Comment by embedding-shape

8 hours ago

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.

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embedding-shape

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pkroll  7 hours ago

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.

  • loldog  2 hours ago

    Knowing r/StableDiffusion this will run on a Raspberry Pico's PIO core in real-time by end of this week.

wincy  3 hours ago

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%

  • embedding-shape  2 hours ago

    Depends on what weights, I landed on:

        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

    Ends up at ~83GB, but they also shipped bunch of pruned + quantized versions of the diffusion model, might fit with a 5090: https://huggingface.co/Comfy-Org/MiniMax-H3