/`
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||||
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||||
## Why this is the current master
|
||||
|
||||
- Explicitly optimized for lower step count
|
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- Much more aligned with your hardware than generic official baselines
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- Clear developer guidance exists for key settings
|
||||
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||||
## What I intentionally kept
|
||||
|
||||
- Turbo LoRA route
|
||||
- `8`-step recommendation from the source notes
|
||||
- `euler` sampler direction
|
||||
- MiniMax acceleration helpers already wired in the graph
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||||
|
||||
## What I intentionally did not add yet
|
||||
|
||||
- INT8 reference-video complexity from the separate community workflow
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||||
- extra latent upscale stages
|
||||
- broad claims that MiniMax beats `LTX` before we see real results
|
||||
|
||||
## Required custom nodes
|
||||
|
||||
- MiniMax-compatible Comfy support
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||||
- `ComfyUI-KJNodes`-style helper nodes present in the graph
|
||||
- optional acceleration stack may include SageAttention, Sol Attention, Gradient, and Spectrum support
|
||||
|
||||
## Expected source model route
|
||||
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||||
- Turbo LoRA source notes recommend:
|
||||
- `minimax_h3_turbo_v4_step600_ema_pruned_comfyui.safetensors`
|
||||
- `8` steps
|
||||
- `euler`
|
||||
- `beta`
|
||||
- LoRA strength `1.0`
|
||||
|
||||
## Monday test checklist
|
||||
|
||||
- Confirm whether all MiniMax helper nodes resolve.
|
||||
- Try the source-recommended settings before changing anything.
|
||||
- Judge whether this is merely "possible" or actually practical on your box.
|
||||
|
||||
## Next optimization candidates
|
||||
|
||||
- merge proven low-VRAM ideas from the INT8 R2V workflow
|
||||
- split out an `image-to-video` MiniMax master if the family proves worth keeping
|
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