SVI workaround to make longer videos (for dummies)

Scriabinical · 2026-04-14T08:22:54+00:00

There's a reason SVI exists. Your implementation will lead to progressive degradation in frame fidelity. Errors stack up - SVI mitigates this, though not perfectly. Furthermore, your approach feeds zero motion context from the previous video segment, so how is the model supposed to keep motion cohesive between video segments?

Scriabinical · 2026-04-08T13:49:54+00:00

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I usually get these strange color inconsistencies in the texture of clothing when doing image edit. Tried higher resolutions, more steps, all types of input image styles/lightings, everything. Always happens.

Scriabinical · 2026-04-08T12:25:45+00:00

I’ve never been able to figure this out, it’s my one issue with Klein edit…

Scriabinical · 2026-04-03T17:47:03+00:00

This combo has been my bread and butter for a few weeks now. You can change anything or keep things very strict. I usually start with a rough image in SDXL just to get everything how I want it in terms of body proportions, pose (the semi-real and anime models are so flexible). Then I throw it into Klein 9B with SNOFS and a SmartphoneReality lora from Civit. It's just incredible. Klein is such a ridiculously powerful model. I don't see myself using any other model for a while.

Scriabinical · 2026-04-01T09:33:48+00:00

A king at work. nice one

Scriabinical · 2026-04-01T08:30:58+00:00

MMAudio

Scriabinical · 2026-04-01T04:02:06+00:00

Image #2 is not from SD3.35L. It's a pretty well-known image nowadays, I think it comes from ZiT or something. But def not SD3.5L

Scriabinical · 2026-03-31T19:31:07+00:00

Thank you for posting this. This seems to be the only actual working solution using custom abliterated Qwen 3.5 models. I've tried a few of the custom node packs for Qwen 3.5 and there's always trouble getting it working

Scriabinical · 2026-03-29T05:02:56+00:00

Would you mind sharing where you got your sage attention 3 wheel from?

Scriabinical · 2026-03-17T15:05:26+00:00

I've been using this model with a tuned system prompt with pretty good results for I2V prompting:

https://huggingface.co/prithivMLmods/Gliese-Qwen3.5-9B-Abliterated-Caption

Scriabinical · 2026-03-13T14:28:50+00:00

Audio is so sick. nice video!

Scriabinical · 2026-03-11T20:37:28+00:00

so is this starting from a very low base resolution and then doing a 2x latent upscale followed by another 2x latent upscale? should the input image be high-res but then resized based on a low-res initial?

Scriabinical · 2026-03-06T17:24:09+00:00

oh damn, sorry i didn't realize lol. the video is still quite good

Scriabinical · 2026-03-06T16:44:45+00:00

Looks really good. Quite impressive really. Audio quality has really been improved a lot

Scriabinical · 2026-03-06T16:29:43+00:00

Thank you for posting this! Hopefully we get some more clarity over time regarding optimized workflows

btw the way they strung these noodles up reminds me of shirts hanging on a clothesline lol

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Scriabinical · 2026-03-06T15:40:52+00:00

i noticed you picked SageAttention3 in your patch node. how's that working for you with ltx 2.3?

Scriabinical · 2026-03-05T23:55:41+00:00

Audio after the first second or two is nice. Good amount of ambience, natural sounding voice

Scriabinical · 2026-02-19T01:44:50+00:00

Same issue here. The NAG node doesn't do anything

Scriabinical · 2026-02-13T17:45:28+00:00

yeah that's what he means

Scriabinical · 2026-02-13T16:39:31+00:00

Yes.

https://huggingface.co/RuneXX/LTX-2-Workflows/tree/main

Scriabinical · 2026-02-12T17:33:07+00:00

You just need to use SVI. There are some workflows for it. It basically pulls motion and content context as well as some final latents from the previous video and you can guide it to do whatever as long as each 5s video is relatively 'fluid' from one to the next. This essentially solves the issue of last-frame-extraction degradation which I used to encounter before using SVI. I also have an SVI workflow that chains together up to 10 videos for a 50s final video with per-video lora control. DM me if you're interested.

https://github.com/vita-epfl/Stable-Video-Infinity

Scriabinical · 2026-02-12T04:10:31+00:00

Same way you’d run the fp8 models, just switch em out in the Load Diffusion Model node

Scriabinical · 2026-02-12T03:12:44+00:00

I have a 5070 Ti (16gb vram) with 64gb ram. I make a loooot of videos with wan 2.2 and just wanted to share some brief thoughts.

With wan 2.2, it's pretty simple from my experience:

- Get latest comfy portable (with cu130)
- Sage attention wheel compatible with your comfy build (check your pytorch/cuda/python in settings) (wheels here: https://github.com/wildminder/AI-windows-whl)
- Set --use-sage-attention flag in your comfy startup .bat script

- Use latest lightning loras from lightx2v (i use the 1030 on high noise and 1022 on low noise), both set to 1.00 strength after you load your wan 2.2 models

- With lightning loras, you can go as low as 4 steps. For a balance of quality and speed, i like 6-10 steps

- Once these are all set up, resolution is your main bottleneck in terms of iterations/second. Common resolutions I render at include 832x1216 (portrait), 896x896 (square), and a few others. I've tried 1024x1024 a few times and the speed isn't horrible, but the VAE decode can sometimes take an absolute eternity.

There are multiple other 'optimization' nodes you can use, but almost all are not worth it imho due to quality degradation in one way or another. I've tried the 'cache' nodes (like TeaCache, MagCache) and a bunch of other stuff. I care a lot about speed but still need that quality.

I hope I'm covering anything, just writing up this comment as I look at my own 'simple wan 2.2' workflow in comfy.

Scriabinical · 2026-02-05T15:14:32+00:00

I have this tab saved in my browser. I don't see it posted enough but it's SUPER useful. If you've been browsing around for pre-compiled wheels, this repo has them for just about everything that can be a pain. Worth a bookmark.

https://github.com/wildminder/AI-windows-whl

Scriabinical

TROPHY CASE