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.
Since no one else posted it... I have open-webui pointed at a linux box with 128 gig of ram and an RTX Pro 6000, and after a couple of runs on trivia, had it do one of Open WebUI's conversation starters: "Show me a code snippet of a website's sticky header in CSS and JavaScript."
72.06 t/s. That's the full Qwen 3.6 27B model BF16, using MTP, running on Ollama. Yes I know I should bite the bullet and get vllm running on that box.
That was, also, at a 570 watt limit: I normally run a little less, but when I first tried this I actually forgot I had set the limit to 300 (it's a hot day, I figured why fight the A/C?), and at 300 watts the same question came back at 69.38 t/s. (The extra power matters more for compute bound things, the difference in generating LTX2.3 videos is considerably higher... but still not linear.)
Not a shareholder, but on first try, it won't do it because it recognizes Iger's name. And clearly the deal is fresh because it balked at Mickey Mouse too. But it has no trouble with just, "mouse": https://sora.chatgpt.com/p/s_693ae0d25bbc819188f6758fce3f90c...
Did you test some local image gen software in that you installed the Python code on the github page for a local model, which is clearly a LOT for a normal user... or did you look at ComfyUI, which is how most people are running local video and image models? There are "just install this" versions, which eases the path for users (but it's still, admittedly, chaos beneath the surface).
Interesting you say that. No I've tried out Invoke and AUTOMATIC1111/WebUI. I specifically avoided ComfyUI because of my inexperience in this and the fact that people described it as a much more advanced system with manual wiring of the pipeline and so on.
It's likely that I'm seeing this from my deep into ComfyUI bubble. My impression was that AUTOMATIC1111 and Forge and the like, were fading as ComfyUI was the "what people ended up on" no matter which AI generation framework they started with. But I don't know that there are any real stats on usage of these programs, so it's entirely possible that AUTOMATIC1111/Forge/InvokeAI are being used by more people than ComfyUI.
I think there are actually more school shootings than mass shootings because mass requires ~4 victims and school doesn't. There were ~330 shootings in 2024. 70 people died. 200 wounded.
Some content is truly exactly 24 FPS or 30 FPS though, so whichever path the TV goes (i.e. NTSC rate or integer rate) the same problem will exist. I suppose some TVs might have extremely fancy film mode detection which catches the occasional frame difference, but I doubt mine does :D
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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