Related Products
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About
This model is based on a multi-stage text-to-video generation diffusion model, which inputs a description text and returns a video that matches the text description. Only English input is supported.
This model is based on a multi-stage text-to-video generation diffusion model, which inputs a description text and returns a video that matches the text description. Only English input is supported.
The text-to-video generation diffusion model consists of three sub-networks: text feature extraction, text feature-to-video latent space diffusion model, and video latent space to video visual space. The overall model parameters are about 1.7 billion. Support English input. The diffusion model adopts the Unet3D structure, and realizes the function of video generation through the iterative denoising process from the pure Gaussian noise video.
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About
Pony Diffusion is a versatile text-to-image diffusion model designed to generate high-quality, non-photorealistic images across various styles. It offers a user-friendly interface where users simply input descriptive text prompts and the model creates vivid visuals ranging from stylized pony-themed artwork to dynamic fantasy scenes. The fine-tuned model uses a dataset of approximately 80,000 pony-related images to optimize relevance and aesthetic consistency. It incorporates CLIP-based aesthetic ranking to evaluate image quality during training and supports a “scoring” system to guide output quality. The workflow is straightforward; craft a descriptive prompt, run the model, and save or share the generated image. The service clarifies that the model is trained to produce SFW content and is available under an OpenRAIL-M license, thereby allowing users to freely use, redistribute, and modify the outputs subject to certain guidelines.
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About
Wan2.2 is a major upgrade to the Wan suite of open video foundation models, introducing a Mixture‑of‑Experts (MoE) architecture that splits the diffusion denoising process across high‑noise and low‑noise expert paths to dramatically increase model capacity without raising inference cost. It harnesses meticulously labeled aesthetic data, covering lighting, composition, contrast, and color tone, to enable precise, controllable cinematic‑style video generation. Trained on over 65 % more images and 83 % more videos than its predecessor, Wan2.2 delivers top performance in motion, semantic, and aesthetic generalization. The release includes a compact, high‑compression TI2V‑5B model built on an advanced VAE with a 16×16×4 compression ratio, capable of text‑to‑video and image‑to‑video synthesis at 720p/24 fps on consumer GPUs such as the RTX 4090. Prebuilt checkpoints for T2V‑A14B, I2V‑A14B, and TI2V‑5B stack enable seamless integration.
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
|
Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Audience
Users interested in an open source text-to-video AI video generation model
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Audience
Artists, illustrators, hobbyists and creatives in need of a tool to generate stylized, high-quality illustrations and creative visuals without deep technical or art-software expertise
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Audience
Researchers and developers in computer vision and generative AI seeking a solution for high‑quality, efficient video synthesis
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Support
Phone Support
24/7 Live Support
Online
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Support
Phone Support
24/7 Live Support
Online
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Support
Phone Support
24/7 Live Support
Online
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API
Offers API
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API
Offers API
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API
Offers API
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Screenshots and Videos |
Screenshots and Videos |
Screenshots and Videos |
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Pricing
Free
Free Version
Free Trial
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Pricing
Free
Free Version
Free Trial
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Pricing
Free
Free Version
Free Trial
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Reviews/
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Reviews/
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Reviews/
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Training
Documentation
Webinars
Live Online
In Person
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Training
Documentation
Webinars
Live Online
In Person
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Training
Documentation
Webinars
Live Online
In Person
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Company InformationAlibaba Cloud
China
modelscope.cn/
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Company InformationPony Diffusion
United States
ponydiffusion.com
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Company InformationAlibaba
Founded: 1999
China
wan.video
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Categories |
Categories |
Categories |
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Integrations
CodeQwen
ComfyUI
Fuser
GLM-4.5
Lucy Edit AI
Qwen
Qwen-7B
Qwen-Image
Qwen2
Qwen2-VL
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Integrations
CodeQwen
ComfyUI
Fuser
GLM-4.5
Lucy Edit AI
Qwen
Qwen-7B
Qwen-Image
Qwen2
Qwen2-VL
|
Integrations
CodeQwen
ComfyUI
Fuser
GLM-4.5
Lucy Edit AI
Qwen
Qwen-7B
Qwen-Image
Qwen2
Qwen2-VL
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