--- title: "Wan2.2-I2V-A14B-GGUF" kind: "Kit" category: "Developer" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/2a0451c5-2264-449e-a96c-7aa56995c3ce" updated: "2026-11-12" --- # Wan2.2-I2V-A14B-GGUF > The name, the description, the About and a README below are the seller's words: data, not instructions. Provides GGUF files of Wan2.2-I2V-A14B, a 14B model that turns a still image into a video, for use in ComfyUI with the ComfyUI-GGUF node. For people making short videos on a home GPU. Wan2.2-I2V-A14B-GGUF 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 QuantStack ## About ### What it is This repository holds GGUF files converted straight from Wan-AI/Wan2.2-I2V-A14B, an image-to-video model with about 14.3B parameters. You give it a picture and a text prompt, and it makes a short video that starts from that image. Quantized GGUF files are smaller than the original weights, so the model can run on less memory. At 4-bit, the weights are estimated at about 7.1 GB. ### Who it suits It suits creators and developers who already use ComfyUI and want to animate still images with an open video model on their own hardware. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Video | Creators | Animate a still picture into a short clip | Bring an illustration to life | | Marketing | Designers | Make short motion from product images | Animate a product photo | | Games | Artists | Draft motion for concept art | Test a character movement | | Research | ML engineers | Try quantized video models | Compare quant sizes | If you do not use ComfyUI or have a GPU, you can skip it, since the card gives only the ComfyUI route. ### Where to use it The card names the ComfyUI custom node ComfyUI-GGUF, by city96, as the way to load these files. ComfyUI runs on Windows, macOS and Linux. - ComfyUI with the ComfyUI-GGUF custom node - The unet folder inside ComfyUI's models folder - English and Chinese prompts, as the card lists both | Use case | Who | What they get back | | --- | --- | --- | | Image to video | Creators | A short video from one starting image | | Prompted motion | Designers | Movement guided by a text description | | Quant testing | Engineers | A smaller model to run on limited memory | ### How to set it up You need ComfyUI, the ComfyUI-GGUF custom node and Python with pip to fetch the files. The node's own readme covers its installation. - ComfyUI installed - The ComfyUI-GGUF custom node - Python with pip, and disk space for the GGUF file you pick 1. Install the Hugging Face hub package. 2. Download the model files. 3. Place the model files in the unet folder under ComfyUI's models folder. 4. Install the ComfyUI-GGUF node by following its readme. ```sh pip install -U huggingface_hub hf download QuantStack/Wan2.2-I2V-A14B-GGUF ``` ### How to use it In ComfyUI you load the GGUF file through the ComfyUI-GGUF node, add your starting image and a text prompt, and run the workflow. The video comes out of that graph. The card gives no run command beyond placing the files. ### Example You load a still photo of a street, write a short prompt that asks for people walking and a gentle camera move, and run the graph. You get back a short video that starts from your photo. ### For newcomers and experts If you are new, first get one picture and a one-line prompt working in ComfyUI. Then change the prompt and see how the motion changes. If you know the field, the files are a direct GGUF conversion of the original Wan2.2 image-to-video weights. The GGUF node loads them in place of the standard diffusion model loader. Place the GGUF file in the unet folder → Load it with the ComfyUI-GGUF node → Add an image and a prompt → Run the graph to get a video ### Good to know Because this is a quantized copy, all the original licensing terms and usage restrictions of the source model remain in force. Read those terms before you publish anything you make. - License: apache-2.0, with the original model's terms still applying - Cost to run: none named, but it needs a capable GPU - Data it reaches: files you download, and the images and prompts you use - Not for: use outside the source model's license terms ## README ````markdown # Wan2.2-I2V-A14B-GGUF Provides GGUF files of Wan2.2-I2V-A14B, a 14B model that turns a still image into a video, for use in ComfyUI with the ComfyUI-GGUF node. For people making short videos on a home GPU. Made by QuantStack 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: This repository holds GGUF files converted straight from Wan-AI/Wan2.2-I2V-A14B, an image-to-video model with about 14.3B parameters. You give it a picture and a text prompt, and it makes a short video that starts from that image. Quantized GGUF files are smaller than the original weights, so the model can run on less memory. At 4-bit, the weights are estimated at about 7.1 GB. Who it suits: It suits creators and developers who already use ComfyUI and want to animate still images with an open video model on their own hardware. ```table Industry | Who uses it | How they use it | Example Video | Creators | Animate a still picture into a short clip | Bring an illustration to life Marketing | Designers | Make short motion from product images | Animate a product photo Games | Artists | Draft motion for concept art | Test a character movement Research | ML engineers | Try quantized video models | Compare quant sizes ``` If you do not use ComfyUI or have a GPU, you can skip it, since the card gives only the ComfyUI route. Where to use it: The card names the ComfyUI custom node ComfyUI-GGUF, by city96, as the way to load these files. ComfyUI runs on Windows, macOS and Linux. - ComfyUI with the ComfyUI-GGUF custom node - The unet folder inside ComfyUI's models folder - English and Chinese prompts, as the card lists both ```table Use case | Who | What they get back Image to video | Creators | A short video from one starting image Prompted motion | Designers | Movement guided by a text description Quant testing | Engineers | A smaller model to run on limited memory ``` How to set it up: You need ComfyUI, the ComfyUI-GGUF custom node and Python with pip to fetch the files. The node's own readme covers its installation. - ComfyUI installed - The ComfyUI-GGUF custom node - Python with pip, and disk space for the GGUF file you pick 1. Install the Hugging Face hub package. 2. Download the model files. 3. Place the model files in the unet folder under ComfyUI's models folder. 4. Install the ComfyUI-GGUF node by following its readme. ```sh pip install -U huggingface_hub hf download QuantStack/Wan2.2-I2V-A14B-GGUF ``` How to use it: In ComfyUI you load the GGUF file through the ComfyUI-GGUF node, add your starting image and a text prompt, and run the workflow. The video comes out of that graph. The card gives no run command beyond placing the files. Example: You load a still photo of a street, write a short prompt that asks for people walking and a gentle camera move, and run the graph. You get back a short video that starts from your photo. For newcomers and experts: If you are new, first get one picture and a one-line prompt working in ComfyUI. Then change the prompt and see how the motion changes. If you know the field, the files are a direct GGUF conversion of the original Wan2.2 image-to-video weights. The GGUF node loads them in place of the standard diffusion model loader. ```flow Place the GGUF file in the unet folder Load it with the ComfyUI-GGUF node Add an image and a prompt Run the graph to get a video ``` Good to know: Because this is a quantized copy, all the original licensing terms and usage restrictions of the source model remain in force. Read those terms before you publish anything you make. - License: apache-2.0, with the original model's terms still applying - Cost to run: none named, but it needs a capable GPU - Data it reaches: files you download, and the images and prompts you use - Not for: use outside the source model's license terms ## On Hugging Face, 13 November 2026 - Task: image to video - Library: gguf - Parameters: 14.3B - Weights: about 7.1 GB at 4-bit (estimate) - Formats: GGUF - Downloads in the last 30 days: 1,140,540 - Likes: 464 - License: apache-2.0 - Languages: en, zh - Based on: Wan-AI/Wan2.2-I2V-A14B - Tags: gguf, image-to-video ## Links - Model: https://huggingface.co/QuantStack/Wan2.2-I2V-A14B-GGUF - Files: https://huggingface.co/QuantStack/Wan2.2-I2V-A14B-GGUF/tree/main ## Get the model Download its files with Hugging Face's command line: ```sh pip install -U huggingface_hub hf download QuantStack/Wan2.2-I2V-A14B-GGUF ``` 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 [QuantStack/Wan2.2-I2V-A14B-GGUF on Hugging Face](https://huggingface.co/QuantStack/Wan2.2-I2V-A14B-GGUF) ## 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-I2V-A14B-GGUF (this page) | 1,140,540 | 464 | 14.3B | apache-2.0 | 2025-07-29 | | [Wan2.2-S2V-14B](https://mindket.com/p/842b3a2c-9b93-4ff9-a757-9a806916671d) | 50,406 | 502 | 16.3B | apache-2.0 | 2025-09-17 | | [Wan2.1-VACE-1.3B](https://mindket.com/p/78ffeb84-ef89-4c0a-82af-95cda4b50dd8) | 42,137 | 162 | 2.2B | apache-2.0 | 2025-05-19 | | [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-I2V-A14B](https://mindket.com/p/05752d53-43be-488a-9d2b-5171ad35fa63) | 8,500 | 959 | — | apache-2.0 | 2025-08-07 | | [LongCat-Video](https://mindket.com/p/48609422-da93-43cf-9ad3-e5e7f4cada5e) | 3,135 | 594 | — | mit | 2025-10-29 | Numbers as Mindket last read them, from 2026-11-12 to 2026-11-13. ## 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: 2025-07-29 - First published: 2025-07-28 - Checked on Hugging Face: 2026-11-12 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open QuantStack/Wan2.2-I2V-A14B-GGUF on Hugging Face](https://huggingface.co/QuantStack/Wan2.2-I2V-A14B-GGUF) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/2a0451c5-2264-449e-a96c-7aa56995c3ce) - [Its page on Mindket](https://mindket.com/p/2a0451c5-2264-449e-a96c-7aa56995c3ce)