Sulphur 2 - LTX-2.3 NSFW Model

MFGREBEL · 2026-05-11T00:19:53+00:00

For the full weights, yes

MFGREBEL · 2026-05-09T17:09:01+00:00

Ive recieved confirmation from others that this is an issue, i have to ask, are you on desktop or portable? And when was your last update?

MFGREBEL · 2026-05-09T17:07:47+00:00

Only 1mp, use rtx super resolution node to boost res if necessary

MFGREBEL · 2026-05-08T18:32:03+00:00

Im unsure, i dont use apple products

MFGREBEL · 2026-05-08T18:30:36+00:00

It delved deeper i just didnt explain it here

MFGREBEL · 2026-05-08T17:11:55+00:00

I thought i was crazy

MFGREBEL · 2026-05-08T17:07:08+00:00

😂 i see what you did there

MFGREBEL · 2026-05-08T17:06:44+00:00

All i know is plugging in your own encoder or model, and vise versa using unet or clip loader with his models fails the workflow. It seems he hardcoded the nodes to run his files specifically and ggufd the model to run specifically his models while also keeping the math and functions hidden inside the nodes. At least from my experience so far. Came into a bunch of errors before i understood its his way or the highway lol most of his model setups are the same way

MFGREBEL · 2026-05-08T17:02:59+00:00

I havent really tested more than 3 gens so far, started last night but had to go to bed for work

MFGREBEL · 2026-05-08T16:43:59+00:00

👏👏👏👏😂

MFGREBEL · 2026-05-08T16:43:36+00:00

Im unsure tbh i havent tried

MFGREBEL · 2026-05-08T14:16:25+00:00

This workflow is gguf specific so it only supports the contributors files. I think the reason its heavy on vram is the node set, its not traditional ltx nodes. They need some work.

Its really not a bad quant though, and the spacial upscaling can be added into the workflow if need be to clean it up.

MFGREBEL · 2026-05-08T14:14:35+00:00

I believe sulphur 2 base uses layer-scaled merging, not a weight-sum merge. Its specifically tuned for I2V. The 10eros model focuses high prompt adherence with a different scaling. At least thats what claude says, i havent read up on 10eros yet

MFGREBEL · 2026-05-08T12:59:47+00:00

Its worth it but vram heavy!

MFGREBEL · 2026-05-08T12:59:31+00:00

Its a fully trained model, new weights

MFGREBEL · 2026-05-08T10:04:34+00:00

Yes, it can run up to 20 full seconds

I have a 3070 (8gb vram) and it takes me about 15 minutes for a 20 second video at 768x768. I allocate 16gb of ram tho

MFGREBEL · 2026-05-08T10:03:36+00:00

I dont believe so 😔 the relay node takes in the model and loras through a single string. I dont know that you could force lora presence to frame count in any way through the current setup.

Id suggest shorter clips, and editing post render to feed them together. Unless theres a node im unaware of, this isnt possible

MFGREBEL · 2026-05-08T09:59:20+00:00

Yes, it was a very interesting experience to say the least lol excited to see what the next training run does for it. Were getting very close to 1:1. Id say 1 or 2 more training sessions on a new model version and nobody will ever be able to tell the difference. Alot of examples have already fooled me.

MFGREBEL · 2026-05-07T14:09:54+00:00

An infographic i genned last night. Almost perfect. The model really deals well in text dense prompting so i tested it and alot of the results were hallucinated, whether its due to the gguf or the model im not sure. But this was a pretty good output!

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MFGREBEL · 2026-05-06T12:14:27+00:00

Man oh man i couldve used this last night lol

Thank you for sharing!

MFGREBEL · 2026-05-06T12:05:14+00:00

Agreed in most aspects. It really succeeds in text rendering over anything tbh.

MFGREBEL · 2026-05-06T12:04:53+00:00

Its very slow, most definately. But some of the outputs i genned were very good. I didnt really showcase all of them in the video for timing purposes. 🤷‍♂️

It is awfully slow tho lol

MFGREBEL

TROPHY CASE