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
Follow DeepBeepMeep on Twitter/X to get the Latest News: https://x.com/deepbeepmeep
WanGP exclusive: VRAM requirements have never been that low !
Wan 2.2 Ovi 10 GB for all the GPU Poors of the World: only 6 GB of VRAM to generate 121 frames at 720p. With 16 GB of VRAM, you may even be able to load all the model in VRAM with Memory Profile 3
To get the x10 speed effect just apply the FastWan Lora Accelerator that comes prepackaged with Ovi (acccessible in the dropdown box Settings at the top)
After thorough testing it appears that Pytorch 2.8 is causing RAM memory leaks when switching models as it won't release all the RAM. I could not find any workaround. So the default Pytorch version to use with WanGP is back to Pytorch 2.7 Unless you want absolutely to use Pytorch compilation which is not stable with Pytorch 2.7 with RTX 50xx , it is recommended to switch back to Pytorch 2.7.1 (tradeoff between 2.8 and 2.7):
cd Wan2GP
conda activate wan2gp
pip install torch==2.7.1 torchvision torchaudio --index-url https://download.pytorch.org/whl/test/cu128
You will need to reinstall SageAttention FlashAttnetion, ...
update v9.21: Got FastWan to work with Ovi: it is now 10 times faster ! (not including the VAE) update v9.25: added Chroma Radiance october edition + reverted to pytorch 2.7
With WanGP v9 you will have enough features to go to a desert island with no internet connection and comes back with a full Hollywood movie.
First here are the new models supported:
Upgraded Features:
Huge Kudos & Thanks to Tophness that has outdone himself with these Great Features:
WanGP v9 is now targetting Pytorch 2.8 although it should still work with 2.7, don't forget to upgrade by doing:
pip install torch==2.8.0 torchvision torchaudio --index-url https://download.pytorch.org/whl/test/cu128
You will need to upgrade Sage Attention or Flash (check the installation guide)
Update info: you might have some git error message while upgrading to v9 if WanGP is already installed. Sorry about that if that's the case, you will need to reinstall WanGP. There are two different ways to fix this issue while still preserving your data:
cd installation_path_of_wangp
git fetch origin && git reset --hard origin/main
pip install -r requirements.txt
This new version hasn't any new model...
...but temptation to upgrade will be high as it contains a few Loras related features that may change your Life:
Ready to use Loras Accelerators Profiles per type of model that you can apply on your current Generation Settings. Next time I will recommend a Lora Accelerator, it will be only one click away. And best of all of the required Loras will be downloaded automatically. When you apply an Accelerator Profile, input fields like the Number of Denoising Steps Activated Loras, Loras Multipliers (such as "1;0 0;1" ...) will be automatically filled. However your video specific fields will be preserved, so it will be easy to switch between Profiles to experiment. With WanGP 8.993, the Accelerator Loras are now merged with *Non Accelerator Loras". Things are getting too easy...
Embedded Loras URL : WanGP will now try to remember every Lora URLs it sees. For instance if someone sends you some settings that contain Loras URLs or you extract the Settings of Video generated by a friend with Loras URLs, these URLs will be automatically added to WanGP URL Cache. Conversely everything you will share (Videos, Settings, Lset files) will contain the download URLs if they are known. You can also download directly a Lora in WanGP by using the Download Lora button a the bottom. The Lora will be immediatly available and added to WanGP lora URL cache. This will work with Hugging Face as a repository. Support for CivitAi will come as soon as someone will nice enough to post a GitHub PR ...
.lset file supports embedded Loras URLs. It has never been easier to share a Lora with a friend. As a reminder a .lset file can be created directly from WanGP Web Interface and it contains a list of Loras and their multipliers, a Prompt and Instructions how to use these loras (like the Lora's Trigger). So with embedded Loras URL, you can send an .lset file by email or share it on discord: it is just a 1 KB tiny text, but with it other people will be able to use Gigabytes Loras as these will be automatically downloaded.
I have created the new Discord Channel share-your-settings where you can post your Settings or Lset files. I will be pleased to add new Loras Accelerators in the list of WanGP *Accelerators Profiles if you post some good ones there.
With the 8.993 update, I have added support for Scaled FP8 format. As a sample case, I have created finetunes for the Wan 2.2 PalinGenesis Finetune which is quite popular recently. You will find it in 3 flavors : t2v, i2v and Lightning Accelerated for t2v.
The Scaled FP8 format is widely used as it the format used by ... ComfyUI. So I except a flood of Finetunes in the share-your-finetune channel. If not it means this feature was useless and I will remove it πππ
Not enough Space left on your SSD to download more models ? Would like to reuse Scaled FP8 files in your ComfyUI Folder without duplicating them ? Here comes WanGP 8.994 Multiple Checkpoints Folders : you just need to move the files into different folders / hard drives or reuse existing folders and let know WanGP about it in the Config Tab and WanGP will be able to put all the parts together.
Last but not least the Lora's documentation has been updated.
update 8.991: full power of Vace Lynx unleashed with new combinations such as Landscape + Face / Clothes + Face / Injectd Frame (Start/End frames/...) + Face update 8.992: optimized gen with Lora, should be 10% faster if many loras update 8.993: Support for Scaled FP8 format and samples Paligenesis finetunes, merged Loras Accelerators and Non Accelerators update 8.994: Added custom checkpoints folders update 8.999: fixed a lora + fp8 bug and version sync for the jump to the unknown
This new version of WanGP introduces Wan 2.1 Lynx the best Control Net so far to transfer Facial Identity. You will be amazed to recognize your friends even with a completely different hair style. Congrats to the Byte Dance team for this achievement. Lynx works quite with well Fusionix t2v 10 steps.
WanGP 8.9 also illustrate how existing WanGP features can be easily combined with new models. For instance with Lynx you will get out of the box Video to Video and Image/Text to Image.
Another fun combination is Vace + Lynx, which works much better than Vace StandIn. I have added sliders to change the weight of Vace & Lynx to allow you to tune the effects.
See full changelog: Changelog
One-click installation:
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==2.7.1 torchvision torchaudio --index-url https://download.pytorch.org/whl/test/cu128
pip install -r requirements.txt
Run the application:
python wgp.py
Update the application: If using Pinokio use Pinokio to update otherwise: Get in the directory where WanGP is installed and:
git pull
conda activate wan2gp
pip install -r requirements.txt
if you get some error messages related to git, you may try the following (beware this will overwrite local changes made to the source code of WanGP):
git fetch origin && git reset --hard origin/main
conda activate wan2gp
pip install -r requirements.txt
For Debian-based systems (Ubuntu, Debian, etc.):
./run-docker-cuda-deb.sh
This automated script will:
Docker environment includes:
Supported GPUs: RTX 40XX, RTX 30XX, RTX 20XX, GTX 16XX, GTX 10XX, Tesla V100, A100, H100, and more.
For detailed installation instructions for different GPU generations:
For detailed installation instructions for different GPU generations:
Made with β€οΈ by DeepBeepMeep
Python
98.8%
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
Follow DeepBeepMeep on Twitter/X to get the Latest News: https://x.com/deepbeepmeep
WanGP exclusive: VRAM requirements have never been that low !
Wan 2.2 Ovi 10 GB for all the GPU Poors of the World: only 6 GB of VRAM to generate 121 frames at 720p. With 16 GB of VRAM, you may even be able to load all the model in VRAM with Memory Profile 3
To get the x10 speed effect just apply the FastWan Lora Accelerator that comes prepackaged with Ovi (acccessible in the dropdown box Settings at the top)
After thorough testing it appears that Pytorch 2.8 is causing RAM memory leaks when switching models as it won't release all the RAM. I could not find any workaround. So the default Pytorch version to use with WanGP is back to Pytorch 2.7 Unless you want absolutely to use Pytorch compilation which is not stable with Pytorch 2.7 with RTX 50xx , it is recommended to switch back to Pytorch 2.7.1 (tradeoff between 2.8 and 2.7):
cd Wan2GP
conda activate wan2gp
pip install torch==2.7.1 torchvision torchaudio --index-url https://download.pytorch.org/whl/test/cu128
You will need to reinstall SageAttention FlashAttnetion, ...
update v9.21: Got FastWan to work with Ovi: it is now 10 times faster ! (not including the VAE) update v9.25: added Chroma Radiance october edition + reverted to pytorch 2.7
With WanGP v9 you will have enough features to go to a desert island with no internet connection and comes back with a full Hollywood movie.
First here are the new models supported:
Upgraded Features:
Huge Kudos & Thanks to Tophness that has outdone himself with these Great Features:
WanGP v9 is now targetting Pytorch 2.8 although it should still work with 2.7, don't forget to upgrade by doing:
pip install torch==2.8.0 torchvision torchaudio --index-url https://download.pytorch.org/whl/test/cu128
You will need to upgrade Sage Attention or Flash (check the installation guide)
Update info: you might have some git error message while upgrading to v9 if WanGP is already installed. Sorry about that if that's the case, you will need to reinstall WanGP. There are two different ways to fix this issue while still preserving your data:
cd installation_path_of_wangp
git fetch origin && git reset --hard origin/main
pip install -r requirements.txt
This new version hasn't any new model...
...but temptation to upgrade will be high as it contains a few Loras related features that may change your Life:
Ready to use Loras Accelerators Profiles per type of model that you can apply on your current Generation Settings. Next time I will recommend a Lora Accelerator, it will be only one click away. And best of all of the required Loras will be downloaded automatically. When you apply an Accelerator Profile, input fields like the Number of Denoising Steps Activated Loras, Loras Multipliers (such as "1;0 0;1" ...) will be automatically filled. However your video specific fields will be preserved, so it will be easy to switch between Profiles to experiment. With WanGP 8.993, the Accelerator Loras are now merged with *Non Accelerator Loras". Things are getting too easy...
Embedded Loras URL : WanGP will now try to remember every Lora URLs it sees. For instance if someone sends you some settings that contain Loras URLs or you extract the Settings of Video generated by a friend with Loras URLs, these URLs will be automatically added to WanGP URL Cache. Conversely everything you will share (Videos, Settings, Lset files) will contain the download URLs if they are known. You can also download directly a Lora in WanGP by using the Download Lora button a the bottom. The Lora will be immediatly available and added to WanGP lora URL cache. This will work with Hugging Face as a repository. Support for CivitAi will come as soon as someone will nice enough to post a GitHub PR ...
.lset file supports embedded Loras URLs. It has never been easier to share a Lora with a friend. As a reminder a .lset file can be created directly from WanGP Web Interface and it contains a list of Loras and their multipliers, a Prompt and Instructions how to use these loras (like the Lora's Trigger). So with embedded Loras URL, you can send an .lset file by email or share it on discord: it is just a 1 KB tiny text, but with it other people will be able to use Gigabytes Loras as these will be automatically downloaded.
I have created the new Discord Channel share-your-settings where you can post your Settings or Lset files. I will be pleased to add new Loras Accelerators in the list of WanGP *Accelerators Profiles if you post some good ones there.
With the 8.993 update, I have added support for Scaled FP8 format. As a sample case, I have created finetunes for the Wan 2.2 PalinGenesis Finetune which is quite popular recently. You will find it in 3 flavors : t2v, i2v and Lightning Accelerated for t2v.
The Scaled FP8 format is widely used as it the format used by ... ComfyUI. So I except a flood of Finetunes in the share-your-finetune channel. If not it means this feature was useless and I will remove it πππ
Not enough Space left on your SSD to download more models ? Would like to reuse Scaled FP8 files in your ComfyUI Folder without duplicating them ? Here comes WanGP 8.994 Multiple Checkpoints Folders : you just need to move the files into different folders / hard drives or reuse existing folders and let know WanGP about it in the Config Tab and WanGP will be able to put all the parts together.
Last but not least the Lora's documentation has been updated.
update 8.991: full power of Vace Lynx unleashed with new combinations such as Landscape + Face / Clothes + Face / Injectd Frame (Start/End frames/...) + Face update 8.992: optimized gen with Lora, should be 10% faster if many loras update 8.993: Support for Scaled FP8 format and samples Paligenesis finetunes, merged Loras Accelerators and Non Accelerators update 8.994: Added custom checkpoints folders update 8.999: fixed a lora + fp8 bug and version sync for the jump to the unknown
This new version of WanGP introduces Wan 2.1 Lynx the best Control Net so far to transfer Facial Identity. You will be amazed to recognize your friends even with a completely different hair style. Congrats to the Byte Dance team for this achievement. Lynx works quite with well Fusionix t2v 10 steps.
WanGP 8.9 also illustrate how existing WanGP features can be easily combined with new models. For instance with Lynx you will get out of the box Video to Video and Image/Text to Image.
Another fun combination is Vace + Lynx, which works much better than Vace StandIn. I have added sliders to change the weight of Vace & Lynx to allow you to tune the effects.
See full changelog: Changelog
One-click installation:
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==2.7.1 torchvision torchaudio --index-url https://download.pytorch.org/whl/test/cu128
pip install -r requirements.txt
Run the application:
python wgp.py
Update the application: If using Pinokio use Pinokio to update otherwise: Get in the directory where WanGP is installed and:
git pull
conda activate wan2gp
pip install -r requirements.txt
if you get some error messages related to git, you may try the following (beware this will overwrite local changes made to the source code of WanGP):
git fetch origin && git reset --hard origin/main
conda activate wan2gp
pip install -r requirements.txt
For Debian-based systems (Ubuntu, Debian, etc.):
./run-docker-cuda-deb.sh
This automated script will:
Docker environment includes:
Supported GPUs: RTX 40XX, RTX 30XX, RTX 20XX, GTX 16XX, GTX 10XX, Tesla V100, A100, H100, and more.
For detailed installation instructions for different GPU generations:
For detailed installation instructions for different GPU generations:
Made with β€οΈ by DeepBeepMeep
Python
98.8%