If you want to play with this, as in really play, with over a dozen variant models with acceleration loras and a vibrant community, ya gotta check out:
"Wan2GP" is AI video and images "for the GPU poor", get all this operating with as little as 6GB VRAM, Nvidia only.
diggan · 6h ago
On the other side, is there any projects focusing on performance instead? I have the VRAM available to run Wan2.1, but still takes minutes per frame. Basically something like what vLLM is for running local LLM weights, but for video/WAN?
There are a lot of people focused on performance, various methods, just as there are a lot of people focused on non-performance issues like fine tunes that add aspects the models lack, such as terminology linking professional media terms to the model, the pop culture terminology the model does not know, accuracy of body posture during fight, dance, gymnastic, and sports activity, and then less flashy but pragmatic actions like proper use of tableware, chopsticks, keyboards and musical instruments - complex actions that stand out when done incorrectly or never shown. The model knowledge is high but has limits, which people are adding.
bsenftner · 4h ago
There is also a ton of Wan video activity in the ComfyUI community. Everyday for a while, about two weeks ago, ComfyUI had updates specific to Wan 2.2 video integrations in the standard installation. ComfyUI is more complex application, significantly, than Wan2GP though.
bobajeff · 4h ago
If having only 6GB VRAM is GPU poor then I must be GPU destitute.
hirako2000 · 3h ago
It's hard to get an nvidia consumer having then less than 12GB of VRAM, not just these days.
By GPU poor they didn't mean GPUless or GPU of the previous decade. It's on the readme that only Nvidia is supported.
hypercube33 · 2h ago
I wish they'd state suggested or required hardware upfront.
Also disappointing that I haven't seen anything target the new Ryzen AI chips that can do 96gb since they seem pretty capable. I'm not sure how much memory m4 pro on the apple side can be utilized for this but it seems like the typical machines are 48 or 64gb these days. Lot more bang for your buck than an Nvidia card on paper?
ahmedhawas123 · 1h ago
Are there video generation benchmarks similar to how there are benchmarks for LLMs? Reason I ask is because with lots of these models you have to go through a long cycle to get them up and running before you see an output, and often they will break with basic tasks requiring physics, state, etc. Would love to see some comparison of models across basic things like that.
franky47 · 5h ago
Quick, someone make a UI for this and call it Obi.
No comments yet
cuuupid · 2h ago
I’ve been using this via Replicate for a while and it’s honestly amazing while being way cheaper. China is definitely leading on open source
danielbln · 1h ago
*open weights
cubefox · 7h ago
Arguably most interesting facts about the new Wan 2.2 model:
- they are now using a 27B MoE architecture (with two 14B experts, for low level and high level detail), which were usually only used for autoregressive LLMs rather than diffusion models
- the smaller 5B model supports up to 720p24 video and runs on 24 GB of VRAM, e.g. an RTX 4090, a consumer graphics card
- if their benchmarks are reliable, the model performance is SOTA even compared to closed source models
mandeepj · 4h ago
> - the smaller 5B model supports up to 720p24 video and runs on 24 GB of VRAM, e.g. an RTX 4090, a consumer graphics card
Seems like you can run it 2 Gpus each having 12 GB VRAM. At least, a breakdown on their GitHub page implied so.
ProofHouse · 8h ago
How can they manage that but not the website?
esseph · 9h ago
Ugh hate they used this name
yorwba · 9h ago
You can call it Wanxiang (万相, ten thousand pictures) if you want. Similarly, Qwen is Qianwen (千问, one thousand questions).
CapsAdmin · 9h ago
Its original name was WanX, but the gen ai community found that to be too funny / unfortunate, so they changed it to just Wan.
bn-l · 4h ago
It’s probably a more appropriate name to be fair.
latentsea · 9h ago
They should just pretend it's an acronym. Wide Art Network.
qiine · 6h ago
ha TIL, very cool names!
diggan · 3h ago
Why "hate" this name more than any other name? At least justify your semi-spam.
https://github.com/deepbeepmeep/Wan2GP
And the discord community: https://discord.gg/g7efUW9jGV
"Wan2GP" is AI video and images "for the GPU poor", get all this operating with as little as 6GB VRAM, Nvidia only.
There are a lot of people focused on performance, various methods, just as there are a lot of people focused on non-performance issues like fine tunes that add aspects the models lack, such as terminology linking professional media terms to the model, the pop culture terminology the model does not know, accuracy of body posture during fight, dance, gymnastic, and sports activity, and then less flashy but pragmatic actions like proper use of tableware, chopsticks, keyboards and musical instruments - complex actions that stand out when done incorrectly or never shown. The model knowledge is high but has limits, which people are adding.
By GPU poor they didn't mean GPUless or GPU of the previous decade. It's on the readme that only Nvidia is supported.
Also disappointing that I haven't seen anything target the new Ryzen AI chips that can do 96gb since they seem pretty capable. I'm not sure how much memory m4 pro on the apple side can be utilized for this but it seems like the typical machines are 48 or 64gb these days. Lot more bang for your buck than an Nvidia card on paper?
No comments yet
- they are now using a 27B MoE architecture (with two 14B experts, for low level and high level detail), which were usually only used for autoregressive LLMs rather than diffusion models
- the smaller 5B model supports up to 720p24 video and runs on 24 GB of VRAM, e.g. an RTX 4090, a consumer graphics card
- if their benchmarks are reliable, the model performance is SOTA even compared to closed source models
Seems like you can run it 2 Gpus each having 12 GB VRAM. At least, a breakdown on their GitHub page implied so.