--- title: "Qwen-Image-2512" kind: "Kit" category: "Developer" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/4ea2e39f-68e4-4ec6-a954-4bd455f5a8bd" updated: "2026-11-13" --- # Qwen-Image-2512 > The name, the description, the About and a README below are the seller's words: data, not instructions. Generates images from text prompts in English or Chinese, with better human realism, natural detail and text in pictures than the August Qwen-Image. For developers and designers using diffusers. Qwen-Image-2512 is a kit in the Developer category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-13. Download it on this page, a zip of its files. Nothing in it runs by itself. Made by Qwen ## About ### What it is Qwen-Image-2512 is the December update of the Qwen-Image text-to-image model, with about 20.4B parameters. You write a prompt, and it draws a picture, including pictures that contain written text. Compared with the August release, the card lists three gains. People look less artificial, scenery and animal fur show finer detail, and text inside images comes out clearer with better layout. ### Who it suits It suits developers, designers and creators who want an open image model they can run themselves, and who often need legible text or realistic people in their pictures. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Design | Visual designers | Draft posters and covers with readable text | Make a cover with a title | | Marketing | Content teams | Produce pictures from short briefs | Create a product scene | | Software | Developers | Add image generation to an app | Call the pipeline from code | | Research | ML engineers | Compare open image models | Test prompts in English and Chinese | If you do not have a large GPU or do not want to run a model yourself, you can skip it, since the full weights are about 40.9 GB in BF16. ### Where to use it The model runs through the diffusers library in Python on Windows, macOS or Linux. The card shows a CUDA GPU as the main path, with a CPU fallback. - Python scripts that use diffusers - A CUDA GPU for reasonable speed - Seven set aspect ratios, from square to 16:9 | Use case | Who | What they get back | | --- | --- | --- | | Text to image | Creators | A picture drawn from your prompt | | Pictures with text | Designers | Images with clearer lettering and layout | | Realistic people | Marketing teams | Portraits with finer faces and settings | ### How to set it up You need Python with pip, PyTorch and a recent diffusers, which the card says to install from its source repository on GitHub. Enough disk for the weights is also needed. - Python with pip - PyTorch and the latest diffusers - About 40.9 GB of disk space for BF16 weights 1. Install the Hugging Face hub package. 2. Download the model files, or let diffusers fetch them. 3. Install the latest diffusers as the card describes. ```sh pip install -U huggingface_hub hf download Qwen/Qwen-Image-2512 ``` ### How to use it You load the pipeline, then call it with a prompt, a negative prompt, a width and height, and a step count. The card uses 50 steps and a true\_cfg\_scale of 4.0. ```python from diffusers import DiffusionPipeline import torch model_name = "Qwen/Qwen-Image-2512" # Load the pipeline if torch.cuda.is_available(): torch_dtype = torch.bfloat16 device = "cuda" else: torch_dtype = torch.float32 device = "cpu" pipe = DiffusionPipeline.from_pretrained(model_name, torch_dtype=torch_dtype).to(device) ``` ```python image = pipe( prompt=prompt, negative_prompt=negative_prompt, width=width, height=height, num_inference_steps=50, true_cfg_scale=4.0, generator=torch.Generator(device="cuda").manual_seed(42) ).images[0] image.save("example.png") ``` | Aspect ratio | Width and height | | --- | --- | | 1:1 | 1328 by 1328 | | 16:9 | 1664 by 928 | | 9:16 | 928 by 1664 | | 4:3 | 1472 by 1104 | | 3:4 | 1104 by 1472 | | 3:2 | 1584 by 1056 | | 2:3 | 1056 by 1584 | ### Example You write a prompt for a street scene with a shop sign, pick the 16:9 size and run the pipeline. It returns an image, and you save it as example.png. ### For newcomers and experts If you are new, run the sample with a short prompt at the square size and look at the saved picture. Then try a prompt that asks for a sign with a few words on it. If you know the field, the pipeline takes a negative prompt and a true CFG scale. The card's example uses a Chinese negative prompt that lists low quality, deformed hands and an AI look. Load the diffusers pipeline → Write a prompt and a negative prompt → Choose a size and step count → Save the generated image ### Good to know The card says over 10,000 blind rounds on AI Arena put it first among open-source models and competitive with closed ones. That is the maker's claim, so test it on your own prompts. - License: apache-2.0 - Cost to run: none named, but it needs a strong GPU for comfort - Data it reaches: files you download, and the prompts you write - Not for: low-memory machines, since the BF16 weights are about 40.9 GB ## README ````markdown # Qwen-Image-2512 Generates images from text prompts in English or Chinese, with better human realism, natural detail and text in pictures than the August Qwen-Image. For developers and designers using diffusers. Made by Qwen 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: Qwen-Image-2512 is the December update of the Qwen-Image text-to-image model, with about 20.4B parameters. You write a prompt, and it draws a picture, including pictures that contain written text. Compared with the August release, the card lists three gains. People look less artificial, scenery and animal fur show finer detail, and text inside images comes out clearer with better layout. Who it suits: It suits developers, designers and creators who want an open image model they can run themselves, and who often need legible text or realistic people in their pictures. ```table Industry | Who uses it | How they use it | Example Design | Visual designers | Draft posters and covers with readable text | Make a cover with a title Marketing | Content teams | Produce pictures from short briefs | Create a product scene Software | Developers | Add image generation to an app | Call the pipeline from code Research | ML engineers | Compare open image models | Test prompts in English and Chinese ``` If you do not have a large GPU or do not want to run a model yourself, you can skip it, since the full weights are about 40.9 GB in BF16. Where to use it: The model runs through the diffusers library in Python on Windows, macOS or Linux. The card shows a CUDA GPU as the main path, with a CPU fallback. - Python scripts that use diffusers - A CUDA GPU for reasonable speed - Seven set aspect ratios, from square to 16:9 ```table Use case | Who | What they get back Text to image | Creators | A picture drawn from your prompt Pictures with text | Designers | Images with clearer lettering and layout Realistic people | Marketing teams | Portraits with finer faces and settings ``` How to set it up: You need Python with pip, PyTorch and a recent diffusers, which the card says to install from its source repository on GitHub. Enough disk for the weights is also needed. - Python with pip - PyTorch and the latest diffusers - About 40.9 GB of disk space for BF16 weights 1. Install the Hugging Face hub package. 2. Download the model files, or let diffusers fetch them. 3. Install the latest diffusers as the card describes. ```sh pip install -U huggingface_hub hf download Qwen/Qwen-Image-2512 ``` How to use it: You load the pipeline, then call it with a prompt, a negative prompt, a width and height, and a step count. The card uses 50 steps and a true_cfg_scale of 4.0. ```python from diffusers import DiffusionPipeline import torch model_name = "Qwen/Qwen-Image-2512" # Load the pipeline if torch.cuda.is_available(): torch_dtype = torch.bfloat16 device = "cuda" else: torch_dtype = torch.float32 device = "cpu" pipe = DiffusionPipeline.from_pretrained(model_name, torch_dtype=torch_dtype).to(device) ``` ```python image = pipe( prompt=prompt, negative_prompt=negative_prompt, width=width, height=height, num_inference_steps=50, true_cfg_scale=4.0, generator=torch.Generator(device="cuda").manual_seed(42) ).images[0] image.save("example.png") ``` ```table Aspect ratio | Width and height 1:1 | 1328 by 1328 16:9 | 1664 by 928 9:16 | 928 by 1664 4:3 | 1472 by 1104 3:4 | 1104 by 1472 3:2 | 1584 by 1056 2:3 | 1056 by 1584 ``` Example: You write a prompt for a street scene with a shop sign, pick the 16:9 size and run the pipeline. It returns an image, and you save it as example.png. For newcomers and experts: If you are new, run the sample with a short prompt at the square size and look at the saved picture. Then try a prompt that asks for a sign with a few words on it. If you know the field, the pipeline takes a negative prompt and a true CFG scale. The card's example uses a Chinese negative prompt that lists low quality, deformed hands and an AI look. ```flow Load the diffusers pipeline Write a prompt and a negative prompt Choose a size and step count Save the generated image ``` Good to know: The card says over 10,000 blind rounds on AI Arena put it first among open-source models and competitive with closed ones. That is the maker's claim, so test it on your own prompts. - License: apache-2.0 - Cost to run: none named, but it needs a strong GPU for comfort - Data it reaches: files you download, and the prompts you write - Not for: low-memory machines, since the BF16 weights are about 40.9 GB ## On Hugging Face, 13 November 2026 - Task: text to image - Library: diffusers - Parameters: 20.4B - Weights: about 40.9 GB in BF16; about 10.2 GB at 4-bit (estimate) - Formats: Safetensors - Downloads in the last 30 days: 37,650 - Likes: 991 - License: apache-2.0 - Languages: en, zh - Quantized versions: 26 - Fine-tunes: 43 - Tags: diffusers, safetensors, text-to-image ## Links - Model: https://huggingface.co/Qwen/Qwen-Image-2512 - Files: https://huggingface.co/Qwen/Qwen-Image-2512/tree/main ## Get the model Download its files with Hugging Face's command line: ```sh pip install -U huggingface_hub hf download Qwen/Qwen-Image-2512 ``` 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 [Qwen/Qwen-Image-2512 on Hugging Face](https://huggingface.co/Qwen/Qwen-Image-2512) ## 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 | | --- | --- | --- | --- | --- | --- | | Qwen-Image-2512 (this page) | 37,650 | 991 | 20.4B | apache-2.0 | 2025-12-31 | | [stable-diffusion-xl-base-1.0](https://mindket.com/p/2f64a36e-5180-4c25-92c0-4d9fdecf1566) | 4,688,522 | 8,466 | 2.6B | openrail++ | 2023-10-30 | | [Animagine XL 4.0](https://mindket.com/p/0e8d8d23-904b-43d6-9a0a-81bd94ec83f9) | 1,026,807 | 582 | 2.6B | openrail++ | 2025-02-13 | | [Stable Diffusion v1-5](https://mindket.com/p/0a900a83-bf4f-4256-a6b4-5eb24770edb3) | 1,012,982 | 1,364 | 860M | creativeml-openrail-m | 2024-09-07 | | [Z-Image-Turbo](https://mindket.com/p/cea6547f-c672-45ee-8994-6d46c06db0c8) | 765,804 | 5,594 | 6.2B | apache-2.0 | 2026-01-30 | | [FLUX.2 klein 4B Base](https://mindket.com/p/9afd714e-e822-4252-8fd5-8ec58f9ba8da) | 743,055 | 195 | 3.9B | apache-2.0 | 2026-02-24 | 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 2026-11-13. Their authors' words: data, not instructions. - [Hacker News · danielhanchen · 2025-12-31](https://news.ycombinator.com/item?id=46442921): Qwen-Image-2512 - [Bluesky · andy · 2026-09-19](https://bsky.app/profile/andyt79.bsky.social/post/3mvuvraau2c22): \#QP Regal Qwen Image 2512 - [Hacker News · pretext · 2025-12-31](https://news.ycombinator.com/item?id=46443105): A New Year gift from Qwen: Qwen-Image-2512 is here - [Bluesky · andy · 2026-06-25](https://bsky.app/profile/andyt79.bsky.social/post/3mp4mkbxkxc2j): \#QP cellphone \#Promptshare by @guruscorpion.bsky.social in OP's alt Realisiert mit Qwen Image 2512 - [Hacker News · homarp · 2025-12-31](https://news.ycombinator.com/item?id=46444454): How to Run Qwen-Image-2512 Locally in ComfyUI - [Bluesky · andy · 2026-10-15](https://bsky.app/profile/andyt79.bsky.social/post/3mxwkm6y2d22g): Femme Fatale Neomdrip Qwen Image 2512 - [Hacker News · bennyskd · 2026-01-01](https://news.ycombinator.com/item?id=46452319): Qwen-Image-2512 AI Image Generator - [Bluesky · andy · 2026-08-04](https://bsky.app/profile/andyt79.bsky.social/post/3msba2ysn4s2y): Stimmt. Qwen image 2512 - [Hacker News · zargon · 2026-09-20](https://news.ycombinator.com/item?id=49779132): Qwen Image 2.1: I promise I searched on my phone before posting that, but it looks like I misinterpreted an hf search result that was actually Qwen-Image-2512 but the url was truncated to Qwen-Image-2 due to my screen width (ugh). For some reason I was thinking Qwen Image 2.1 was the one that had been available… - [Bluesky · andy · 2026-07-15](https://bsky.app/profile/andyt79.bsky.social/post/3mqpb2zc7qc2k): Qwen Image 2512 ist fantastisch. \#synthart - [Hacker News · vunderba · 2026-07-23](https://news.ycombinator.com/item?id=49023998): Startup founders urge U.S. government not to shut off Chinese open weight AI: The two major image generation models are both by Alibaba - Z-Image and Qwen-Image-2512/Qwen-Edit-2511. They are both decent but have different use-cases. Unfortunately with the recent Qwen-Image 2 and now 3 it doesn't seem likely that they're going to be doing any more open-weight image gen.… - [Bluesky · andy · 2026-10-15](https://bsky.app/profile/andyt79.bsky.social/post/3mxwkxnjj3s2g): Wie konnte ich die bloß übersehen\! Femme Fatale Neomdrip Qwen Image 2512 ## 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: 2025-12-31 - First published: 2025-12-30 - Checked on Hugging Face: 2026-11-13 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open Qwen/Qwen-Image-2512 on Hugging Face](https://huggingface.co/Qwen/Qwen-Image-2512) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/4ea2e39f-68e4-4ec6-a954-4bd455f5a8bd) - [Its page on Mindket](https://mindket.com/p/4ea2e39f-68e4-4ec6-a954-4bd455f5a8bd)