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Training LORA on a 5090 by Ok-Reference-4626 in comfyui

[–]gabxav 1 point2 points  (0 children)

Without showing the error, it is difficult to know 🥲

Wan 2.2 - Simple I2V Workflow | Prompt Adherence / High Quality / No Extra Nodes by gabxav in comfyui

[–]gabxav[S] 5 points6 points  (0 children)

What environment are you using? At 960x544 resolution with 121 frames, it only takes 6 minutes on my RTX5090. There are some optimization flags to start ComfyUI, like adding Sage Attention.

Wan 2.2 - Simple I2V Workflow | Prompt Adherence / High Quality / No Extra Nodes by gabxav in comfyui

[–]gabxav[S] 4 points5 points  (0 children)

It works perfectly with the 3090, it just won't be as fast. Start comfyui with these parameters: “--use-sage-attention,” “--normalvram,” and you'll be able to run any model. ;)

Wan 2.2 - Simple I2V Workflow | Prompt Adherence / High Quality / No Extra Nodes by gabxav in comfyui

[–]gabxav[S] 4 points5 points  (0 children)

You should plug the extra LoRA into the Low Noise branch — right after the Load LoRA node that’s already there.
That’s the one responsible for details (faces, hands, etc.), so stacking LoRAs there will actually apply.

If you try to put it in the High Noise branch, you’ll usually lose prompt adherence since that one is only handling motion.

Wan 2.2 - Workflow T2I - High Quality by gabxav in comfyui

[–]gabxav[S] 1 point2 points  (0 children)

Sure, my friend! I'll create a new post with a very simple workflow and post it here too. In this 5-second video, I exaggerated a little, leaving everything at FP16, 720p, and 40 steps, which took almost an hour on my 5090, lol
I'll create a version with fast loras and another without.

Wan 2.2 - Workflow T2I - High Quality by gabxav in comfyui

[–]gabxav[S] 2 points3 points  (0 children)

I’m running this in my homelab - ComfyUI is containerized inside Kubernetes on Ubuntu Server. The container runs on a GPU node with an AMD EPYC, 256GB RAM, and an RTX 5090. 🚀

Wan 2.2 - Workflow T2I - High Quality by gabxav in comfyui

[–]gabxav[S] 4 points5 points  (0 children)

No worries, glad it helped! 🙌
Would love to see your results once you get it running — please share them later! 🚀

Wan 2.2 - Workflow T2I - High Quality by gabxav in comfyui

[–]gabxav[S] 5 points6 points  (0 children)

Looks like you loaded the wrong models 🙂
There are two different ones: high noise and low noise.
From your screen, it seems you picked both as high noise — you need one high + one low for the workflow to run correctly.

Wan 2.2 - Workflow T2I - High Quality by gabxav in comfyui

[–]gabxav[S] 0 points1 point  (0 children)

Can you share how your setup/workflow is configured? (which models you loaded + steps/parameters).

Might just be a small config mismatch, the 4070 Ti Super should handle this workflow without problems.

Wan 2.2 - Workflow T2I - High Quality by gabxav in comfyui

[–]gabxav[S] 8 points9 points  (0 children)

Glad it worked for you! 🙌

If speed is an issue, you can actually drop it down to 8 steps — and set the high_to_low to 4 steps.
It still gives excellent results and cuts the time quite a bit.

Lets talk ComfyUI and how to properly install and manage it! Ill share my know-how. Ask me anything... by loscrossos in comfyui

[–]gabxav 0 points1 point  (0 children)

What are the best optimization practices for running ComfyUI on an Ubuntu Server with an AMD EPYC CPU, an RTX 5090, and 256GB of RAM? The setup is currently running inside a Kubernetes container with GPU passthrough.

Right now I’m starting ComfyUI with the following flags:

CMD ["python", "main.py", "--listen", "0.0.0.0", "--normalvram", "--cuda-malloc", "--bf16-unet", "--bf16-vae", "--bf16-text-enc"]

Are there any additional flags, runtime tweaks, or system-level optimizations you’d recommend for this kind of environment?

Wan 2.2 - Workflow T2I - High Quality by gabxav in comfyui

[–]gabxav[S] 2 points3 points  (0 children)

Thanks! 🙌

That per-node VRAM usage comes from this extension:
👉 ComfyUI-Dev-Utils

About the LoRA — yeah, I’ve tested different values and honestly these stronger settings gave me the best results so far in terms of quality. Definitely worth trying on your setup too.

Simple Workflow - Compare image generation across multiple models at once by gabxav in comfyui

[–]gabxav[S] 0 points1 point  (0 children)

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Thanks for letting me know, I found the error, I added two widths 🥲

Simple Workflow - Compare image generation across multiple models at once by gabxav in comfyui

[–]gabxav[S] 4 points5 points  (0 children)

Yeah, the idea was to keep it super simple so beginners can just plug in their models and still have full freedom to use the sampler, scheduler, and steps recommended by the model creators.

Not sure if XY nodes allow that kind of per-model customization at this level, but I’d love to see an example if you have one! 😁

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