using 4090, 8 steps - 14 sec - 12 imagesreduce batch size if you have a lower GPUI know the workflow is messy Updated on the workflow of Capybara's SDXL Workflow v1.4<a target="_blank" rel="ugc" href="https://civarchive.com/user/capybara_paws">capybara_paws </a>you will need:<a target="_blank" rel="ugc" href="https://huggingface.co/collections/latent-consistency/latent-consistency-models-loras-654cdd24e111e16f0865fba6">LCM lora </a>- <a target="_blank" rel="ugc" href="https://huggingface.co/latent-consistency">Latent Consistency team</a>Advanced Enhancer XL LoRA <a target="_blank" rel="ugc" href="https://civarchive.com/user/Z_phyr">Z_phyr</a>Add More Details - Detail Enhancer <a target="_blank" rel="ugc" href="https://civarchive.com/user/Lykon">Lykon</a>models used as base Cardos XL v1 <a target="_blank" rel="ugc" href="https://civarchive.com/user/charsheetanon">Charsheetanon</a>as refiner NightVision XL - Photorealistic 0.7.7.0 <a target="_blank" rel="ugc" href="https://civarchive.com/user/socalguitarist">Socalguitarist</a>

LCM Hyperloop - 8 steps - 14 sec - 12 images

images of 1536 x 2688 in 63 seconds!updates: much better output qualityWe added a model merge, which improved the output quality, and now model options are not restricted to Cardos and Nightvision; other models are getting good results as well.the work flow is now is 10 steps instead of 8, i have seen differency between my GPUs, one does better with 8 steps "4-4" the other does better with 10 "5-5" 2 IP adapters are now IPadapter Plus, and "IPAdapter Plus Face" is separate, having its own nodeAdded 1 additional "Apply node" for for each IP Adapeter to have more control over the Base model and refiner model IPadapter weight I forgot to name the "apply nodes for IP Adapters Base and Refiner, The base model control on top, the refiner model control is below. To improve the speed, change the save image nodes in the work flow to the standard save image node; it will improve at least 16+ seconds for 6 images.This version's Batch size reduced to 6 images, with an image size of 768x1344, then upscaling to 1536x2688SDXL Upscaling using RTX4090(1536x1536 upscale size, not image size) took 63 seconds for 6 images, double the SDXL recommended size (1024x1024 upscale size, not image size) took 81 secondsfor 6 images, double the SDXL recommended size 12 images in 2 minutes and 1.4 seconds! 1536x2688....<pre><code>Canva size: 1536x2688
Image size: 768x1344
Scale factor: 2
Upscaling iteration 1 with scale factor 2
Tile size: 1536x1536
Tiles amount: 2
Grid: 2x1
Redraw enabled: True
Seams fix mode: NONE
Requested to load SDXL
Loading 1 new model
100%|████████████████████████████████████████████████████████████████████████████████████| 4/4 [00:16&lt;00:00, 4.11s/it]
Requested to load SDXL
Loading 1 new model
100%|████████████████████████████████████████████████████████████████████████████████████| 4/4 [00:16&lt;00:00, 4.12s/it]
Prompt executed in 121.74 seconds</code></pre>SD1.5 Upscaling:I didn't do the speed test as i am still working to improve it

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