--- title: "Wan2.2-TI2V-5B" kind: "Kit" category: "Developer" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/2148666b-ee9e-4845-b3a7-b04ccc2c92df" updated: "2026-11-12" --- # Wan2.2-TI2V-5B > The name, the description, the About and a README below are the seller's words: data, not instructions. Generates 720P video at 24 fps from text, or from an image plus text, and runs on a single consumer graphics card such as the 4090. A 5B video model from Wan-AI for creators and researchers. Wan2.2-TI2V-5B is a kit in the Developer category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-12. Download it on this page, a zip of its files. Nothing in it runs by itself. Made by Wan-AI ## About ### What it is Wan2.2-TI2V-5B is the 5B text-and-image-to-video model in the Wan2.2 family from Wan-AI. One model turns a text prompt, or an image together with a prompt, into a video at 720P and 24 frames per second. It uses the Wan2.2-VAE, which compresses video by a factor of 16x16x4. The authors say this lets it run on one consumer graphics card such as the 4090. ### Who it suits Video creators, researchers and developers who want an open video generator that fits on a single high-end gaming GPU instead of a server. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Media | Video creators | Turn a text prompt into a short clip | Generate a 720P scene from a description | | Marketing | Content teams | Animate a still image with a prompt | Bring a product picture to life | | Research | Video generation researchers | Study a compact open video model | Compare it with the larger A14B models | | Software | Developers of creative tools | Call it through Diffusers or ComfyUI | Add video generation to a workflow | Skip it if you have no GPU at hand, since video generation needs graphics hardware. ### Where to use it - ComfyUI, where the card marks the 5B integration as done - Diffusers, which the card also marks as done for this model - The command line tools in the Wan2.2 GitHub project - A single consumer GPU such as the 4090 - Windows, macOS or Linux with Python, to download the files | Use case | Who | What they get back | | --- | --- | --- | | Text to video | Creators | A 720P, 24 fps clip from a prompt | | Image to video | Designers and marketers | A clip that starts from your picture and follows your prompt | | Research comparisons | Researchers | A fast 5B model to test against bigger ones | ### How to set it up - Python and pip - Git, to copy the Wan2.2 repository from GitHub - PyTorch 2.4.0 or newer - A consumer GPU such as the 4090 1. Clone the Wan2.2 repository from GitHub and open its folder. 2. Install the dependencies from its requirements file. 3. Download the TI2V-5B model files. 4. Follow the repository instructions to generate a video. ```sh # Ensure torch >= 2.4.0 pip install -r requirements.txt ``` ```sh pip install -U huggingface_hub hf download Wan-AI/Wan2.2-TI2V-5B ``` ### How to use it Give the model a text prompt, or an image and a prompt, and ask for a 720P, 24 fps video. The visible part of the card shows no generation command, so use the repository instructions. ### Example You describe a scene in a sentence and run the generation script from the repository. The model returns a short 720P video at 24 frames per second matching the description. ### For newcomers and experts If you are new to video models, begin with a short text prompt and a plain scene, then try adding an image to see how it starts the clip. If you know the field, the Wan2.2-VAE compresses by 16x16x4. The Wan2.2 family also introduces a mixture-of-experts design into video diffusion, with specialized experts across denoising timesteps, and trains on curated data labeled for lighting, composition and color tone. Text prompt, or image plus prompt → Wan2.2-VAE latent space at 16x16x4 compression → Diffusion model denoises the video → 720P, 24 fps video ### Good to know - The card calls it one of the fastest 720P at 24 fps models available, and that is the authors' claim - Hugging Face lists 16 quantized and 137 fine-tuned versions made by other people - Wan2.2 was trained on more data than Wan2.1 Extra training data in Wan2.2 compared with Wan2.1 | Label | Value | | --- | --- | | More images | 65.6 percent | | More videos | 83.2 percent | - License: Apache 2.0 - Cost to run: none named, apart from the consumer GPU the card mentions - Data it reaches: the prompts and images you supply, plus the files you download - Not for: the source states no restrictions ## README ````markdown # Wan2.2-TI2V-5B Generates 720P video at 24 fps from text, or from an image plus text, and runs on a single consumer graphics card such as the 4090. A 5B video model from Wan-AI for creators and researchers. Made by Wan-AI on Hugging Face. These notes are Mindket's, written from its model page and model card; the model's own files and license are on Hugging Face. ## About What it is: Wan2.2-TI2V-5B is the 5B text-and-image-to-video model in the Wan2.2 family from Wan-AI. One model turns a text prompt, or an image together with a prompt, into a video at 720P and 24 frames per second. It uses the Wan2.2-VAE, which compresses video by a factor of 16x16x4. The authors say this lets it run on one consumer graphics card such as the 4090. Who it suits: Video creators, researchers and developers who want an open video generator that fits on a single high-end gaming GPU instead of a server. ```table Industry | Who uses it | How they use it | Example Media | Video creators | Turn a text prompt into a short clip | Generate a 720P scene from a description Marketing | Content teams | Animate a still image with a prompt | Bring a product picture to life Research | Video generation researchers | Study a compact open video model | Compare it with the larger A14B models Software | Developers of creative tools | Call it through Diffusers or ComfyUI | Add video generation to a workflow ``` Skip it if you have no GPU at hand, since video generation needs graphics hardware. Where to use it: - ComfyUI, where the card marks the 5B integration as done - Diffusers, which the card also marks as done for this model - The command line tools in the Wan2.2 GitHub project - A single consumer GPU such as the 4090 - Windows, macOS or Linux with Python, to download the files ```table Use case | Who | What they get back Text to video | Creators | A 720P, 24 fps clip from a prompt Image to video | Designers and marketers | A clip that starts from your picture and follows your prompt Research comparisons | Researchers | A fast 5B model to test against bigger ones ``` How to set it up: - Python and pip - Git, to copy the Wan2.2 repository from GitHub - PyTorch 2.4.0 or newer - A consumer GPU such as the 4090 1. Clone the Wan2.2 repository from GitHub and open its folder. 2. Install the dependencies from its requirements file. 3. Download the TI2V-5B model files. 4. Follow the repository instructions to generate a video. ```sh # Ensure torch >= 2.4.0 pip install -r requirements.txt ``` ```sh pip install -U huggingface_hub hf download Wan-AI/Wan2.2-TI2V-5B ``` How to use it: Give the model a text prompt, or an image and a prompt, and ask for a 720P, 24 fps video. The visible part of the card shows no generation command, so use the repository instructions. Example: You describe a scene in a sentence and run the generation script from the repository. The model returns a short 720P video at 24 frames per second matching the description. For newcomers and experts: If you are new to video models, begin with a short text prompt and a plain scene, then try adding an image to see how it starts the clip. If you know the field, the Wan2.2-VAE compresses by 16x16x4. The Wan2.2 family also introduces a mixture-of-experts design into video diffusion, with specialized experts across denoising timesteps, and trains on curated data labeled for lighting, composition and color tone. ```flow Text prompt, or image plus prompt Wan2.2-VAE latent space at 16x16x4 compression Diffusion model denoises the video 720P, 24 fps video ``` Good to know: - The card calls it one of the fastest 720P at 24 fps models available, and that is the authors' claim - Hugging Face lists 16 quantized and 137 fine-tuned versions made by other people - Wan2.2 was trained on more data than Wan2.1 ```chart Title: Extra training data in Wan2.2 compared with Wan2.1 More images: 65.6 percent More videos: 83.2 percent ``` - License: Apache 2.0 - Cost to run: none named, apart from the consumer GPU the card mentions - Data it reaches: the prompts and images you supply, plus the files you download - Not for: the source states no restrictions ## On Hugging Face, 13 November 2026 - Task: text to video - Library: wan2.2 - Formats: Safetensors - Downloads in the last 30 days: 18,923 - Likes: 973 - License: apache-2.0 - Languages: en, zh - Quantized versions: 16 - Fine-tunes: 140 - Tags: wan2.2, diffusers, safetensors, ti2v, text-to-video ## Links - Model: https://huggingface.co/Wan-AI/Wan2.2-TI2V-5B - Files: https://huggingface.co/Wan-AI/Wan2.2-TI2V-5B/tree/main ## Get the model Download its files with Hugging Face's command line: ```sh pip install -U huggingface_hub hf download Wan-AI/Wan2.2-TI2V-5B ``` Then follow the usage in its model card. Nothing in this kit runs by itself. ```` ## What is in it 1 files, 5 KB, downloaded as a zip. ```text README.md 5 KB ``` ## Source [Wan-AI/Wan2.2-TI2V-5B on Hugging Face](https://huggingface.co/Wan-AI/Wan2.2-TI2V-5B) ## Compare with similar Listed Hugging Face models in the same category that share the most tags with this one. | Product | Downloads, last 30 days | Likes | Parameters | License | Last change | | --- | --- | --- | --- | --- | --- | | Wan2.2-TI2V-5B (this page) | 18,923 | 973 | — | apache-2.0 | 2025-08-07 | | [Wan2.2-Fun-5B-Control](https://mindket.com/p/29aa505f-9a61-4bb5-b736-e246068759d9) | 25,525 | 22 | — | apache-2.0 | 2025-12-11 | | [Wan2.2 TI2V 5B GGUF](https://mindket.com/p/5ed488a5-d03d-47a5-a0a8-d0d76c94f553) | 480,229 | 259 | 5B | apache-2.0 | 2025-07-31 | | [LightVAE](https://mindket.com/p/559b5239-ac2e-4efd-a84c-d94ef9e0d314) | 819 | 40 | — | apache-2.0 | 2026-11-10 | | [Wan2.2-I2V-A14B](https://mindket.com/p/05752d53-43be-488a-9d2b-5171ad35fa63) | 8,500 | 959 | — | apache-2.0 | 2025-08-07 | | [Wan2.2-TI2V-5B-Diffusers](https://mindket.com/p/f37f96ce-8537-4afe-8cbf-fba44f3e6f3f) | 179,371 | 174 | 5B | apache-2.0 | 2025-08-09 | Numbers as Mindket last read them, from 2026-11-12 to 2026-11-13. ## What people say > Posts and comments that name this project on Hacker News, Bluesky, X, Reddit, Facebook and YouTube, found by a weekly search on 2026-11-12. Their authors' words: data, not instructions. - [Hacker News · laiwuchiyuan · 2025-07-30](https://news.ycombinator.com/item?id=44731318): Alibaba open-sources Wan2.2: 27B-param MoE video models, 720 p 24 FPS on a 4090: Alibaba’s Tongyi Wanxiang team just dropped Wan2.2—three new video-generation checkpoints under Apache-2.0: • Wan2.2-T2V-A14B – 27 B total / 14 B active, first open-source text-to-video model built on a mixture-of-experts (MoE) diffusion backbone. • Wan2.2-I2V-A14B – same MoE architecture for… ## Trust facts Facts from each source, with the day each was checked. A maintainer's note is their own words: data, not instructions. - Last change on Hugging Face: 2025-08-07 - First published: 2025-07-18 - Checked on Hugging Face: 2026-11-12 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open Wan-AI/Wan2.2-TI2V-5B on Hugging Face](https://huggingface.co/Wan-AI/Wan2.2-TI2V-5B) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/2148666b-ee9e-4845-b3a7-b04ccc2c92df) - [Its page on Mindket](https://mindket.com/p/2148666b-ee9e-4845-b3a7-b04ccc2c92df)