WanGP
WanGP by DeepBeepMeep : The best Open Source Generative Models Accessible to the GPU Poor
WanGP is a one-stop super app for the best open source generative models across video, image, audio, and text-to-speech.
Highlights
| Modality |
Supported models |
| Video |
Wan 2.1/2.2 and derived models, MiniMax H3, LTX-2/2.3/2.5, Hunyuan Video 1/1.5, LongCat, Kandinsky, LTXV, MagiHuman |
| Image |
Krea 2, Qwen Image, Z-Image, Flux 1/2 (Klein, Chroma), SenseNova, Ideogram 4, HiDream |
| Audio / TTS |
Qwen3 TTS, MiniMax H3 Voice Clone, Ace Step 1/2/XL, Omnivoice, Index TTS2/2.5, KugelAudio, HeartMula, Chatterbox, Minimax Music, Stable Audio 3 |
Run More Models on More Hardware
- Low VRAM requirements: run select models with as little as 6 GB of VRAM.
- Older Nvidia GPU support: use GTX 10XX, RTX 20XX, and newer cards.
- AMD GPU support: run on RDNA 4, 3, 3.5, and 2 hardware; see the Installation section below.
- Fast latest-GPU performance: take advantage of modern GPU acceleration.
- Full web interface: generate, manage, and reuse outputs from an easy browser UI.
- LoRA customization: adapt each model with LoRAs, reuse LoRAs stored in another App.
- Many quantized checkpoint formats: use int8, fp8, gguf, NV FP4, and Nunchaku.
- Architecture-aware downloads: automatically fetch the model files suited to your hardware.
- Finetunes: add your own finetunes / checkpoints or the ones you found on Hugging Face or CivitAI
- Generation queue: line up videos, images, and audio jobs, then come back later.
- Headless mode: launch batches from the command line for images, videos, and audio.
- WanGP API: add generative capabilities to your own apps.
- Video, image, and audio galleries: browse generations and reuse them as new inputs.
- Reusable settings: extract settings from any generation, create templates, and share them.
- Per-model prompt enhancer: improve prompts with model-specific syntax and expectations.
- Input preparation tools: use the mask editor, background remover, pose/depth/flow extractors, speaker diarization, and background noise/song remover.
- Deepy low-VRAM offline agent: orchestrate generation jobs and tedious tasks such as transcription, video splitting, and color-frame generation while you are away.
- Temporal and spatial upsampling: improve outputs with RIFE, FlashVSR, and Lanczos.
- Audio postprocessing: generate soundtracks with MMAudio, replace voices with SeedVC, or remux a video with any soundtrack.
- Ready-to-use plug-ins: Gallery Browser, Motion Designer, Models/Checkpoints Manager, CivitAI browser and downloader, and more.
Discord Server to get Help from the WanGP Community and show your Best Gens: https://discord.gg/g7efUW9jGV
Follow DeepBeepMeep on Twitter/X to get the Latest News: https://x.com/deepbeepmeep
Official WanGP Web Site: https://wangp.ai/
[!IMPORTANT]
WanGP is free to use locally. The official project will never ask you to pay a license fee, subscription, or donation to run WanGP on your own computer (see the license for terms).
Use only the official GitHub repository or wangp.ai / wan2gp.ai websites. WanGP is not affiliated to any other third-party service using the WanGP/Wan2GP names, unless explicitly stated here.
📋 Table of Contents
🔥 Latest Updates :
Thanks to WanGP community contributing code, testing and feedback!
Community Contributions
Live Video Previews: watch motion develop during generation! Under Configuration / General / Generation Preview, choose legacy fast RGB frames, clearer Tiny VAE frames, or a looping Tiny VAE video. Click the video to pause/resume it. Thanks @GOvEy1nw!
YuE2 Score Continuation: the Composition source menu lets you import or extend an ABC score, including scores transcribed from audio. Thanks @Beanow!
FLAC Audio: import FLAC, export 16-bit lossless audio with embedded generation settings, and use FLAC soundtracks in MP4/MKV. Thanks @Beanow!
Balanced x265 Exports: CRF 18 (Balanced) joins CRF 28 (Small) and CRF 8 (High Quality). Thanks @Beanow!
More Patient Media Flow Exports: saving and continuation merges now allow five minutes instead of 30 seconds. Thanks @kito408!
The Enhance Button Stays Put: manual enhancement remains available when automatic enhancement is enabled. Thanks @GKartist75!
Other Additions and Improvements
H3 Welcomes More References: Ref2VA now accepts up to three reference videos and three audio references, alongside its image references. Reference videos share a 15-second budget; audio references share a separate 15-second budget.
H3 Reference Excerpts: pick up to three moments from one reference video, or independently from its soundtrack. Enter positions and optional durations, such as 5s/3s for a three-second excerpt centred on five seconds.
H3 Keeps Your Soundtrack: Ref2VA can now build a video around uploaded speech/music or a reference video's soundtrack, keeping the original audio synchronized across sliding windows. Select an audio choice marked Soundtrack Kept.
H3 Learns to Hold Still: select Text to Image for a single still. The prompt enhancer gains dedicated image prompts, including reference-based edits.
H3 Ref2VA Frames Injection: Ref2VA should be now on par with Fl2VA. But keep in mind, you will get better results with Fl2VA for Start,End,Injected Frames and Text2Video
H3 In-Context LoRAs: Use Control Video as In-Context Guide enables compatible face/character-swap LoRAs. The previous editing mode is renamed Denoise Control Video (Video-to-Video Edit).
H3 ControlNet-Union 2.0: FL2VA 33B and Pruned 20B gain pose, depth, edge, shape and recoloring controls, plus inpainting and spatial outpainting.
Floating Generate Buttons: controls float on the right until their normal position is visible; Edit Mode buttons float too. Enabled by default in Configuration / General.
Three Voices, One Conversation: three uploaded voice references now work with H3 Audio, Qwen3 TTS Base, OmniVoice, KugelAudio, IndexTTS2/2.5, DramaBox and Scenema. Use Speaker 1: through Speaker 3:; Scenema applies its references through SeedVC.
Krea 2 Real and HD VAEs: Krea 2 and compatible Qwen Image 20B/Edit models gain a VAE dropdown: try Real for photographic textures or HD for detail and contrast.
More LoKr Compatibility: Krea 2, Qwen Image, Ming Image and Qwen Image 2.1 gain support for compatible decomposed LoKr adapters.
Deepy Learns Magic Mask: ask Deepy to mask named objects in an image or video, invert the selection, or create simple rectangular masks. The masks go straight into the Gallery for editing.
Deepy Handles RGBA: convert between RGB and RGBA, extract or recombine color channels, and use a grayscale mask as an image's transparency channel.
Deepy Prime Mixes and Muxes: replace a video's soundtrack, mix audio sources, keep separate selectable audio tracks, or add selectable subtitles. The video is preserved without re-encoding.
Faster Deepy and Prompt Enhancement: GGUF CUDA kernels 1.0.25 accelerate speculative decoding for Q4_K and Bonsai PTQ1_0 without extra VRAM. See the installation guide.
24th of September 2026: WanGP v13.1315 — It's Your Lucky Day^?!
- Qwen Image 2.1: A new Qwen Image model with out-of-the-box editing capabilities and strong text rendering.
WanGP supports VRAM Optimization, Pose/Depth/Edge Transfer, Inpainting, LanPaint, Outpainting, KV Cache Acceleration, and Enhanced Prompts from day one.
The base model works without an accelerator; optional LoRA profiles below offer faster 4- to 8-step generation.
Full JIT Checkpoint Loading: WanGP now downloads preprocessing and postprocessing checkpoints only when needed, instead of downloading them all on first use. This saves disk space if you use WanGP for a specific task, such as audio generation, or want to build a portable version of WanGP.
Comfy Kitchen Kernels Support: These kernels are installed automatically and can accelerate specific models. They have been integrated into H3 and LTX2.x, which are now 10% faster.
Minimax H3 INT8 ConvRot VAE: Twice as fast. Now downloaded automatically and used by default when INT8 is selected in your transformer configuration.
Deepy Prime for the Masses: Thanks to the new Bonsai 2 Abliterated PTQ1_0 checkpoint, Deepy Prime and its advanced Prompt Enhancer can now run with 10 GB of VRAM, or possibly less. You will need GGUF CUDA kernels 1.0.25. Please see the installation guide.
UI Optimizations: The UI should be even faster, especially the Image/Video Gallery.
Yue2 Instrumental Model Only: you can now generate instrumentals track only, please check new option in main dropdown box and also prompt instructions or new prompt enhancer templates.
Yue2 Hum to Song: Turn a clear hummed melody, your lyrics and a music style into a new stereo song.
YuE2 support AR LoRAs: YuE2 first phase, is an Auto Regressive phase (score writing phase) and it can now accept LoRAs. LoRAs for second Diffusion phase was already added previously.
DFlash2 & DSpark Acceleration for Deepy & Prompt Enhancer*: for an extra VRAM cost you will be able to generate up tp 200 tokens / s
Various UI Improvements: add directly the current frame of Video Gallery to the Image Gallery, Extract settings of a Video/Audio/Image in Workspace Gallery
Ming Image 0.1 Design: a new image generation and editing model for detailed infographics, posters, and carefully arranged layouts. It accepts standard text prompts and a structured JSON format for more precise control over composition. WanGP's visual Prompt Helper lets you arrange layers and edit their positions, colors, and descriptions. You can also choose a classic or JSON prompt enhancer to turn a short brief into a detailed prompt with explicit titles, labels, and explanations.
Ming Image 0.1 Design-Layer: turn a finished poster, infographic, or other design into separate transparent image layers. Provide one reference image and a text prompt describing the layers from front to back. WanGP adds every RGBA layer to the image gallery and saves a ZIP of the complete layer set. Design and Design-Layer share their language encoder and vision tower checkpoints to reduce downloads and disk use.
Qwen Image 2.1 Viggle Turbo LoRA Accelerators: generate images faster with v0.1 (4 steps), v0.2 (5 steps), or v0.2.1 (6 steps). Select an acceleration profile to apply the matching LoRA, scheduler, and recommended settings. The 6-step profile is the recommended Viggle starting point and is also available in Deepy for image generation and editing.
Qwen Image 2.1 Pruna LoRA Accelerators: choose Pruna v0.1 (5 steps) for speed or the recommended 8-step profile for better quality. Each profile applies its matching LoRA and Pruna scheduler with the correct sigma sequence, guidance 1, and LoRA strength 1.; Pruna's adapters were trained for edits with up to three reference images.
Remove Vocals Audio Postprocessing: create an instrumental version of an audio track by removing its vocals. Available in Post Processing, Late Post Processing, and through Deepy Prime.
Update v13.1313: YuE2 instrumental mode, YuE2 Hum to Song, AR LoRA support, and DFlash2 / DSpark acceleration
Update v13.1314: Ming Image 0.1 Design and Design-Layer, Qwen Image 2.1 Viggle Turbo and Pruna LoRA accelerators, and Remove Vocals audio postprocessing
16th of September 2026: WanGP v13.10 — It's Your Lucky Day!
WanGP Major Release
Upgraded User Interface: a more responsive interface for switching models and browsing media, a modern look, and five color themes, including Classic Gradio. Use the microphone beside a prompt to dictate it, then review and edit the text before generating.
Access Anywhere: start a generation at home and follow it from another browser or device connected to the same running WanGP server (VPN recommended for remote access). Galleries, selected media, progress, and the generation queue stay synchronized, so you can check results and add new jobs. Each Gradio page keeps its own unsent prompts and draft settings.
Clearer Progress and Cancellation: see what WanGP is doing while it downloads files, loads models, encodes prompts, or generates media. Progress bars now cover more stages, and you can request cancellation during preparation as well as generation.
Workspaces: keep generated and imported media organized by project, with collections and selections remembered after restarting WanGP. Switch workspaces between tasks, or open the workspace manager beside the gallery selector to browse the full collection, reorder items, copy or move them between workspaces, and download a selection as a ZIP. Copying media between workspaces does not duplicate the files on disk. See the workspace guide.
Deepy Web App: take Deepy with you in a phone-friendly interface. Upload a photo or recording, describe what you want, and follow the conversation and results from your phone or desktop. Open Web app → in Deepy's settings to find it, and add it to your phone's home screen for quick access. See the Deepy guide. You can use this way both Deepy Zero & Deepy Prime, although you will get best results with Deepy Prime.
Prompt Enhancer Upgrades: when using a Qwen3.5/3.8 powered Prompt Enhancer, now all attached images (Start Image/End Image/Control Image/Ref Images) may be used to produce the enhanced prompt. The prompt enhancer is also given the duration of the video / sliding window you want to generate (this works also when prompt commands like [\duration=3s] are used). Even better multiple sliding windows prompts can be enhanced at the same time based on the actual start/end frames they will see.
New Models
YuE2: turn lyrics and a musical style into a complete song with vocals and accompaniment. The cover workflow can extract melody and chords from a source song to guide a new performance; supply the lyrics separately and keep them aligned with the original sections.
AuK Speech: generate speech from written instructions, or use a source recording for voice cloning, spoken-word edits, speech cleanup, and speaker separation. Choose Flash for a fast four-step result or Base for more control. Start with a short clip and describe both what to change and what to preserve.
LTX2.5 updates: added LTX 2.5 MSR (reference to videos), LTX 2.5 Ingredients is now used when Ref. Images are provided, updated Media Flow processes with LTX 2.5 unblur and uncompress LoRAs
update 13.10: Prompt Enhancer Upgrades, LTX2.5 updates
6th of September 2026: WanGP v12.72 — Power Up, Polish, Pause
H3 VDN: at least 20% Faster and even more on larger / longer videos, requires a bit more VRAM and Triton must be installed
DLSS 5 Neural Rendering — More Than an Upscale: give finished images and videos an AI polish that can enrich lighting and material appearance, improve fine features such as skin, hair, fabric, and foliage, and keep enhancements stable over time. Use x1 for native-resolution refinement or x1.5–x3 to refine and enlarge, with adjustable intensity. WanGP estimates depth and motion for recorded media, so results remain content-dependent. See the DLSS 5 overview and installation guide.
Fast Temporal Upsampling up to x6: DLSS Frame Generation uses a native RTX path designed for real-time multi-frame generation, so it should generally run faster than RIFE on supported hardware while turning low-FPS footage into smoother video. It supports x2–x4 on compatible RTX 40/50 GPUs and x5/x6 where supported on RTX 50. RIFE v4.26 now adds x3 temporal upsampling alongside x2/x4, with no extra native DLSS runtime.
Media Flow / Temporal Upsampling & Neural Engine: DLSS5 / Rife Temporal Upsampling and DLSS5 Neural Engine can now be used in Media Flow, so you can convert your entire collection of stop motion movies.
H3 Voice Audio: a new TTS preset reuses MiniMax H3 Ref2VA Pruned for voice cloning and general audio generation. It accepts one or two audio references, under the hood it denoises a hidden 32x32 video for speed, skips video decoding, and saves only 32 kHz stereo audio.
H3 Outpainting: discover the truth that lies beyond the borders of the H3 frames, also available in Media Flow
H3 Audio Refinement Extra Phase: optionally improve the soundtrack after FL2VA or Ref2VA video generation using 6 extra steps without LoRAs. WanGP preserves the original full-resolution video and audio latents, locks the video exactly, partially re-noises only the audio at 0.5 denoising strength, and then decodes the refined result. The pass deliberately does not re-inject reference media or the original Control Video. It is unavailable when an FL2VA soundtrack controls generation and on fixed 8-step PDD variants.
Viggle Animate: a H3 Based model similar to Wan Animate but 3 steps only. Give Viggle a Control Video and an Edited Frame (the person or object to animate injected in one frame taken from the control video, use a WanGP Image Editor or ask Deepy). Motion is quite good, but model will need to build 5s long sliding windows.
Deepy Goodies:
- Pause and resume Deepy without losing its progress. Pausing temporarily releases its GPU and VRAM resources for another WanGP task or application; an active tool is allowed to finish safely first.
- Optional sessions continuously preserve the conversation, displayed cards, workspace, and media used or generated by Deepy. Resume past work, switch sessions, or rename, duplicate, export, and delete them from the interface.
- Faster responses through decoding optimizations that can improve speed from 50% to 100%, depending on the model and configuration. (please update to the latest GGUF 1.0.24 kernels, see docs/INSTALLATION.md)
- Qwen3.8 27B IQ3_S offers a new middle ground between Q2 and Q4: better quality than Q2 with a lower memory footprint than Q4, while remaining compatible with faster speculative decoding. It may make 16 GB VRAM configurations practical with suitable context settings.
update WanGP v12.72*: H3 Outpainting, Viggle Animate
See full changelog: Changelog
🚀 Quick Start
One-click Bat/SH Script Auto-installer:
The 1-click automated scripts for both Windows (.bat) and Linux/macOS (.sh) make installation, environment management, and updates as seamless as possible. These scripts will not only install WanGP but also best acceleration kernels (Triton, Sage, Flash, GGuf, Lightx2v, Nunchaku) available for your config.
👉 Windows Users: Double-click the .bat files. Linux Users: Run the .sh files in your terminal.
1️⃣ Installation (scripts\install.bat | scripts/install.sh)
Choose Installation Type
- Auto Install
- Manual Install
Manual Install
If you selected Manual Install, you will be guided through:
- Choose your package manager
- Name your environment
- Select your Install Mode
2️⃣ Starting the App (scripts\run.bat | scripts/run.sh)
Once installed, use this script to launch the application. It runs WAN2GP using your active environment.
- ⚙️ Customizing Launch Arguments (
args.txt)
3️⃣ Updating & Upgrading (scripts\update.bat | scripts/update.sh)
Use this script to get the latest updates for WAN2GP and upgrade dependencies.
- 1. Update: Fetches the latest code from GitHub and updates requirements.
- 2. Upgrade: Allows you to manually individually upgrade heavy backend components (like PyTorch, Triton, Sage Attention).
Triton recommendations follow both your GPU and selected PyTorch: 3.3.x with PyTorch 2.7, 3.6.x with PyTorch 2.10 on RTX 30XX or newer, 3.2.x on RTX 20XX, and 3.7.x with PyTorch 2.13 on AMD. Use Upgrade to correct an older Triton installation; Update alone does not change it.
4️⃣ Managing Environments (scripts\manage.bat | scripts/manage.sh)
Use this script to manage and switch between your sandboxed environments safely.
One-click Installers
Pinokio installer
Get started instantly with Pinokio App
It is recommended to use in Pinokio the Community Scripts wan2gp or wan2gp-amd by Morpheus rather than the official Pinokio install.
Wan2GP Desktop by GKArtist
Wan2GP Desktop is a desktop launcher for Wan2GP that installs, updates, and runs it from one window — handling Git, Python, CUDA, and PyTorch setup so you don't have to configure them manually.
Manual installation: (for RTX20xx - RTX50xx)
git clone https://github.com/deepbeepmeep/Wan2GP.git
cd Wan2GP
conda create -n wan2gp python=3.11.14
conda activate wan2gp
pip install torch==2.10.0 torchvision==0.25.0 torchaudio==2.10.0 --index-url https://download.pytorch.org/whl/cu130
pip install -r requirements.txt
On Windows, install Triton in the same environment, using the command matching your GPU and PyTorch:
| GPU |
PyTorch |
Command |
| RTX 30XX - RTX 50XX |
2.10 (recommended) |
python -m pip install -U "triton-windows>=3.6,<3.7" |
| RTX 30XX - RTX 50XX |
2.7 / 2.7.1 |
python -m pip install -U "triton-windows>=3.3,<3.4" |
| RTX 20XX |
2.7 or 2.10 (legacy Triton compatibility exception) |
python -m pip install -U "triton-windows>=3.2,<3.3" |
Triton 3.2 on RTX 30XX or newer can crash YuE2's optimized INT8 ConvRot kernels because it lacks triton.language.gather. Upgrade Triton as above and restart WanGP. RTX 20XX must stay on 3.2 and uses the existing standard INT8 path; compatibility with newer PyTorch is not guaranteed upstream. RTX 50XX users should use PyTorch 2.10 / Triton 3.6 for WanGP's optimized INT8 and NV FP4 support. Linux normally receives matching Triton through PyTorch. See the Triton Installation Guide for details and RTX 20XX limitations.
For optimized attention, install SageAttention 1.0.6 on RTX 20XX and SageAttention 2.2.0 on RTX 30XX or newer. SageAttention 2 requires an Ampere-or-newer GPU; GTX 10XX should use SDPA. See the Installation Guide for the platform-specific commands.
Manual installation: (for GTX 10xx)
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==0.22.1 torchaudio==2.7.1 --index-url https://download.pytorch.org/whl/test/cu128
pip install -r requirements.txt
Run the application:
python wgp.py
If you are low on VRAM, there is a trick to increase the amount of VRAM available (between 1GB and 5GB of VRAM to be gained depending on the GPU): disable GPU Usage in your Web Browser.
Run scripts/start-chrome-no-gpu.bat or scripts/start-chrome-no-gpu.sh to launch Chrome without using your GPU.
First time using WanGP ? Just check the Guides tab, and you will find a selection of recommended models to use.
Update the application (stay in the current python / pytorch version):
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
Upgrade from Python 3.10, Pytorch 2.7.1, Cuda 12.8 to Python 3.11, Pytorch 2.10, Cuda 13/13.1 (for non GTX10xx users)
I recommend renaming first the old conda environment to avoid bad surprises when installing a different config in this old environment.
conda rename -n wan2gp old_wan2gp
Get in the directory where WanGP is installed and:
git pull
conda create -n wan2gp python=3.11.9
conda activate wan2gp
pip install torch==2.10.0 torchvision==0.25.0 torchaudio==2.10.0 --index-url https://download.pytorch.org/whl/cu130
pip install -r requirements.txt
Once you are done you will have to reinstall Sage Attention, Triton, Flash Attention. Check the Installation Guide -
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
When you have the confirmation it works well you can then delete the old conda env:
conda uninstall -n old_wan2gp --all
Run headless (batch processing):
Process saved queues without launching the web UI:
# Process a saved queue
python wgp.py --process my_queue.zip
Create your queue in the web UI, save it with "Save Queue", then process it headless. See CLI Documentation for details.
🐳 Docker:
For Debian-based systems (Ubuntu, Debian, etc.):
./run-docker-cuda-deb.sh
This automated script will:
- Detect your GPU model and VRAM automatically
- Select optimal CUDA architecture for your GPU
- Install NVIDIA Docker runtime if needed
- Build a Docker image with all dependencies
- Run WanGP with optimal settings for your hardware
Docker environment includes:
- NVIDIA CUDA 12.4.1 with cuDNN support
- PyTorch 2.6.0 with CUDA 12.4 support
- SageAttention compiled for your specific GPU architecture
- Optimized environment variables for performance (TF32, threading, etc.)
- Automatic cache directory mounting for faster subsequent runs
- Current directory mounted in container - all downloaded models, loras, generated videos and files are saved locally
Supported GPUs: RTX 40XX, RTX 30XX, RTX 20XX, GTX 16XX, GTX 10XX, Tesla V100, A100, H100, and more.
📦 Installation
Nvidia
For detailed installation instructions for different GPU generations:
AMD
For detailed installation instructions for different GPU generations:
🎯 Usage
Basic Usage
Advanced Features
- Deepy Assistant - Launch Deepy in Gradio, CLI or standalone Web mode; configure tools, media references, saved sessions and phone access
- Authentication, HTTPS, and Reverse Proxies - Protect web access, configure proxy hosting with
--public-url, and set up MCP OAuth
- Remote LLMs - Configure Codex, Claude Code, and OpenCode providers for Deepy and Prompt Enhancer
- Loras Guide - Using and managing Loras for customization
- Finetunes - Add manually new models to WanGP
- VACE ControlNet - Advanced video control and manipulation
- Processing Guide - Preprocessing, masks, sliding windows, and postprocessing
- Command Line Reference - All available command line options
📚 Documentation
📚 Video Guides
Other Models for the GPU Poor
- HuanyuanVideoGP - One of the best open source Text to Video generators
- Hunyuan3D-2GP - Image to 3D and text to 3D tool
- FluxFillGP - Inpainting/outpainting tools based on Flux
- Cosmos1GP - Text to world generator and image/video to world
- OminiControlGP - Flux-derived application for object transfer
- YuE GP - Song generator with instruments and singer's voice
Made with ❤️ by DeepBeepMeep
WanGP is a one-stop open source app for running top generative AI models for video, image, and audio/TTS generation, built specifically to work on modest consumer GPUs (the 'GPU Poor').