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.
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.
diffusion model: minimax_h3_fl2va_bf16.safetensors
text encoder: qwen3vl_32b_minimax_h3_nvfp4_awq.safetensors
video VAE: minimax_h3_video_vae_fp16.safetensors
audio VAE: minimax_h3_audio_vae_fp32.safetensors
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.
Is MiniMax H3 capable of logical / technical reasoning, or is it purely art oriented?
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?
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.
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.
Do you know how to ride a bike?