WanGP by DeepBeepMeep : The best Open Source Video Generative Models Accessible to the GPU Poor
WanGP supports the Wan (and derived models), Hunyuan Video and LTV Video models with:
Discord Server to get Help from Other Users and show your Best Videos: https://discord.gg/g7efUW9jGV
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This is your lucky day ! thanks to new configuration options that will let you store generated Videos and Images in lossless compressed formats, you will find they in fact they look two times better without doing anything !
Just kidding, they will be only marginally better, but at least this opens the way to professionnal editing.
Support:
Also you can now choose different output directories for images and videos.
unexpected luck: fixed lightning 8 steps for Qwen, and lightning 4 steps for Wan 2.2, now you just need 1x multiplier no weird numbers. update 7.777 : oops got a crash a with FastWan ? Luck comes and goes, try a new update, maybe you will have a better chance this time update 7.7777 : Sometime good luck seems to last forever. For instance what if Qwen Lightning 4 steps could also work with WanGP ?
We have a funny one here today: FastWan 2.2 5B, the Fastest Video Generator, only 20s to generate 121 frames at 720p. The snag is that VAE is twice as slow... Thanks to Kijai for extracting the Lora that is used to build the corresponding finetune.
WanGP 7.76: fixed the messed up I did to i2v models (loras path was wrong for Wan2.2 and Clip broken)
Added support for Qwen Lightning lora for a 8 steps generation (https://huggingface.co/lightx2v/Qwen-Image-Lightning/blob/main/Qwen-Image-Lightning-8steps-V1.0.safetensors). Lora is not normalized and you can use a multiplier around 0.1.
Mag Cache support for all the Wan2.2 models Don't forget to set guidance to 1 and 8 denoising steps , your gen will be 7x faster !
Ever wondered what impact not using Guidance has on a model that expects it ? Just look at Qween Image in WanGP 7.71 whose outputs were erratic. Somehow I had convinced myself that Qwen was a distilled model. In fact Qwen was dying for a negative prompt. And in WanGP 7.72 there is at last one for him.
As Qwen is not so picky after all I have added also quantized text encoder which reduces the RAM requirements of Qwen by 10 GB (the text encoder quantized version produced garbage before)
Unfortunately still the Sage bug for older GPU architectures. Added Sdpa fallback for these architectures.
7.73 update: still Sage / Sage2 bug for GPUs before RTX40xx. I have added a detection mechanism that forces Sdpa attention if that's the case
This release comes with two new models :
There is catch though, they are very picky if you want to get good generations: first they both need lots of steps (50 ?) to show what they have to offer. Then for Qwen Image I had to hardcode the supported resolutions, because if you try anything else, you will get garbage. Likewise Wan 2.2 5B will remind you of Wan 1.0 if you don't ask for at least 720p.
7.71 update: Added VAE Tiling for both Qwen Image and Wan 2.2 TextImage to Video 5B, for low VRAM during a whole gen.
With this new version you won't have any excuse if there is no sound in your video.
Continue Video now works with any video that has already some sound (hint: Multitalk ).
Also, on top of MMaudio and the various sound driven models I have added the ability to use your own soundtrack.
As a result you can apply a different sound source on each new video segment when doing a Continue Video.
For instance:
To multiply the combinations I have also implemented Continue Video with the various image2video models.
Also:
Here is now Wan 2.2 image2video a very good model if you want to set Start and End frames. Two Wan 2.2 models delivered, only one to go ...
Please note that although it is an image2video model it is structurally very close to Wan 2.2 text2video (same layers with only a different initial projection). Given that Wan 2.1 image2video loras don't work too well (half of their tensors are not supported), I have decided that this model will look for its loras in the text2video loras folder instead of the image2video folder.
I have also optimized RAM management with Wan 2.2 so that loras and modules will be loaded only once in RAM and Reserved RAM, this saves up to 5 GB of RAM which can make a difference...
And this time I really removed Vace Cocktail Light which gave a blurry vision.
Wan 2.2 is here. The good news is that WanGP wont require a single byte of extra VRAM to run it and it will be as fast as Wan 2.1. The bad news is that you will need much more RAM if you want to leverage entirely this new model since it has twice has many parameters.
So here is a preview version of Wan 2.2 that is without the 5B model and Wan 2.2 image to video for the moment.
However as I felt bad to deliver only half of the wares, I gave you instead .....** Wan 2.2 Vace Experimental Cocktail** !
Very good surprise indeed, the loras and Vace partially work with Wan 2.2. We will need to wait for the official Vace 2.2 release since some Vace features are broken like identity preservation
Bonus zone: Flux multi images conditions has been added, or maybe not if I broke everything as I have been distracted by Wan...
7.4 update: I forgot to update the version number. I also removed Vace Cocktail light which didnt work well.
While waiting for Wan 2.2, you will appreciate the model selection hierarchy which is very useful to collect even more models. You will also appreciate that WanGP remembers which model you used last in each model family.
I am really convinced that Vace can do everything the other models can do and in a better way especially as Vace can be combined with Multitalk.
Here are some new Vace improvements:
Also you will enjoy our new real time statistics (CPU / GPU usage, RAM / VRAM used, ... ). Many thanks to Redtash1 for providing the framework for this new feature ! You need to go in the Config tab to enable real time stats.
Flux Family Reunion : Flux Dev and Flux Schnell have been invited aboard WanGP. To celebrate that, Loras support for the Flux diffusers format has also been added.
LTX Video upgraded to version 0.9.8: you can now generate 1800 frames (1 min of video !) in one go without a sliding window. With the distilled model it will take only 5 minutes with a RTX 4090 (you will need 22 GB of VRAM though). I have added options to select higher humber frames if you want to experiment (go to Configuration Tab / General / Increase the Max Number of Frames, change the value and restart the App)
LTX Video ControlNet : it is a Control Net that allows you for instance to transfer a Human motion or Depth from a control video. It is not as powerful as Vace but can produce interesting things especially as now you can generate quickly a 1 min video. Under the scene IC-Loras (see below) for Pose, Depth and Canny are automatically loaded for you, no need to add them.
LTX IC-Lora support: these are special Loras that consumes a conditional image or video Beside the pose, depth and canny IC-Loras transparently loaded there is the detailer (https://huggingface.co/Lightricks/LTX-Video-ICLoRA-detailer-13b-0.9.8) which is basically an upsampler. Add the detailer as a Lora and use LTX Raw Format as control net choice to use it.
Matanyone is now also for the GPU Poor as its VRAM requirements have been divided by 2! (7.12 shadow update)
Easier way to select video resolution
This release turns the Wan models into Image Generators. This goes way more than allowing to generate a video made of single frame :
And to complete the full suite of AI Image Generators, Ladies and Gentlemen please welcome for the first time in WanGP : Flux Kontext.
As a reminder Flux Kontext is an image editor : give it an image and a prompt and it will do the change for you.
This highly optimized version of Flux Kontext will make you feel that you have been cheated all this time as WanGP Flux Kontext requires only 8 GB of VRAM to generate 4 images at the same time with no need for quantization.
WanGP v7 comes with Image2image vanilla and Vace FusinoniX. However you can build your own finetune where you will combine a text2video or Vace model with any combination of Loras.
Also in the news:
Maybe you knew that already but most Loras accelerators we use today (Causvid, FusioniX) don't use Guidance at all (that it is CFG is set to 1). This helps to get much faster generations but the downside is that Negative Prompts are completely ignored (including the default ones set by the models). NAG (https://github.com/ChenDarYen/Normalized-Attention-Guidance) aims to solve that by injecting the Negative Prompt during the attention processing phase.
So WanGP 6.7 gives you NAG, but not any NAG, a Low VRAM implementation, the default one ends being VRAM greedy. You will find NAG in the General advanced tab for most Wan models.
Use NAG especially when Guidance is set to 1. To turn it on set the NAG scale to something around 10. There are other NAG parameters NAG tau and NAG alpha which I recommend to change only if you don't get good results by just playing with the NAG scale. Don't hesitate to share on this discord server the best combinations for these 3 parameters.
The authors of NAG claim that NAG can also be used when using a Guidance (CFG > 1) and to improve the prompt adherence.
Vace our beloved super Control Net has been combined with Multitalk the new king in town that can animate up to two people speaking (Dual Voices). It is accelerated by the Fusionix model and thanks to Sliding Windows support and Adaptive Projected Guidance (much slower but should reduce the reddish effect with long videos) your two people will be able to talk for very a long time (which is an Infinite amount of time in the field of video generation).
Of course you will get as well Multitalk vanilla and also Multitalk 720p as a bonus.
And since I am mister nice guy I have enclosed as an exclusivity an Audio Separator that will save you time to isolate each voice when using Multitalk with two people.
As I feel like resting a bit I haven't produced yet a nice sample Video to illustrate all these new capabilities. But here is the thing, I ams sure you will publish in the Share Your Best Video channel your Master Pieces. The best ones will be added to the Announcements Channel and will bring eternal fame to its authors.
But wait, there is more:
Also, of interest too:
Taking care of your life is not enough, you want new stuff to play with ?
If you had upgraded to v6.5 please upgrade again to 6.5.1 as this will fix a bug that ignored Loras beyond the first one
See full changelog: Changelog
One-click installation: Get started instantly with Pinokio App
Manual installation:
git clone https://github.com/deepbeepmeep/Wan2GP.git
cd Wan2GP
conda create -n wan2gp python=3.10.9
conda activate wan2gp
pip install torch==2.7.0 torchvision torchaudio --index-url https://download.pytorch.org/whl/test/cu128
pip install -r requirements.txt
Run the application:
python wgp.py # Text-to-video (default)
python wgp.py --i2v # Image-to-video
Update the application: If using Pinokio use Pinokio to update otherwise: Get in the directory where WanGP is installed and:
git pull pip install -r requirements.txt
For detailed installation instructions for different GPU generations:
Made with ❤️ by DeepBeepMeep