This is my "Ultimate" SDXL workflow. After about a year of messing around with SDXL checkpoints. This is what i've sort of landed with that has a good balance of quality and speed. 3 minutes from 0 to 2721x6167 that...
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Intro
This is my "Ultimate" SDXL workflow. After about a year of messing around with SDXL checkpoints. This is what i've sort of landed with that has a good balance of quality and speed. 3 minutes from 0 to 2721x6167 that blows the doors off Flux. It tries to push SDXL to the max in terms of detail and resolution trying to match FLUX. Tons of great SDXL models that I wish had the clean Flux look. You can make stuff that looks VERY close to Flux by using alot of these great extentions that in my opinion put SDXL on Meth. Some of this stuff is very obscure and most workflows are overly bloated with nonsense. Hopefully this is something that you can just expand on as a base.
QuickStart
Everything is initially setup for pure text-to-image. Enter a prompt and hit queue. Example prompt is provided.
AI-generated commentary
AI-generated explanation based on source and configuration details. Suggestions are clearly labeled.
SDXL Ultimate 16 MegaPixel is an SDXL workflow for generating images from text prompts or refining images through image-to-image and depth-controlnet modes, with tiled stages described at 2MP, 8MP, and 16MP.
For a first pass, enter a prompt and queue the workflow; enable the image-to-image or depth-controlnet group for those modes.
The described sequence develops composition and cleanup around 2MP, then continues through tiled 8MP and 16MP stages.
Inputs include text prompts, with image-to-image and depth-controlnet modes described as additional options.
Outputs are generated or refined images, with the described stages reaching 2MP, 8MP, and 16MP.
It is listed as a Workflows item, uses SDXL 1.0 as its base model, and is published by Smeks.
The listed model files are 4x_foolhardy_Remacri.pth; longclip-L.pt; sdxl_lustify_endgame.safetensors; and sdxl_tile_realistic_v2_fp16.safetensors.
Named workflow components include ACN_TimestepKeyframeInterpolation; RandomNoise; SamplerCustomAdvanced; Anything Everywhere3; LayerMask: LoadFlorence2Model; Seed Everywhere; VAEEncode; easy imageListToImageBatch; Anything Everywhere; VAEDecode; PerturbedAttention; MarkdownNote;
Other named workflow components include BasicScheduler; Power Lora Loader (rgthree); Image Save; TTP_Image_Tile_Batch; SetNode; UpscaleModelLoader; ApplyFBCacheOnModel; TiledDiffusion; ControlNetLoader; TTP_Image_Assy; Any Switch (rgthree); CheckpointLoaderSimple; DynSamplerSelec
SeaArtLongXLClipMerge is described as extending the clip limit from 77 to 248 tokens.
For conditional merges, put the conditioning in one prompt with BREAK separators; a PerturbedAttention setting of 1.5–2 is listed.
Suggestion · not verified
The description specifies 30% denoise at 8MP and 16MP for the described “defogging” and “sharpening” stages.
Before running it, confirm that the listed files and components are available in your setup.
Suggestion · not verified
Before tiled stages, aim for nearly perfect composition with few major artifacts, and be ready to adjust conditioning and CFG ramping for the model you use.
Suggestion · not verified
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Sources
1 sourceSource excerpts
1 excerptSource context: 703 downloads · Type Workflows · Base model SDXL 1.0
Optional Stuff
Everything is setup to do depth-controlnet or image-to-image without messing with anything. Just enable the following group and go.
image-to-image
depth-controlnet
Advanced
There are many knobs to tweak. Honestly, you'll have to experiment and see what does what, but breifely I think its worth at least noting from my experience most important bits.
SeaArtLongXLClipMerge All SD checkpoints have a clip limited to 77 tokens and so this patches any clip to 248 tokens allowing alot more detailes. Actual human readable prompts work with it much better similar to flux but it's still very limited. Each tile can hold 248 tokens generated from Florence + base prompt which gives unbelevable results at high tile counts.
Clip Text Encode with BREAK This in conjuction with the long clip merge node gives alot of new possibilities and simplifies a ton of noodles around conditioning. Conditional merges are all in one prompt seperated by the BREAK.
CLIP NegPip + PerturbedAttentionGuidance This definetly helps cleanup the image alot. Generations are much more coherent and make sense. Alot of artifacting goes away by simply having these enabled. A setting of 1.5-2 is about all you really want.
Dynamic Sampler + Detail Daemon I have all this setup how i want but you may want to experiment, but these dynamic samplers push alot more refined + smooth details out of the image almost like flux. Honestly you dont even need to pass the image through Flux because it looks that clean.
Conclusion
Basically steps 1 and 2 are the primers for the actual tiling steps 3 and 4. The image has to be nearly perfect in composition and mostly free from any major artifacting before going into tiling. Step 1 tries to just get a good composition and you may have to change around conditioning and CFG ramping to get a desired result depending on model used etc. Step 2 does the heavy lifting to clean up everything and 2 Mega Pixels seems to be the sweet spot with the TTPlanet Realistic Tile Controlnet before requiring full breakup into tiles. Step 3 and 4 require a nearly perfect image for them to work properly. Going to 8MP and 16MP only requires 30% denoise for "defogging" and "sharpening" everything to bring it all into focus. After 2MP the need for CFG and denoise goes away as you already have the image. It's really just a matter of massaging defects out along the way to 16MP. Thats just my perspective on it all.
Curious to see what people think and would wanna see anything that could improve on this because ive tried so many workflows in the past and nothing ever seemed to really go as far as this.
Requirements
Upscaler · 63.9 MB · PTH · Unknown
ImageUpscaleWithModel
PossibleUpscaler · Unknown
longclip-L.pt
Not resolvedText encoder · Unknown
sdxl_lustify_endgame.safetensors
Not resolvedCheckpoint · Unknown
sdxl_tile_realistic_v2_fp16.safetensors
Not resolvedControlNet · Unknown
UpscaleModelLoader
PossibleUpscaler · Unknown
VAEDecode
PossibleVAE · Unknown
VAEEncode
PossibleVAE · Unknown
ACN_AdvancedControlNetApply_v2
PossibleNode pack · Unknown
ACN_ScaledSoftControlNetWeights
FoundNode pack · Unknown
ACN_TimestepKeyframeInterpolation
FoundNode pack · Unknown
Any Switch (rgthree)
Node pack · Unknown
Anything Everywhere
FoundNode pack · Unknown
Anything Everywhere3
FoundNode pack · Unknown
ApplyFBCacheOnModel
Not resolvedNode pack · Unknown
BasicGuider
Not resolvedNode pack · Unknown
BasicScheduler
PossibleNode pack · Unknown
CheckpointLoaderSimple
PossibleNode pack · Unknown
CLIPTextEncodeBREAK
FoundNode pack · Unknown
ControlNetLoader
PossibleNode pack · Unknown
DetailDaemonSamplerNode
FoundNode pack · Unknown
DynSamplerSelect
FoundNode pack · Unknown
easy imageBatchToImageList
FoundNode pack · Unknown
easy imageListToImageBatch
FoundNode pack · Unknown
Empty Latent by Pixels (WLSH)
FoundNode pack · Unknown
Fast Groups Muter (rgthree)
Not resolvedNode pack · Unknown
GetNode
Not resolvedNode pack · Unknown
Image Comparer (rgthree)
Not resolvedNode pack · Unknown
Image Save
FoundNode pack · Unknown
ImageScaleToTotalPixels
PossibleNode pack · Unknown
JoinStrings
PossibleNode pack · Unknown
KSamplerSelect
PossibleNode pack · Unknown
Node pack · Unknown
Node pack · Unknown
MarkdownNote
Not resolvedNode pack · Unknown
Node pack · Unknown
Power Lora Loader (rgthree)
Not resolvedNode pack · Unknown
PreviewImage
PossibleNode pack · Unknown
RandomNoise
Not resolvedNode pack · Unknown
SamplerCustomAdvanced
Not resolvedNode pack · Unknown
ScheduledPerpNegCFGGuider //Inspire
PossibleNode pack · Unknown
SeaArtLongXLClipMerge
FoundNode pack · Unknown
Seed Everywhere
FoundNode pack · Unknown
SetNode
Not resolvedNode pack · Unknown
ShowText|pysssss
FoundNode pack · Unknown
Text Multiline
FoundNode pack · Unknown
TiledDiffusion
PossibleNode pack · Unknown
TTP_Image_Assy
FoundNode pack · Unknown
TTP_Image_Tile_Batch
FoundNode pack · Unknown
TTP_Tile_image_size
FoundNode pack · Unknown