Seems like a bit of a stretch to call 4 seconds per frame, on a 3060, “realtime” / “as fast as you can type”.
The author can’t type very quickly
A rapid dark-tan mammalian with a bushy tail, propels itself upward off the ground, to an elevation above (or greater) than that of the canine resting below, whom has a disposition contrary to productivity.
I’d guess that the ‘realtime’ is a quote from StabilityAI and of course they’re running that stuff on an A100. A couple of seconds is still interactive rate as generally speaking you want to think about the changes you’re making to your conditioning.
Haven’t tried yet but if individual steps of XL Turbo take ballpark as much time as LCM steps then… well, it’s four to eight times faster. As quality generally isn’t production-ready we’re generally speaking about rough prompt prototyping, testing out an animation pipeline, such stuff, but that has the caveat that increasing step size often leads to markedly different results (complete change of composition, not just details) so the information you gain from those preview-quality images is limited.
Oh, “production ready quality”: image quality being roughly en par with 4-step LCM means that it’s nowhere near production grade. For the final render you still want to give the model more steps. OTOH I’ve found that some LCM-based merges do in 30 steps what other models need 80 steps for so improvements are always welcome. But I’m also worried about these distilled models being less flexible, pruning only slightly trodden paths that you actually might want the model to take.
EDIT: Addendum: I’m not seeing anything about using this stuff as a Lora. The nice thing about LCM is that you can take any model you have on your disk and turn it pretty much instantly into a model that can generate fast previews. Also, VAE decoding already can be slower than generation with LCM, so, yeah. I guess having something in between the full VAE and TAESD would be nice, TAESD is fast but is quite limited both when it comes to details, so much that you might not even be able to see what kind of texture SD generated. Oh and it also tends to get colours wrong, at least in my experience it tends to be oversaturated.
Well, it is technically as fast as you can type if you’re running a better GPU. The 3060 is pretty mid-tier at this point.
Low end card.
I’ll get crucified for saying that because people will interpret that as an attack on their PC or something daft like that. It’s not.
It’s Ampere, a GPU architecture from 3.5 years ago. And even then, here’s what the desktop stack was like:
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3090 Ti (GA102)
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3090 (GA102)
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3080 Ti (GA102)
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3080 12GB (GA102)
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3080 (GA102)
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3070 Ti (GA102/GA104)
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3070 (GA104)
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3060 Ti (GA104/GA103)
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3060 (GA106/GA104)
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3050 (GA106/GA107)
It was almost at the bottom of Nvidia’s stack 3 years ago. It was a low end card then (because, you know, it was at the bottom end of what they were offering). It’s an even more low end card now.
People are always fooled by Nvidia’s marketing and thinking they’re getting a mid range card when in reality Nvidia’s giving people the scraps and pretending they’re giving you a great deal. People need to demand more from these companies.
Nvidia takes a low end card, slaps a $400 price tag on it, calls it mid range, and people lap it up every time.
I know it’s low-end when compared to the newer generations but if we call a 3060 low-end then what do we call people with older GPUs like a 1070?
Should we not compare the 3060 against its own generation/the current one? To me that makes more sense than including the 1000 series or 900 series or something. How far would we go back? Are all cards sold now high end because they’re faster than a GTX 960? Earlier?
Personally my cut off was cards still on sale either right now or very recently, say within the past year.
The pricing makes it a mid range card, because the budget end is just gone these days.
Nvidia conning people into paying what used to be mid range/high end pricing for a low end card does not make it a low end card.
The 3060 was always a low end card. Because it was on the low end of the product stack, both for Nvidia and against AMD.
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I’m on a 3060 and with 4x upscaling it takes about a second and a half.
This isn’t free BTW folks
I haven’t messed with any AI imaging stuff yet. And free recommendations to just have some fun?
Bing and Open AI still and free stuff. Bing’s is actually really good.
Great, even more online noise that I can look forward to.
That’s impressive
And the resulting faces still all have lazy eyes, asymmetric features, and significantly uncanny issues.
Humans have asymmetric features. No one is symmetrical
These features are abnormally asymmetric to the point of being off-putting. General symmetry of features is a significant part of what attracts people one to another, and why facial droops from things like Bells Palsy or strokes can often be psychologically difficult for the patient who experiences them.
General symmetry, not exact symmetry.
Anecdote: I think Denzel Washington is supposed to have one of the most symmetrical faces.
You can easily get incredibly canny stuff.
This is great news for people who make animations with deforum as the speed increase should make Rakile’s deforumation GUI much more usable for live composition and framing.
I’ve tried to install this multiple times but always manage to fuck it up somehow. I think the guides I’m following are outdated or pointing me to one or more incompatible files.
Tough luck running any code published by people who put out models, it’s research-grade software in every sense of the word. “Works on my machine” and “the source is the configuration file” kind of thing.
Get yourself comfyui, they’re always very fast when it comes to supporting new stuff and the thing is generally faster and easier on VRAM than A1111. Prerequisite is a torch (the python package) enabled with CUDA (nvidia) or rocm (AMD) or whatever Intel uses. Fair warning: Getting rocm to run on not officially supported cards is an adventure in itself, I’m still on torch-1.13.1+rocm5.2 newer builds just won’t work as the GPU I’m telling rocm I have so that it runs in the first place supports instructions that my actual GPU doesn’t, and they started using them.
Do you use comfyui ?
This is the best summary I could come up with:
Stability detailed the model’s inner workings in a research paper released Tuesday that focuses on the ADD technique.
One of the claimed advantages of SDXL Turbo is its similarity to Generative Adversarial Networks (GANs), especially in producing single-step image outputs.
Stability AI says that on an Nvidia A100 (a powerful AI-tuned GPU), the model can generate a 512×512 image in 207 ms, including encoding, a single de-noising step, and decoding.
This move has already been met with some criticism in the Stable Diffusion community, but Stability AI has expressed openness to commercial applications and invites interested parties to get in touch for more information.
Meanwhile, Stability AI itself has faced internal management issues, with an investor recently urging CEO Emad Mostaque to resign.
Stability AI offers a beta demonstration of SDXL Turbo’s capabilities on its image-editing platform, Clipdrop.
The original article contains 553 words, the summary contains 138 words. Saved 75%. I’m a bot and I’m open source!
Does it actually run any faster though? For instance, if I manually spun a model with the diffusers library and ran it locally on dml, would there be any difference?
Edit: Assuming we’re normalizing the output to something reasonable, e.g. a recognizable picture of a dog.
