Comment by vblanco
8 hours ago
Im running this on my 4070ti super (16 gb vram), and it takes 10 minutes for a 10-seconds 480p video. but the results are spectacular.
8 hours ago
Im running this on my 4070ti super (16 gb vram), and it takes 10 minutes for a 10-seconds 480p video. but the results are spectacular.
FWIW on a 5080 16GB it takes 3 minutes for 10 seconds 480p video (the mouse video workflow with length changed from 5 seconds to 10 seconds)
FWIW on a 6000 Pro it takes 68 seconds for 10 seconds 480p video, (cold) same demo workflow as you used. Set "megapixels" to 2.0 (1920x1088) and same video seems to take 5+ minutes, not sure if everything is right/correct at the moment.
As far as I can tell, the current ComfyUI nodes don't even do compilation, and I haven't looked into what attention mechanism they're using, but I'm sure with time these durations will come down even more.
People on reddit have definitely pointed out that sageattention will speed up the renders.
And it's literally the first day. Someone will make a distilled 4-8 step LoRA and we're off to the races.
Edit: did a couple of 10 second long 864/480 i2v videos on my RTX Pro 6000: sageattention bumps them up 33%, that is to say, 140.89 seconds without sageattention becomes 105.69 with sageattention on (if using the KJ Sageattention node, "allow_compile" doesn't seem to affect it, just "sage_attention" set to "auto" works fine).
EasyCache also appears to work, but does affect quality, at least with the default threshold or even down to 0.10. Still, at 0.10 threshold the same render above, with sageattention, is down to 71.33 seconds, so depending on your use case the quality hit might be worth it. Also it seems that with EasyCache the video still matches the un-EasyCached video (with the same seed), so you could use it to do seed hunting.
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What’s the vram usage? I’ve got a 5090 so as long as I can fit it in memory the gen times should be roughly equivalent ~10%
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Waiting for the “FWIW on a B200” reply
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I must be doing something incredibly wrong.
I'm on an RTX 5090. I told it to make a 5 second 864x480 video, it's been running for over 30 minutes and is only 35% done in the SamplerCustomAdvanced step.
EDIT: Oh, I'm an idiot. Forgot I had a llama.cpp webserver running with a model loaded. Killed it and it finished very fast.
I am particularly curious how multimodal models will work with types of knowledge that are inherently non-text. For example, SOTA LLMs really suck at electronics, especially analog electronics.
Is MiniMax H3 capable of logical / technical reasoning, or is it purely art oriented?
Suck at what aspect of (analog) electronics specifically? Not contradicting the claim, just want to understand it.
I have not tested yet, but I suspect that LLMs with a harness that can execute code can do SPICE simulations rather ok these days? I have seen MCPs for measurement equipment also, maybe they can even close the physical loop?
spice is a very bad simulation. it's not like a unit test or a VM. it works very differently to the real thing, only approximating it in some highly controlled situations.
> work with types of knowledge that are inherently non-text
What are those things exactly? AFAIK, everything we can "know" can be written down, one way or another, even analog circuits.
Also, what SOTA LLMs are you referring to? GPTs been handling analog circuits fine for quite some time, I want to say for at least one year? I've been "pair programming" a bunch of working circuits with GPT models since probably GPT 5 or so.
> AFAIK, everything we can "know" can be written down, one way or another, even analog circuits.
writing down circuit diagrams is like cooking about music.
> what SOTA LLMs are you referring to?
I have done a survey among analog electronics designers just a couple weeks ago and they all said that their forays into LLMs were great for digital electronics, code, and firmware, but for analog they were pretty terrible, with a variety of LLMs, according to everyone.
> everything we can "know" can be written down
Do you know how to ride a bike?
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I've had great results on electronics with Claude and Gemini.
what sorts of things have you designed with it?
They can be used to create synthetic training data for robotics. It's not the best approach, though.
i bet they're good for it. however robotics aren't electronics. that's a completely different space.
If you wouldn't mind sharing, what's your Comfy workflow for this? I have the same video card setup and would like to give it a shot.
just the default one in the link for image-to-video
1 minute for a second of footage, that is awesome! Thanks for sharing.
Huh, interesting. I tried to generate a 10 second 1080p clip on a bigger machine and the results were quite poor. Unusable for anything, in fact.
How much RAM does your machine have?