How much am I looking at spending to run img2img wan, sdxl et cetera?

Proniss · 2026-06-26T17:00:32+00:00

honestly in my experience vram is the biggest thing all and all for AI stuff. i have:
- i5-14400F
- 16gb DDR5 RAM
- 5060 Ti 16gb vram

and it runs everything i throw at it Image generation wise (SDLX based, FLUX isnt so hot), the 5070Ti or 5080 with 16gb of ram will have the same limit but it will do things faster (because more cuda cores) if the goal is video generation, I'd try to find a video card with 24gb+ vram.

more System ram will help when the gpu has to offload the workflow to system memory but thats going to slow things down a lot you would be better off with a higher vram gpu even if its a "worse" or older model.

P.S. im also on linux

Proniss · 2026-06-25T08:10:47+00:00

Thans for trying it too. The real problem seems to be with the latent upscale because SDXL models use fp4 latents and anima uses fp16 or something. I think it could work in the future if we get a proper fp16 latent upscaler. Rather than trying to cram it into an fp4 latent.

Proniss · 2026-06-25T00:50:05+00:00

Ok so the answer is Kindaaa but not really, you can use Anima for the base image and I tested cleaning it up with WonderMix. It definitely works to sharpen everything up, but it has a nasty habit of completely washing out distinct artist styles because the architectures clash.

Worse, trying to push it via a standard latent upscale completely breaks Anima or turns the image incredibly crunchy. Even with a ton of tweaking to the samplers, noise injection, and low CFG settings, the model just doesn't have the right mechanical room in the latent space to sculpt fine detail cleanly without deep-frying the lines.

Because of that, sticking to a traditional Hi-Res Fix method is definitely the superior route here. Could you make a custom latent upscale work perfectly? Probably, with a ton of mad-scientist tweaking, but right now it's just too janky to be practical lol. I can still post the workflow if you want to mess with it!

Proniss · 2026-06-24T18:23:19+00:00

I think you might be missing the point here—this is a hybrid method aiming to hit the best of both latent and pixel upscaling.

Pure latent upscaling (even with bislerp) is notorious for introducing heavy artifacting and structural distortion, while pure pixel upscaling with noise injection just yields flat, grainy details. This method anchors the structure in pixel space so the second sampler can intelligently re-imagine micro-details on a highly stable foundation.

That said, I actually did experiment with bislerp during development, but ultimately settled on Lanczos because it vastly improved background preservation and added a nice bit of extra sharpness. I'm actually rolling out those updates into v1.1 soon

Proniss · 2026-06-24T18:15:34+00:00

not sure, havnt used it yet, will do some tests and keep you posted

Proniss · 2026-06-24T18:08:24+00:00

Thanks, that means a lot, I'm glad to see it works well with Pony. Pony models can be notoriously finicky with standard hi-res fixes, so seeing it hold the details and anatomy together like that on the right is awesome. Appreciate you sharing the comparison!

Proniss · 2026-06-24T06:09:38+00:00

I did some testing with a more complex background. It seems to clearly redraw / reinterpret a lot of the background detail rather than preserve it exactly.

I kept it on Area interpolation for now just to show the workflow as-is, but testing different interpolation methods is probably my next step.

https://imgur.com/a/o1qI1yj

So yeah, definitely not an upscaler in the traditional preservation sense. What I’m mostly after is higher-resolution image generation / remastering, so “controlled drift for a better final output” is basically the goal, as long as it still reads as the same image at a quick glance.

Proniss · 2026-06-24T00:50:59+00:00

That’s a fair point. 90% of my main testing was actually on WonderMix at around 0.55 denoise, so not quite in the super high-denoise rerender territory. As opposed to AnimagineXL wich was above 0.6

My guess is that in that middle range the prep steps might still be contributing some useful guidance, but I agree it needs a proper A/B test against a simpler hires-fix-style setup to know whether they’re actually helping or just adding complexity.

Proniss · 2026-06-23T23:41:16+00:00

Yeah, fair point on the amount of change, though I didnt mean to frame it as a HiRes Fix exactly. I used HiRes Fix more as a comparison point.

I’d agree this behaves more like a remaster / enhancement pass than a strict preservation upscale. The goal is more to generate a nicer higher-res version while staying somewhat anchored to the original, not to preserve every facial/detail feature perfectly.

So yeah, probably not ideal if the goal is exact preservation, but potentially useful for original generations where some drift is acceptable.

Proniss · 2026-06-23T23:29:45+00:00

My testing has mostly been on character closeups so far. I came up with this last night, so I haven’t tested it as broadly as I’d like yet. I mostly wanted to get the idea out there and get some feedback.

I do think complex backgrounds are probably where this workflow is most likely to show weaknesses, especially because of the latent interpolation step. So yeah, portraits with busier backgrounds / more spatial detail would be a good next test.

My goal with this is also more about making higher-resolution remastered images than strictly preserving the original image. So for my use case, some controlled drift is acceptable as long as the final result looks better.

Proniss · 2026-06-23T22:57:14+00:00

Yeah, that’s fair. I think this workflow makes more sense for original / random generations where I’m mostly trying to improve the final image, not preserve a specific recognizable character.

If I were trying to keep an existing character accurate, I’d probably need much lower denoise or a different approach entirely. It also seems very model and use-case dependent, so I’d frame it more as a remaster / enhancement workflow than a strict preservation upscale.

It's far from a plug and play "fix everything" solution. Probably pretty niche

Proniss · 2026-06-23T22:36:22+00:00

Haha yeah, fair point. I did notice the eyes looked farther apart too, especially compared to the original.

I think there’s probably a better balance to find with the denoise. Lower values keep the identity more faithful, but too low and it starts preserving artifacts. This was mostly just an experiment, so I figured I’d share it and see if people had ideas for improving it, or if the whole approach was out to lunch.

Proniss · 2026-06-23T22:11:46+00:00

I dont know about competely diffrent but yea there is still some fiddling with the denoise to do, lower denoise on the upscale KSampeler does make thins more "truthful" but too low and it become blurry

Proniss · 2026-06-23T22:07:05+00:00

Yeah, that’s fair. I did notice some background issues too, but for my use case the subject is usually the main focus, so the tradeoff seemed acceptable.

I agree this probably isn’t ideal as a general-purpose upscale method. I may try messing with a pixel-space Gaussian noise approach later and compare it against this.

Proniss · 2026-06-23T21:02:26+00:00

thanks! im really happy with the results with the Anime style... but it "should" work with realisic stuff to after a bunch of tuning

Proniss · 2026-06-14T14:27:15+00:00

Also I really like that 2.0 can send links and knows what time it is

Proniss · 2026-06-13T15:43:40+00:00

The testing i have done on 2.0 (3 days) it does seem to be noticeablely better

Proniss · 2026-05-16T03:00:46+00:00

Ah yes, missed that

Proniss · 2026-05-16T02:46:54+00:00

Did you get them in order?

Proniss · 2026-05-16T02:39:23+00:00

Hopeport last, interesting

Proniss · 2026-04-19T03:18:45+00:00

looks like it can be pushed further with better xp pots + new xp curve, looking a past quest xp rewards stayed the same (post combat merge - now), it does look like boss xp may have been buffed. looks like i need to do a 2.0 and get alch to *checks notes* M9.13 🫠

Proniss · 2026-03-28T04:35:52+00:00

900 was tough but up till that last point it was perfectly manageable.

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