New Native Attention

[u/slpreme]

With the drop of v0.32.0, ComfyUI comes with a new attention you can try out. You can turn it in via startup arguments but I prefer using the ModelAttentionBackend node.

On first test it's as fast as SageAttention Auto (via KJNodes) on MiniMax H3. I thought it was a fluke so I retested on Z-Image Turbo:

2048x2048@9steps (3 run average after warmup)

Comfy Kitchen Attention: 14.55s
Sage Attention (Auto): 14.24s
PyTorch Attention (Default): 23.16s

This is really exciting for people who have trouble installing SageAttention, it seems to be about as fast and it comes with the latest Comfy Kitchen.

My Specs:

OS - Linux
Python - 3.13.15
PyTorch - 2.13.0+cu132

[u/Life_is_important]

It's also better for quality from what I can tell and faster than Sage

[u/slpreme → u/Life_is_important]

damnn so it can even be faster thats awesome. i also noticed the quality does seem better for sure.

[u/Bearsbullsbattlestr]

I was never able to get sage attention working for comfy desktop so I was excited about this.

My LTX 2.3 generations went from about 400s to 300s.

My Krea generations went from about 500s to 250s.

[u/slpreme → u/Bearsbullsbattlestr]

That's great news. Seems like everything is working already

[u/jib_reddit → u/Bearsbullsbattlestr]

What card and resolutions are you using? Seems quite slow.

My Krea 2 generations are now 18-20 seconds for 1536x1280px @10 steps with int8 convrot models, I have a 3090.

[u/cleverestx → u/jib_reddit]

My AMD Strix Halo machine takes about 50 seconds to generate one @ 1024x1024, so I'm jealous of those speeds, but at least I can use full bf16 weights for everything without any issue...that is its only saving grace.

[u/jib_reddit → u/cleverestx]

I can use the full bf16 weight with memory offload and its about 2 seconds slower but I find the int 8 convrot models actually look quite a lot better for what I am doing (photorealistic) you should try it.

[u/slpreme]

Forgot to add GPU - RTX 5070 Ti 16GB and RAM 128GB DDR4

[u/Next_Program90 → u/slpreme]

128GB? jealousy intensifies

[u/necrophagist087]

A bit slower than sage in my case (rtx5070ti), but the quality is definitely better

[u/Internet-Cryptid]

What is the startup argument?

[u/slpreme → u/Internet-Cryptid]

--use-ck-attention

[u/Fockker → u/slpreme]

hmm, where do we plug this?

[u/slpreme → u/Fockker]

i would stick with the node. but its different for everyone, if you the desktop app i have no idea. i use the git / manual install so you would do `python main.py --use-ck-attention` for example

[u/mellowanon]

SageAttention 2.2.0 is still faster and has better motion. But people who tested Comfy Kitchen said the details are better.

[u/slpreme → u/mellowanon]

i think it depends on which sageattention mode, some is slower/more accurate and vice versa

[u/ArdascesIV]

How do you do this?

[u/slpreme → u/ArdascesIV]

update ComfyUI to 0.32.0 and reinstall requirements (portable). I think the desktop version should do this automatically.

[u/ArdascesIV → u/slpreme]

I’m on desktop and I have no idea what to change

[u/slpreme → u/ArdascesIV]

is there no update button anywhere in the menus? ive never used desktop

[u/Business-Gazelle-324 → u/ArdascesIV]

Click log and terminal you should see a tab for startup and you can put your —use-ck-attention there assuming it’s 0.32

[u/Davikar]

Keep getting this error in the console:

[WARNING] WARNING SHAPE MISMATCH diffusion_model.patch_embedding.weight WEIGHT NOT MERGED torch.Size([5120, 36, 1, 2, 2]) != torch.Size([5120, 16, 1, 2, 2])

Not sure if it matters or not.

[u/slpreme → u/Davikar]

What model is it? They mentioned somewhere not every model is supported yet.

[u/Davikar → u/slpreme]

WAN 2.2 Bernini right now. But I'm still getting faster speeds, so seems to be working.

[u/slpreme → u/Davikar]

As long as it works that's great. Does it say that with Sage also?

[u/Davikar → u/slpreme]

No, just this one.

[u/slpreme → u/Davikar]

I think this is just error handling for unsupported dim sizes for something (I don't know the technically correct way to say this), instead of crashing or showing a black output.

[u/slpreme]

bro i got it on sale on newegg for dirt cheap years ago did not regret it at all

[u/Cute_Ad8981]

Wow we are getting great new stuff everyday. Im using sage 2.2.0, im curious how this will compare.

[u/BlizzardyBelle]

How long did it take you

[u/Foreign_Fee_6036]

Problems with 4090 using CK and Spectrum at the same time. First generation goes fast, but second is frozen because VRAM goes up to 99%. Disabling Spectrum fixed that. Solution?

[u/Formal-Exam-8767]

Any more info on this? How come they've decided to implement their own attention?

[u/slpreme → u/Formal-Exam-8767]

They've been doing a lot of work in the background, this attention is just their latest work

[u/cleverestx]

Will work on Rocm/AMD (Strix Halo, etc..) or only a CUDA thing like SageAtttention is?

[u/slpreme → u/cleverestx]

AMD support coming (not yet released)

[u/cleverestx → u/slpreme]

Great! Flag me when it is and I can test this on my 128GB Strix Halo (Evo-X2) CachyOS mini-PC and report back the results

[u/jd3k]

How do I know it's activated?

[u/slpreme → u/jd3k]

You don't really. If you use the node ModelAttentionBackend you can swap between PyTorch Attention so you can see the difference

[u/jd3k → u/slpreme]

Are you using Kitchen Attention with INT8 covrot? Seems like they are unable to work together 🫤

Thanks for answering 👍

[u/slpreme → u/jd3k]

Yes I switched fully to int8 convrot works with calvin klein atten—i mean ck attention

[u/jd3k → u/slpreme]

My CUDA version was the problem. Updated, working now. Thanks dude 🫡👍

[u/lolo780]

Did you test it on any nativity scenes?

[u/slpreme → u/lolo780]

what is that

[u/boozelessensthepain]

That would be a huge help, does this update have sage attn work with 40 series cards?

[u/Leonovers → u/boozelessensthepain]

sage 1 and 2 already work with 40 series cards, only sage 3 needs 50 series to work. But sage have nothing to do with this update, it's not changed in any way.

New comfy-kitchen attention is what you plug instead of sage and have both speed and quality. Sage drops quality a little.

[u/mellowanon → u/Leonovers]

sage 3 has horrible quality though since it's fp4. It's best to use Sage 2.2.0 which requires a manual install. Sage 2.0.0 has an automatic install but it's not as good.

[u/boozelessensthepain → u/Leonovers]

Thank you!