Today Stability. Oh yeah. Closes in 3 days. I'm imagining some vision LLM model + lineart controlnet with stable diffusion turbo model with custom UI on top of (or maybe as a node of) comfyui could do it. Live drawing. g. Woman Lying On Grass Comparasion - SD3 vs SDXL vs SDXL Turbo vs Dreamshaper XL Lighting vs Juggernaut X vs Stable Cascade vs EpicRealism 5 vs SD 1. 5 does have more Loras for now. 27 it/s 1. This UI is so simple and efficient. You can use almost any advanced function offered by SD, just need to wait a bit. Tried it, it is pretty low quality and you cannot really diverge from CFG1 (so, no negative prompt) otherwise the picture gets baked instantly, cannot either go higher than 512 up to 768 resolution (which is quite lower than 1024 + upscale), and when you ask for slightly less rough output (4steps) as in the paper's comparison, its gets slower. thanks for the comparison! /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. 8K subscribers in the SDtechsupport community. 1 seconds (about 1 second) at 2. But it also seems to be much less expressive, and more literal to the input. And I'm pretty sure even the step generation is faster. " How to test quality of sampler by steps: do an XYZ plot with both sampler and step count. 065 Stable Diffusion 3 $0. ai/license. 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. It's really cool, but unfortunately really limited currently as it has coherency issues and is "native" at only 512 x 512. ComfyUI: 0. 0_fp16. Sampling method on ComfyUI: LCM. Stable Cascade is an interesting arch by Dome since Wurstchen v3 needs to be released and uses Stability. 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. Right now, SDXL turbo can run 62% faster with OneFlow's OneDiff Optimization (compiled UNet and VAE). A1111 API with a custom made Website that allows you to change prompts in real time without typing, DreamShaper Turbo XL model Steps: 7, Sampler: DPM++ 3M SDE Karras, CFG scale: 2. SDXL-Turbo uses a new training method called Adversarial Diffusion Distillation (ADD) (see the technical report), which enables fast sampling from large-scale pre-trained image diffusion models with only 1 to 4 steps and high image quality. A real-time demo is available here: http://clipdrop. Although, 1. 03 Stable Diffusion Core $0. 3 is probably too high. Utilizing the property of the U-Net, we reuse the high-level features while updating the low-level features in a very cheap way. SDXL-Turbo is based on a novel training method called Adversarial Diffusion Distillation (ADD) (see the technical report), which allows sampling large-scale foundational image diffusion models in 1 to 4 steps at high image quality. Decided to try it out this morning and doing a 6step to a 6step hi-res image resulted in almost a 50% increase in speed! Went from 34 secs for 5 image batch to 17 seconds! I can't even look at the images fast enough. See you next year when we can run real-time AI video on a smartphone x). Open • 2 total votes. 10 CH32V003 microcontroller chips to the pan-European supercomputing initiative, with 64 core 2 GHz workstations in between. Stay tuned! Well, I personally found both very promising. Paper: "Beyond Surface Statistics: Scene Representations in a Latent Diffusion Model". Originally designed for computer architecture research at Berkeley, RISC-V is now used in everything from $0. SD-Turbo vs. SD-Turbo SDXL-Turbo SXDL Base SDXL-LCM SSD-1B LCM SSD-1B I ranked all the 2135 images I generated using the simulacra aesthetic model. The softmax operations need to keep track of multiple local variables for each input and favour speed over memory efficiency, sending all 32k batches of 40-width softmaxes to the GPU at the same time. Using the LoRA model, you can produce high-quality images very quickly with RISC-V (pronounced "risk-five") is a license-free, modular, extensible computer instruction set architecture (ISA). ai's training resources (it seems, I can be corrected), why not rename and release it? The focus has shifted to the speed of image rendering, and on the one hand this is a good thing. So yes. I have more perf tricks, but for non-commercial use, I hope the average user can handle near 150. Also the more canvas you give it to play around with the more chance it has to put crud in you might not want. So instead of x4 do a x2 then a x2 on the result. Nobody asked, but I still kind of feel pity for those who's trying to brute-force the quality by using ridiculous amounts of steps. A true "Turbo" model is never more than 4 steps -- the models like dreamshaper turbo that encourage 8-12 steps aren't "true turbo" per se, they're a mixed/merged half-turbo, getting a partial speedup without the quality reduction. These are pretty For 512x512 the cost is 2 points. (realtime typing for sd 1. 150 fast generations per day, combined in any of the following ways: (I believe this is out of date, currently even 512x512 cost 2 points) Up to 150 (768x768) generations per day. If my 70 fps demo was too slow here's 149 images per second. Getting SDXL-turbo running with tensorRT. I will test it and let you know what will happen. I've managed to install and run the official SD demo from tensorRT on my RTX 4090 machine. true. 0-2-g4afaaf8a PSA - TensorRT works with turbo models for even faster speeds. 5 to 1. I have tested several SDXL Turbo checkpoints and currently there are two I consider as keepers: Dreamshaper SDXL Turbo (absolute must-have, can deal with almost any style) and rmsdxlHybridTurboXL_orion which I use 1. I'm using optical flow for movement. safetensors" (not sure what the difference is) in the folder "StableDiffusion\webUI\stable-diffusion-webui-directml\models\Stable-diffusion. 2. ai/buy. For 512x512 the cost is 2 points. Magnific is trying to take off and marketing all over X Reply reply /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. SDXL 1. The idea here is - get decent result FAST, for ideation / exploration / testing. " But when I load one of them and try to use it, I'm not getting the super-fast performance I was expecting. Run the first section with the second section muted until you have the image you want to use them unmute the second section. Don't forget to update and restart ComfyUI! This workflow was bootstrapped together by using several other workflows, be sure /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. Blender + SDXL Turbo (just Img2Img) I rendered the animation in Blender (left) and used SDXL turbo to enhance it. 5 to generate as fast as posible -> use adapters to control geometry -> upscale with DLSR = Stable diffusion doom. Also interface should be simplistic. Then, I just waited for the magic. Is there somewhere else that should go? $0. SDXL-Turbo is based on a novel training method called Adversarial Diffusion Distillation (ADD) (see the technical report), which allows sampling large-scale foundational image diffusion models in 1 to 4 steps at high image quality. So far I've just tested this with the Dreamshaper SDXL Turbo model, but others are reporting 1-2 seconds per image, if that. One image takes about 8-12 seconds for me. It's been a couple weeks since I updated so maybe it's gone now, but for me that node is under: sampling > custom_sampling > schedulers > SDTurboScheduler. I'm glad it's there for people to make use of but I find it flows better when I completely type a long prompt (or finish drawing a sketch for sketch-to-image) then hit generate and get instant render. I didn't even use controlnet just a simple prompt, 5 steps and low strength (0. Make sure you all update ComfyUI to be able to use it! Distill good old 1. Hi guys, today Stability Inc released their new SDXL Turbo model that can inference an image in as little as 1 step. 22 in FID on ImageNet. Turbo is designed to generate 0. 0 cfg it works great. I took an unfinished old image (from one year ago) and used it as the base image with SDXL Turbo. 5 model then add the 1. SD 1. Download custom SDXL Turbo model. ago. LoRA based on new sdxl turbo, you can use the TURBO with any stable diffusion xl checkpoint, few seconds = 1 image. 6. 0 LoRa's apparently work on Turbo model as well. You still have LCM to reduce the render times. The tensor being Softmax'd is (8, 4096, 40). 0 or 2. The ability to produce high-quality videos in real time is thanks to SDXL turbo. SDXL generates images at a resolution of 1MP (ex: 1024x1024) You can't use as many samplers/schedulers as with the standard models. 1. 5 seconds so there is a significant drop in time but I am afraid, I won't be using it too much because it can't really gen at higher resolutions without creating weird duplicated artifacts. Live generation is really fun. I used touchdesigner to define initial patterns for image generation with SD-Turbo model in comfyui. 6 seconds (total) if I do CodeFormer Face Restore on 1 face. I used touchdesigner to create some initial pattern and for a constant prompt, i generated images from denoise value of 0. First part is SD result and second part (after a short stop) is SDXL result. Install the TensorRT fix FIX. 74 SDXL Turbo accelerates image generation,* delivering high-quality outputs* within notably shorter time frames by decreasing the standard suggested step count from 30, to 1! To try out the model right away, visit Stability Al's image editing platform Clipdrop, demonstrating the real-time text to-image generation capabilities! Arxiv Preprint of SD3-Turbo shows high quality images: Fast High-Resolution Image Synthesis with Latent Adversarial Diffusion Distillation Problem: SDXL Turbo is fast, but the variety of output is very limited. Please note: For commercial use, please refer to https://stability. • 5 mo. I need help understanding why when i use turbo models I get this heavy grain and wierd textures to the images, this is on dreamshaperturbo and recommends cfg 2, sample 4-8 and dmp++ karras sampler to work but I get this grain. 5 seconds to create a single frame. co/stable-diffusion-turbo. But the point was for me to test the model. x times faster which is great to the point I don't want to work with non-turbo models anymore :) But no 10 times more of course. Which might help with the mouth. The images generated using Turbo/LCM have less details, washed-up colors and less Turbo models improved that to just 4 steps at 1. It took around an hour to render a minute's worth of video. I put the files "sd_xl_turbo_1. Researchers discover that Stable Diffusion v1 uses internal representations of 3D geometry when generating an image. When it comes to the sampling steps, Dreamshaper SDXL Turbo does not possess any advantage over LCM. Is there a way to get the DPM XL Turbo sampler that Forge has, on Auto111? Search for scheduler in the Settings, switch to sgm. Even with a mere RTX 3060. Amazed. Seemed like a success at first - everything builds - but images are wrong. At the end I just removed the background from the final video. 5 doesn't have turbo models. The left is SDXL turbo and the right is SD1. Each step took 3 step. Tech support subreddit for stable diffusion Stable Diffusion 3 is on Poe! Stable Diffusion 3 and the faster SD3 Turbo are hosted by Fireworks AI, and available at SD… 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 /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. leonardo. I also realized I could add noise or project noise physically to tweak the generation result. Free plan: https://app. I'm trying to get this to work using CLI and not a UI. 🧍🏽‍♂️I’m literally emphasizing why not to. For each prompt I calculated the average aesthetic across all the methods and then subtracted that from the score of each image in that group. 003 Stable Diffusion XL $0. A prompt with a lot of different variables pretty much outputs the same… Ah I see. 0, Seed: 2263740758, Size: 1024x768, Model hash: 676f0d60c8, Model: dreamshaperXL_turboDpmppSDE, Denoising strength: 0. safetensors" and "sd_xl_turbo_1. did you load sdxl lora and used it with 1. Reply. Share. 5 lcm lora and add 1. 5 model in NMKD? it worked? "Then, I just waited for the magic. 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. Then I tried to create SDXL-turbo with the same script with a simple mod to allow downloading sdxl-turbo from hugging face. This approach uses score Make SDXL Turbo increase +62% E2E Throughput with OneDiff. 512 is too small so 1024² size is enough to get a good idea of where things are going. (longer for more faces) Stable Diffusion: 2-3 seconds + 3-10 seconds for background processes per image. 0 with each model. 2). The same may go for SD 1. Introducing UniFL: Improve Stable Diffusion via Unified Feedback Learning, outperforming LCM and SDXL Turbo by 57% and 20% in 4-step inference. Can't require typing in prompts, it should somehow know what the sketch is without typing. How is this even in the realm of possibility? automatic1111, Steps: 1, Sampler: Euler a, CFG scale: 1, Seed:, Size: 512x512, Model hash SDXL-Turbo is a fast generative text-to-image model that can synthesize photorealistic images from a text prompt in a single network evaluation. md instructions. Up to 30 upscales or unzooms per day. For example: Phoenix SDXL Turbo. 5 depth controlnet, change all the samplers to LCM, 10 steps and 1. Swapping concepts on SD Turbo. LCM gives good results with 4 steps, while SDXL-Turbo gives them in 1 step. Running A1111 with recommended settings (CFG 2, 3-7 steps, R-ESRGAN 4x+ to upscale from 512 to 1024). You can't use a CFG higher than 2, otherwise it will generate artifacts. LoRA based on new sdxl turbo, you can use the TURBO with any stable diffusion xl checkpoint, few seconds = 1 image(4 seconds with a nvidia rtx 3060 with 1024x768 resolution) Tested on webui 1111 v1. 0. Powered by sd-turbo and the excellent model compiler named I'm using AUTOMATIC1111. Can start w SDXL 1. 5 refiner. 0, designed for real-time image generation. 5 with only a 0. Animation - Video. 5 - 2. However, it comes with a trade-off of a slower speed due to its requirement of a 4-step sampling process. The third step will be linked to the union of speed and quality and I believe that this will happen in the short termThe race to see who is fastest will turn into a race to see who is the fastest at 60fps at 1024x1024. Install ArtSpew and then follow the README-maxperf. Stable Diffusion 3 will take another month or so (optimistically) to publishing weights, we will see there. Tutorial - Guide. Astounded. I personally prefer sdxl, it seems better straight up. ComfyUI wasn't able to load the controlnet model for some reason, even after putting it in models/controlnet. Windows Task Manager. It might also be interesting to use, CLIP, or YOLO, to add tokens to the prompt on a frame by frame bases. /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. commonly broken faces/fingers/hands unless that's the whole focus of the image). 0_fp16 on a whim, and I'm generating 9 images in 7 seconds. If budget is a concern a new i3 is also acceptable. This ability emerged during the training phase of the AI, and was not programmed by people. They are all more than 1 pass. 0. Vote. I remember using Midjourney few versions back and it was definitely better, as in for majority of short natural language prompts MJ outputted "correct" looking images while SD3 on SA was much closer to what I would expect from a Stable Diffusion model (e. Refiner has not been implemented yet in Automatic1111. What is the yellow oval can I just gen a whole image. It's like 10 minutes max. Wanted to share this playground for image to image live drawing on SDXL-Turbo https://fal. In the video I single step a few times before clicking "Go". I set it to render 20fps at a resolution of 1280x768. SDXL-Turbo. To be honest SDXL-Turbo is a distilled version of SDXL 1. Install the TensorRT plugin TensorRT for A1111. SDXL-Turbo is a distilled version of SDXL 1. See which sampler gives the best quality with the amount of steps that you consider is fast enough, or slow enough if you don't mind waiting more for the extra quality you might squeeze out of it. LJRE_auteur. 25MP image (ex: 512x512). We would like to show you a description here but the site won’t allow us. 5 upvotes · comments Didn’t dos lot of testing though. Decided to create all 151. Most samplers cap on quality at around 40-50 steps anyway. There is actually a SDXL Turbo Filter on Civitai. A large (2TB+) SSD and a even larger (4TB+) to store all your goodies. 5 CFG, which is 3. You will want a decent CPU, an 13th gen i5 would be a good choice, and more RAM (32GB+). CFG Scale: from 1 to 2. Try something in the range of 1. 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. ai launched the SDXL turbo, enabling small-step image generation with high quality, reducing the required step count from 50 to just 4 or 1. Sure, some of them don’t look so great or not at all like their original design. It gets pretty cursed after 4 or 5. 5 models at 10 steps at a resolution of 640x384 would only take about 20 minutes. It might be another way to handle details like eyes open, vs closed. 1, and the speed in this turbo model is unbelievable. 3X for Stable Diffusion v1. How is this even possible? I'm so used to waiting 60+ seconds per image on my outdated 1080ti, and then I try sd_xl_turbo_1. Someone else on here was able to upscale from 512 to 2048 in under a second It's faster for sure but I personally was more interested in quality than speed. Just for sharing. It looks promising from early teaser. 1X for LDM-4-G with a slight decrease of 0. I have 3050RTX on my laptop so the process was a little bit time consuming! We would like to show you a description here but the site won’t allow us. 5 + sdxl turbo. News. Dreamshaper SDXL Turbo is a variant of SDXL Turbo that offers enhanced charting capabilities. 5 LCM models, but haven't tested it yet. The images are good but the atanomy is often wrong and the prompt is I used the 'Touch Designer' tool to create videos in near-real time by translating user movements into img2img translation! It only takes about 0. 5 vs Midjourney vs Dalle 3 vs Adobe Firefly . Grab a ComfyUI zip, extract it somewhere, add the SDXL-Turbo model into the checkpoints folder, run ComfyUI, drag the example workflow (it's the image itself, download it or just drag) over the UI, hit "queue prompt" in the right toolbar and check resource usage in eg. Nice. 2 to 0. Elated. sd1. If I understood correctly, turbo is just SDXL base model but got bitten by a radioactive spider 😂. This innovative strategy, in turn, enables a speedup factor of 2. Add a Comment. I'm on the dev branch, and I'm not sure the SGM setting has much to do with the specific Turbo samplers. Nvidia EVGA 1080 Ti FTW3 (11gb) SDXL Turbo. 05 decline in CLIP Score, and 4. SDXL takes around 30 seconds on my machine and Turbo takes around 7. 0, trained for real-time synthesis. To be honest Here is the workflow link. I like v2. Maybe I'm just too much of an old-timer but I find that live real-time generation to be more of a distraction than a boost in productivity. 04 Stable Diffusion 3 Turbo My Opinion: Stable Diffusion XL: Best price-performance ratio (probably also the least amount of computing power needed) and the only one with published source code. Can you show the rest of the flow, something seems off in the settings, its overcooked/noisy. For this video I used 4 steps, CFG set to 2. ai/turbo. Mouth open, vs mouth closed, extra. combine this with the upcoming sparse control and make a sparse depth map of the racoon and you can have a video generation. 5 in comfyui) I'm pretty novice here but for your own workflow: If you change the sdxl turbo workflow to use a sd 1. If you want it to stick fairly close to the original I recommend upscaling in stages. Or wait for the pull request that puts the scheduler on the main UI to be merged. Adjust how many total_frames you want it to loop back with. In this experiment i compared two fast models, sd-Turbo & SDXL-Turbo. I was using the Euler A sampler. SDXL-Turbo is a simplified and faster version of SDXL 1. Running sdturbo on M1 Pro MacBook, live webcam input, then pasting a new prompt partway through recording the video gives a morphing effect. Tested on ComfyUI: workflow. For 832x1216 the cost is 3. Sampling steps: 4. 9 to 1. ds tg rd up sz ni hn ld la gn