Sdxl turbo vs sdxl turbo reddit

Sdxl turbo vs sdxl turbo reddit. 5 denoiser strength, start denoising at 0. 5 models at 10 steps at a resolution of 640x384 would only take about 20 minutes. This conclusion was drawn from extensive testing with multiple SDXL Turbo, SDXL Non-Turbo, and SD1. 9K subscribers in the fooocus community. But I can't do face swap properly anymore. I will also have a look at your discussion. Mouth open, vs mouth closed, extra. Specifically, Turbo needs as few as just 1 step, suitable for real-time applications. Best settings for SDXL-Lightning 10 step LORA (strength of 1. The image-to-image pipeline will run for int(num_inference_steps * strength) steps, e. Details tend to get lost post-inpainting! This first caught my attention while using Adetailer for facial enhancements in combination with XL and XL Turbo models. Using SDXL 1. Today, we herald a superior and swifter checkpoint: SDXL Lightning. But it also seems to be much less expressive, and more literal to the input. Question - Help. The way SSD-1B scores higher than SDXL makes me think the simulacra aesthetic model or similar was used in the distillation process. Sampling method on ComfyUI: LCM. You can test SDXL Turbo on Stability AI’s managed to do it with a regular ksampler using Euler-a and sgm-uniform at 1cfg. Someone else on here was able to upscale from 512 to 2048 in under a second SDXL was never behind. Lighting needs more steps, whatever they have implemented there for 1 step seems useless to me most of the time regardless if generating photo or some art. 0 version of SDXL. However, it comes with a trade-off of a slower speed due to its requirement of a 4-step sampling process. 1), SDXL boasts remarkable improvements in image quality, aesthetics, and versatility. SDXL can also be fine-tuned for concepts and used with controlnets. Thanks! Well, this post got six upvotes (which I take as a sign that other You can encode then decode bck to a normal ksampler with an 1. 5 seconds at the 25 steps). Toggle if the seed should be included in the file name or not. So yes. 2 denoise to fix the blur and soft details, you can just use the latent without decoding and encoding to make it much faster but it causes problems with anything less than 1. 34. 1 for speeed. My system limits me with the SDXL models, is it possible to use this Turbo workflow with SD 1. Hardware Limitations: Many users do not have the hardware capable of running SDXL at feasible speeds. But the point was for me to test the model. 5 output is about 512px x 512px with an upscale process afterwords. 5 models. Though there is some evidence floating about that the refiner quality boost over the base sdxl might be negligible, so it might not make that much of a difference. 📷 All of the flexibility of Stable Diffusion: SDXL is primed for complex image design workflows that include generation for text or base image, inpainting (with masks), outpainting, and more. In your case you could just as easily refine with SDXL instead of 1. In most cases this process run pretty fast even on older PCs. . Step 3: Update ComfyUI Step 4: Launch ComfyUI and enable Auto Queue (Under Extra Options) Step 5: Drag and drog and sample image into ConfyUI Step 6: The FUN begins! If queue didn't start automatically, press Queue Prompt So, I need a little bit of help/guidance on LoRa training for SD 1. Speed is the main issue, but even that has been resolved with Turbo & Lightning. to use you need: Switch your A1111 to the dev branch (recomended use new or copy your A1111) - into your A1111 folder run CMD and write: "git checkout dev" and press ENTER. thanks, I'll check it out, some people were using turbo combined with sd1. Then I tried to create SDXL-turbo with the same script with a simple mod to allow downloading sdxl-turbo from hugging face. 9 gb) I want to assume the 'fp16' stands for floating point 16, but I'd rather hear from someone who actually knows. SDXL Lightning can adjust its speed with more steps for better Maturity of SD 1. Fuck SD 1. I used seed 1000000007, lcm sampler and sge_uniform scheduler. from diffusers. 0. "sd_xl_turbo_1. 5 models and LoRAs? I'm using Comfy, so if anyone got a workaround, I would like to know. (The match changed, it was weird. (released in july 2023). 1. When it comes to the sampling steps, Dreamshaper SDXL Turbo does not possess any advantage The use-case for Turbo for people like me, who strive for quality above all is not yet fully clear to me. Download custom SDXL Turbo model. from diffusers import AutoPipelineForImage2Image. For example: Phoenix SDXL Turbo. But since I have something of an aging system I was wondering if my problem lies elsewhere or if I am just using two things that are not Which might help with the mouth. It's manageable. 5-3. next, UniPC for both first and second sampler, 30 steps first pass, 20 second, 0. And both of them have very small context windows so the render time increases a lot. I'd estimate 15-20 seconds an image for SDXL Turbo on my CPU, but I've not tried it yet. LCM LoRA is much easier though and is model agnostic. For researchers and enthusiasts interested in technical details, our research paper is Sort by: chimaeraUndying. 1. Running A1111 with recommended settings (CFG 2, 3-7 steps, R-ESRGAN 4x+ to upscale from 512 to 1024). (longer for more faces) Stable Diffusion: 2-3 seconds + 3-10 seconds for background processes per image. You can try to use GuernikaModelConverter to convert DreamShaper-Turbo or TurboVision. I was wondering if the community has noticed, that SDXL and XL Turbo models are very bad at inpainting. 0, trained for, per Stability AI, “real-time synthesis” – that is – generating images extremely quickly. When it comes to the sampling steps, Dreamshaper SDXL Turbo does not possess any advantage over LCM. utils import load_image. Has 5 parameters which will allow you to easily change the prompt and experiment. These are pretty For normal img2img2, the choice of scheduler and sampler make a huge difference and it is quite conter-intuitive. I was thinking that it might make more sense to manually load the sdxl-turbo-tensorrt model published by stability. 5-based models, Realistic Vision is still the best. Dune is a landmark science fiction novel first published in 1965 and the first in a 6-book saga penned by author Frank Herbert. This community will support you through your AI journey. Also, don't bother with 512x512, those don't work well on SDXL. safetensors" (13. 5 has been superseded for all uses by various fine-tunes. SDXL-Turbo out 🚀by combining the some of the greatest ingredients in generative modeling - diffusion, score-distillation and adversarial training, enabling single-step image generation with unprecedented quality No really but appears in info. 6 and 0. CFG Scale: from 1 to 2. Please post your photos and videos. After the SD1. 5 step: At least 12 steps SDXL Turbo achieves state-of-the-art performance with a new distillation technology, enabling single-step image generation with unprecedented quality, reducing the required step count from 50 to just one. 5 for bringing more quality and details. I use it with 5 steps and with my 4090 it generates 1 image at 1344x768 per 1 second. 0 = 1 step in our example below. So far I've just tested this with the Dreamshaper SDXL Turbo model, but others are reporting 1-2 seconds per image, if that. 5 is the amount of LORAs and specialized models that are available. 5 models noticeably enhances the skin's details and imperfections. 0, SDXL Turbo features the enhancements of a new technology: Adversarial Diffusion Distillation (ADD). We propose a diffusion distillation method that achieves new state-of-the-art in one-step/few-step 1024px text-to- image generation based on SDXL. Yes, mm_sdxl and hotspot, I coudn't get results close to what I can obtain with the SD1. See you next year when we can run real-time AI video on a smartphone x). It might also be interesting to use, CLIP, or YOLO, to add tokens to the prompt on a frame by frame bases. For this video I used 4 steps, CFG set to 2. •. I was using the Euler A sampler. Install the TensorRT plugin TensorRT for A1111. Live drawing. In this paper, we discuss the theoretical analysis, discriminator design InvokeAI natively supports SDXL-Turbo! To install SDXL-turbo, just drop the HF RepoID into the model manager and let Invoke handle the installation. Dreamshaper SDXL Turbo is a variant of SDXL Turbo that offers enhanced charting capabilities. I have also compared it against SDXL Turbo and LCM-LoRA . 5. A place for you to showcase India's incredible beauty through generative AI. With SDXL picking up steam, I downloaded a swath of the most popular stable diffusion models on CivitAI to use for comparison against each other. The original sdxl-turbo could do 1 step, but peaked at 4. So what are the parameters used for SDXL? Please post it for image #1 (CFG, steps, sampler, etc) This image is generated using CFG:7, Step: 30, Sampler: DPM++ 2M Karra. While not exactly the same, to simplify understanding, it's basically like upscaling but without making the image any larger. The main features are: Works with SDXL, SDXL Turbo as well as earlier version like SD1. For realistic SDXL-based models, I’d say either RealVisXL or Realities Edge XL. I've adapted stability's basic SDXL Turbo workflow to work with a live painting element to it (similar to the LCM LoRa one). LoRA based on new sdxl turbo, you can use the TURBO with any stable diffusion xl checkpoint, few seconds = 1 image. Nov 29, 2023 · SDXL Turbo is a newly released (11/28/23) “distilled” version of SDXL 1. Neither Turbo nor Lightning are “improved. All images were generated with the following settings: Steps: 20. In general, base 1. You can run it locally. SD 1. io on an SDXL TURBO A1111 Question - Help /r/StableDiffusion is back open after the protest of Reddit killing open API access, which will bankrupt app developers, hamper For realistic 1. Sd xl is way easier to use than 1. 5 examples were added into the comparison, the way I see it so far is: SDXL is superior at fantasy/artistic and digital illustrated images. In addition to that, I checked out the CivitAI one too, and there it has a 'pruned' version that is 6. Hyper SDXL is the latest entrant, promising even more enhancements. Although, 1. The code, research paper, and weights for non-commercial use are now available on our website. SDXL Turbo is the fastest, taking just one step to finish the race. ai. Or check it out in the app stores SDXL HK 0. SDXL-Lightning is spectacular! Is not a new model, but a new method! For anyone who wants to know more, I've written an article explaining how it works, what improvements it brings and what is the best way to use it to get the most out of it. Download the workflow here r/desmos. The lower the steps, the closer to the original image your output Go civitai download dreamshaperxl Turbo and use the settings they say ( 5-10 ) steps , right sampler and cfg 2. Try denoise between 0. Abstract. On some of the SDXL based models on Civitai, they work fine SDXL Turbo is part of the core SAI model set so my bet is on that. And I'm pretty sure even the step generation is faster. Step 2: Download this sample Image. Adding --lowvram lowers this to ~7. SDXL Turbo has arrived! • Today, StabilityAI has released an exciting key text-to-image model featuring their latest advancements in GenAl technology: SDXL Turbo! • Built on the same technological foundation as SDXL 1. '. Summary: Subjectively, 50-200 steps look best, with higher step counts generally adding more detail. DB on best mix checkpoints inherits their mistakes that lead to overstrain but not to fix that mistakes. How fast should SDXL turbo run with default ComfyUI workflow (1step/cfg1,512x512) on a rtx 2070 super with 8gb of VRam? Because it takes about 3. SD1. I also opensourced the code. Major Inpainting Issues with SDXL & XL Turbo. Anyone have ComfyUI workflows for img2img with SDXL Turbo? If so, could you kindly share some of your workflows please. 0, and 2. 5GB of VRAM, but execution time is drastically increased to 2000-2500ms. Tested on ComfyUI: workflow. It’s a toss up between a checkpoint and a LoRA so, in all fairness, it’s not an ideal comparison. 5 it's ancient now and SDXL Turbo seems more promising and better efficiency that SD 1. 0. I was unable to use SDXL with my 3070 in A1111, just like you. I personally prefer sdxl, it seems better straight up. Reply. I used to get 3 to 6 minutes an image on my CPU (5900X) On a low to mid range GPU (RX7600) I can get 20 to 30 secs per image. ago. 16GB 3060Ti vs 12GB 3070 for SDLX and SDXL Turbo? Question - Help I currently have a 1660 super (and have to use -lowvram and get around 9s/it) and am looking to upgrade and I was wondering how the 16GB 4060Ti compares to the 12GB 4070. Yep. For the base SDXL model you must have both the checkpoint and refiner models. A big plus for SD 1. Most people are just upscaling to get the highest quality. SD Turbo - Distilled SD 2. 3. 80% will look weird, but it's good to see it. x models are 640px² or 768px² or something. The main difference (for you) is what resolution they output at - XL models' optimal resolution is 1024px²; 1. I've managed to install and run the official SD demo from tensorRT on my RTX 4090 machine. Merges with sdxl-turbo generally do 4-8. There are many great SDXL models doing superb job with photorealism and people. The "original" one was sd1. This is a nice post! It's amazing how fast this model is. 9, ddim-uniform scheduler, 3-4 steps and cfg 1. Decided to create all 151. FP8 is marginally slower than FP16, while memory consumption is a lot lower. Cascade will be the new king of SD image generators, but its not perfect yet, still needs many more months to cook in the opensource community. I found dreambooth on base SDXL is slow. Please share your tips, tricks, and workflows for using this…. 46gb, and a full version that is 12. 5 and XL are not compatible, but was wondering if XL and Turbo are. 9 to 1. The current version is compatible with SDXL-Turbo. Feel free to post demonstrations of interesting mathematical phenomena, questions about what is happening in a graph, or just cool things you've found while playing with the calculator. Sampler: DPM++ 2M Karras. This same pattern might apply to LoRAs as well. Even with a mere RTX 3060. To me it seems that SDXL Turbo gets the best realistic images, Hyper is always looking like a painting. I didn't expected my generation to be as fast as in the YT Tutorials but at least 1 image per SDXL can run on CPUs, yes. ” The whole point of using them is the speed, not quality. 6 seconds (total) if I do CodeFormer Face Restore on 1 face. balianone. You know when you sit down for a meal in front of the computer and you just need something new to watch for a bit while you eat? If you search /r/videos or other places, you'll find mostly short videos. If you have any experience, I'd be happy to hear. It’s based on a new training method called Adversarial Diffusion Distillation (ADD), and essentially allows coherent images to be formed in very few steps The workflow of connecting real-time and Fully customizable is going to be ready. Add your thoughts and get the conversation going. I mean if real hands are a 10 and SDXL is a 1 then Cascade is 1. Instead of the latent going to the stage B conditioner, instead VAE decode using stage C. 0 denoise, due to vae, maybe there is an obvious solution but i don't know it. 5: The current version of SDXL is still in its early stages and needs more time to develop better models and tools, whereas SD 1. 17K subscribers in the comfyui community. As an upgrade from its predecessors (such as SD 1. Install the TensorRT fix FIX. SDXL Lightning ⚡: A Swift Advancement Over SDXL Turbo. g. Nice. Batch of 8 averaged. Honestly I use both. It took around an hour to render a minute's worth of video. 0 on a 4GB VRAM card might now be possible with A1111. Welcome to the unofficial ComfyUI subreddit. Now, You can access some shortcuts of your personal workflow inside of Photoshop! I am also working on the SDXL Turbo model for the next updates. Nov 28, 2023 · SDXL Turbo is based on a novel distillation technique called Adversarial Diffusion Distillation (ADD), which enables the model to synthesize image outputs in a single step and generate real-time text-to-image outputs while maintaining high sampling fidelity. 27 it/s. 5 as a refiner so this may have a place in the pipeline too, since I'm sure sd2. Then a pass of 1. 5 * 2. FP8. 1 step turbo has slightly less quality than SDXL at 50 steps, while 4 step turbo has significantly more quality than SDXL at 50 steps. --. 93 seconds. It seems pretty clear: prototype and experiment with Turbo to quickly explore a large number of compositions, then refine with 1. 5 course it understands what you want with short prompt. No need to reprompt. But still, lots of requests for SDXL despite its licensing. At this moment I tagged lcm-lora-sd1. 5 with lcm with 4 steps and 0. Widely considered one of the greatest works within the sci-fi genre, Dune has been the subject of various film and TV adaptations, including the Academy Award winning 2021 film Dune directed by Denis Villeneuve. r/desmos. 5 had where the community developed other components that were added after the fact. For turbo it was 4 steps and LCM it was 6 steps. Follow the parameters: sampler: EulerA CFG: 1. Image quality looks the same to me (and yes: the image is different using the very same settings and seed even when using a deterministic sampler). 5 from nkmd then i changed model to sdxl turbo and used it as base image. This is using the 1. SDXL is superior at keeping to the prompt. A bit similar as you can't train TI on checkpoints except of base. 1 had something unique about it that XL didn't manage to copy. This is the unofficial Subreddit for the open source AI image generation software known as Fooocus! Ask…. I played with it all night, quality is surprisingly good. The average score for each prompt was subtracted from the score for each image. Base SDXL can also still do interesting stuff. I was testing out the SDXL turbo model with some prompt templates from the prompt styler (comfyui) and some Pokémon were coming out real nice with the sai-cinematic template. 10K subscribers in the comfyui community. 6 days ago · SDXL Turbo is known for its speed, creating images in a single step, while SDXL Lightning offers a balance between speed and quality with options. As far as the models themselves, SDXL was immediately better in most ways than SD 1. Animatediff could be cool. /r/StableDiffusion is back open after the protest of Reddit killing open API access, which will bankrupt app developers, hamper moderation, and exclude blind users from the site. 8GB of VRAM and takes ~450ms to execute. I'm running a 3090 24g locally and I have a good image dataset (100 images captioned), but I keep on getting pretty garbage results. They have some flaws like being barely affected by negative prompts, but they let you generate at fewer steps with a similar level of quality. 1 seconds (about 1 second) at 2. The SDXL is excelling all expectations in so many ways in so many areas, but feels like SD Best settings for SDXL base generation NO speed LORAS = DPM++ 3M SDE Exponential sampler at 25-40 steps with a CFG of 5. With ComfyUI the below image took 0. I might test a lower denoise, but I remember it looking bad. SDXL for better initial resolution and composition. Nice hair piece! Doesn't look like an improvement to me. FYI it is completely free on my website! doesnt cost a thing. 9 TURBO Resource - Update Share Sort by: Best. This is a huge moment for real-time generation application! Get the Reddit app Scan this QR code to download the app now Impressed with locally run SDXL Turbo results - 4 steps, 10 seconds an image in odysseyapp. Do you have any tips? 2. The render-as-you-type workflow is pretty fun. 5 still wins on usability though, XL has longer generating times and models take up far more space. Our method combines progressive and adversarial distillation to achieve a balance between quality and mode coverage. Turbo actually sucks as LCM beats it, and it doesn't hold a candle to Runway ML's motion stuff (watch a video comparing). *XL models are based on SDXL; unlabeled ones are (typically) based on non-SDXL models (SD 1. Which is funny because I sorta forgot about lllite after it released, because cnet seems to do much better with traditional sdxl models (I assume because of either the step count or cfg, but maybe it's something intrinsic to the turbo architecture? For general use I always find it hard to go back to using 1. Upscale to 2x and 4x in multi-steps, both with and without sampler (all images are saved) Is the SDXL Turbo compatible with the SDXL's Lora model, or is there a need to train a new Lora , For SDXL Turbo is optimized for a resolution of 512, whereas the SDXL's Lora model is designed for 768 or higher. I set it to render 20fps at a resolution of 1280x768. 5 because inpainting. x ones). Reason I ask is because at least in one case it seems that using a XL LoRA with DreamshaperXL seems to hang up my system. Some of these features will be forthcoming releases from Stability. Turbo needs a range of 50% to 80% denoise for latent upscaling using the same seed number. Despite experimenting with various Adetailer settings – including adjustments to resolution, steps, denoising Didn’t dos lot of testing though. It is specially designed for generating highly realistic images, legible text, and LCM gives good results with 4 steps, while SDXL-Turbo gives them in 1 step. In late 2023, SDXL Turbo made its debut. 5 after using XL for a while. TLDR: Results 1, Results 2, Unprompted 1, Unprompted 2, links to checkpoints used at the bottom. A CFG of 7-10 is generally best, as going over will tend to overbake, as we've seen in earlier SD models. SDXL is a new checkpoint, but it also introduces a new thing called a refiner. BasedEvader. On the other hand, the combination of Adetailer with SD1. Although there are even more SD 1. Its extremely fast and hires. What you see as "behind" was simply the length of time SD 1. I'm using optical flow for movement. Refiner has not been implemented yet in Automatic1111. Discussion. Every other single combination I've tried has produced at best Start with Cascade stage C, 896 x 1152, 42 compression. SDXL Turbo Fine tune/Merging? I didn't found any method to training SDXL model. play around with the denoise to see what its best for you. 5 to achieve the final look. Dreamshaper SDXL Turbo VS Dreamshape SDXL with LCM. Adding --novram instead lowers this further to ~2. The ddim-uniform is really special with img2img turbo, I have the best result with it. It might be another way to handle details like eyes open, vs closed. • 3 mo. Sure, some of them don’t look so great or not at all like their original design. Open SDXL SDXL-Turbo is a non-commercial license. TensorRT compiling is not working, when I had a look at the code it seemed like too much work. 5 is superior at human subjects and anatomy, including face/body but SDXL is superior at hands. x and the vanishingly rare 2. Prompting and the refiner model aside, it seems like the fundamental settings you're used to using Stability AI recently introduced its advanced one-step image generation model, SDXL-Turbo. 92gb. 5, 2. Doing this on my RTX 4070 uses ~8. 5 and appears in the info. The image we get from that is then 4x upscaled using a model upscaler, then nearest exact upscaled by ~1. Step 1: Download SDXL Turbo checkpoint. Nvidia EVGA 1080 Ti FTW3 (11gb) SDXL Turbo. The standard resolution for 1. Get the Reddit app Scan this QR code to download the app now. 0) = DPM++ 2M SDE SGMUniform sampler at 10 steps and cfg of 2. 5 is way better at producing women with really, really big boobs, which I need in my 'work. I know that SD 1. SDXL Turbo on my GPU takes me to around 1sec per image. But I have not checked that yet. The best methods available or the easiest way to train a LoRa for these particular models. (generation time of a 1024x1024 image is 3. 5 AnimateDiff models. x models are 512px²; I think 2. On the AI Horde, SDXL is the second most requested model after Anything Diffusion (people gotta have their waifus I guess). Same settings for upscaling. If more fine-tuned turbo checkpoints keep showing up on Civitai then I think you can safely predict that the future belongs Stable Diffusion XL (SDXL) is a state-of-the-art, open-source generative AI model developed by StabilityAI. One image takes about 8-12 seconds for me. 5 does have more Loras for now. 10% improvement, still just 10% from reality. A subreddit dedicated to sharing graphs created using the Desmos graphing calculator. The most likely reason is that you used an inferior sampler, CFG, or Steps. Lightning and Turbo let you generate with a lot fewer steps. ComfyUI: 0. - Setup -. Has anyone had luck training sdxl using kohya ss (or equivalent) with the new turbo or lightning models? I'd love to train on the new dreamsharper / juggernaut xl model but I can't seem to get much out of them. Honestly you can probably just swap out the model and put in the turbo scheduler, i don't think loras are working properly yet but you can feed the images into a proper sdxl model to touch up during generation (slower and tbh doesn't save time over just using a normal SDXL model to begin with), or generate a large amount of stuff to pick and Some technicals: XL Turbo flourishes in the 5 steps 2-3 CFG range, while 1 is too muddy and 4 looks burnt. 5 LCM models (such as DreamShaper LCM) and also SDXL turbo. 19K Members 41 Online. The whole point of using them is the speed, not quality. I've tried "force" normal kohya sdxl method, but with the result is horrible (just blurry picture), and I've tried converting model into LCM using kohya so it could Feb 22, 2024 · Feb 22, 2024. Join. 2GB of VRAM, but seems to make the execution time fluctuate more, about 450-600ms. 2. Try making the switch to ComfyUI, it's easier than it looks, and way faster than A1111. 5, end denoising at 1 - Adds contrast, detail and improves the image over base. 5 models doing even more superior job with photorealism and people in particular. Hello, does anybody know any method how to combine SD Turbo and AnimateDiff? When using SDXL-Turbo for image-to-image generation, make sure that num_inference_steps * strength is larger or equal to 1. One of the generated images needed to fix boobs so I back to sd1. Seemed like a success at first - everything builds - but images are wrong You need to use --medvram (or even --lowvram) and perhaps even --xformers arguments on 8GB. 5 seconds for me for a single image, which really defeats the purpose of the turbo model. Sampling steps: 4. I feel like there should be a base model set to a couple steps for a baseline in the YMMV, but I've found lllite actually works loads better than cnet with turbo models. This I finally came up with a setting that actually does give a positive output in SD. SD XL is quite new. 5 is very mature with more optimizations available. gw ae lw ev mp gf kj zn oi xo