--- title: "Pixel Art XL" kind: "Kit" category: "Marketing & SEO" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/dde39180-bd7b-4842-ae4d-26c1350099ea" updated: "2026-11-14" --- # Pixel Art XL > The name, the description, the About and a README below are the seller's words: data, not instructions. A pixel art style add-on for Stable Diffusion XL that turns text prompts into pixel-style images, with an optional LCM LoRA for faster runs. For game makers, designers and hobbyists. Pixel Art XL is a kit in the Marketing \& SEO category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-14. Download it on this page, a zip of its files. Nothing in it runs by itself. Made by nerijs ## About ### What it is Pixel Art XL is a LoRA for the Stable Diffusion XL base model that makes text-to-image results look like pixel art. It needs no style prompt and no trigger keyword, and the card says it works with both the 0.9 and 1.0 versions of the base model. You can pair it with an LCM LoRA to generate faster. The card lists v1 as its first release. ### Who it suits It suits people who want pixel art from a text prompt without drawing it by hand. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Games | Indie game makers | Draw sprites and scenes in a pixel style | Prompt for a character and downscale the result | | Design | Graphic designers | Try retro looks for posters, icons and social posts | A set of nine pixel images from one prompt | | Hobby | Digital artists | Explore pixel art ideas quickly | Prompt a small animal and compare variations | | Software | Developers | Add pixel image generation to a tool | Call the pipeline from a Python script | If you want realistic or 3D renders, you can skip it, since it is built for pixel art. ### Where to use it You run it in Python with the diffusers library on top of Stable Diffusion XL. The card's example moves the pipeline to a CUDA graphics card. - Python scripts that use diffusers - A machine with an NVIDIA GPU and CUDA - Windows, macOS or Linux with the huggingface\_hub package | Use case | Who | What they get back | | --- | --- | --- | | Pixel art images | Artists and game makers | Pixel-style pictures from a text prompt | | Fast batches | Developers | Several images quickly with the LCM LoRA pairing | | Isometric scenes | Designers | The card says it works with isometric and non-isometric styles | ### How to set it up You need Python, the diffusers and torch libraries, the Stable Diffusion XL base model, and the Pixel Art XL weights file saved in your working folder. The card's example runs on a CUDA graphics card. - Python on Windows, macOS or Linux - The diffusers and torch libraries - An NVIDIA GPU with CUDA for the card's example 1. Install the Hugging Face hub package. 2. Download the Pixel Art XL files. 3. Put the weights file where the script expects it, then run the script. ```sh pip install -U huggingface_hub hf download nerijs/pixel-art-xl ``` ### How to use it Write a prompt that starts with the word pixel, add a negative prompt, and generate. The card suggests 8 steps, a guidance scale of 1.5 and a strength of 1.2 for this LoRA when you pair it with an LCM LoRA. Downscale the result 8 times with nearest neighbors for pixel-perfect images. ```python from diffusers import DiffusionPipeline, LCMScheduler import torch model_id = "stabilityai/stable-diffusion-xl-base-1.0" lcm_lora_id = "latent-consistency/lcm-lora-sdxl" pipe = DiffusionPipeline.from_pretrained(model_id, variant="fp16") pipe.scheduler = LCMScheduler.from_config(pipe.scheduler.config) pipe.load_lora_weights(lcm_lora_id, adapter_name="lora") pipe.load_lora_weights("./pixel-art-xl.safetensors", adapter_name="pixel") pipe.set_adapters(["lora", "pixel"], adapter_weights=[1.0, 1.2]) pipe.to(device="cuda", dtype=torch.float16) prompt = "pixel, a cute corgi" negative_prompt = "3d render, realistic" num_images = 9 for i in range(num_images): img = pipe( prompt=prompt, negative_prompt=negative_prompt, num_inference_steps=8, guidance_scale=1.5, ).images[0] img.save(f"lcm_lora_{i}.png") ``` | Tool | What it does | | --- | --- | | LCMScheduler | Lets the pipeline run in few steps with the LCM LoRA | | load\_lora\_weights | Loads the LCM LoRA and the Pixel Art XL weights | | set\_adapters | Sets the strength of each adapter, 1.0 and 1.2 in the card | | nearest neighbors downscale | Shrinks the output 8 times for pixel-perfect images | ### Example You prompt "pixel, a cute corgi" with a negative prompt of "3d render, realistic". The script saves nine images, each made in 8 steps, as numbered image files in the working folder. ### For newcomers and experts If you are new to this, a LoRA is a small add-on that changes the look of a bigger image model. A first small step is to run the card's script and open the saved images. Use a fixed VAE if you see artifacts. If you know the field, this LoRA sits on SDXL base, and the card advises against the refiner. It also says the model works well with only one text encoder. The LCM pairing trades some control for speed, at 8 steps and a guidance scale of 1.5. Text prompt with the word pixel → SDXL base model plus two LoRAs → Eight steps with the LCM scheduler → Downscale 8 times, nearest neighbors → A pixel-perfect image ### Good to know The card suggests a fixed VAE, either the 0.9 version or the fp16 fix, to avoid artifacts. The weights file in the script is loaded from the current folder. - License: creativeml-openrail-m - Cost to run: no API key or paid service is named, but the example needs a CUDA graphics card - Data it reaches: the download comes from Hugging Face, and the model works on the prompts you give it on your own machine - Not for: use with the SDXL refiner, which the card says not to use ## README ````markdown # Pixel Art XL A pixel art style add-on for Stable Diffusion XL that turns text prompts into pixel-style images, with an optional LCM LoRA for faster runs. For game makers, designers and hobbyists. Made by nerijs 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: Pixel Art XL is a LoRA for the Stable Diffusion XL base model that makes text-to-image results look like pixel art. It needs no style prompt and no trigger keyword, and the card says it works with both the 0.9 and 1.0 versions of the base model. You can pair it with an LCM LoRA to generate faster. The card lists v1 as its first release. Who it suits: It suits people who want pixel art from a text prompt without drawing it by hand. ```table Industry | Who uses it | How they use it | Example Games | Indie game makers | Draw sprites and scenes in a pixel style | Prompt for a character and downscale the result Design | Graphic designers | Try retro looks for posters, icons and social posts | A set of nine pixel images from one prompt Hobby | Digital artists | Explore pixel art ideas quickly | Prompt a small animal and compare variations Software | Developers | Add pixel image generation to a tool | Call the pipeline from a Python script ``` If you want realistic or 3D renders, you can skip it, since it is built for pixel art. Where to use it: You run it in Python with the diffusers library on top of Stable Diffusion XL. The card's example moves the pipeline to a CUDA graphics card. - Python scripts that use diffusers - A machine with an NVIDIA GPU and CUDA - Windows, macOS or Linux with the huggingface_hub package ```table Use case | Who | What they get back Pixel art images | Artists and game makers | Pixel-style pictures from a text prompt Fast batches | Developers | Several images quickly with the LCM LoRA pairing Isometric scenes | Designers | The card says it works with isometric and non-isometric styles ``` How to set it up: You need Python, the diffusers and torch libraries, the Stable Diffusion XL base model, and the Pixel Art XL weights file saved in your working folder. The card's example runs on a CUDA graphics card. - Python on Windows, macOS or Linux - The diffusers and torch libraries - An NVIDIA GPU with CUDA for the card's example 1. Install the Hugging Face hub package. 2. Download the Pixel Art XL files. 3. Put the weights file where the script expects it, then run the script. ```sh pip install -U huggingface_hub hf download nerijs/pixel-art-xl ``` How to use it: Write a prompt that starts with the word pixel, add a negative prompt, and generate. The card suggests 8 steps, a guidance scale of 1.5 and a strength of 1.2 for this LoRA when you pair it with an LCM LoRA. Downscale the result 8 times with nearest neighbors for pixel-perfect images. ```python from diffusers import DiffusionPipeline, LCMScheduler import torch model_id = "stabilityai/stable-diffusion-xl-base-1.0" lcm_lora_id = "latent-consistency/lcm-lora-sdxl" pipe = DiffusionPipeline.from_pretrained(model_id, variant="fp16") pipe.scheduler = LCMScheduler.from_config(pipe.scheduler.config) pipe.load_lora_weights(lcm_lora_id, adapter_name="lora") pipe.load_lora_weights("./pixel-art-xl.safetensors", adapter_name="pixel") pipe.set_adapters(["lora", "pixel"], adapter_weights=[1.0, 1.2]) pipe.to(device="cuda", dtype=torch.float16) prompt = "pixel, a cute corgi" negative_prompt = "3d render, realistic" num_images = 9 for i in range(num_images): img = pipe( prompt=prompt, negative_prompt=negative_prompt, num_inference_steps=8, guidance_scale=1.5, ).images[0] img.save(f"lcm_lora_{i}.png") ``` ```table Tool | What it does LCMScheduler | Lets the pipeline run in few steps with the LCM LoRA load_lora_weights | Loads the LCM LoRA and the Pixel Art XL weights set_adapters | Sets the strength of each adapter, 1.0 and 1.2 in the card nearest neighbors downscale | Shrinks the output 8 times for pixel-perfect images ``` Example: You prompt "pixel, a cute corgi" with a negative prompt of "3d render, realistic". The script saves nine images, each made in 8 steps, as numbered image files in the working folder. For newcomers and experts: If you are new to this, a LoRA is a small add-on that changes the look of a bigger image model. A first small step is to run the card's script and open the saved images. Use a fixed VAE if you see artifacts. If you know the field, this LoRA sits on SDXL base, and the card advises against the refiner. It also says the model works well with only one text encoder. The LCM pairing trades some control for speed, at 8 steps and a guidance scale of 1.5. ```flow Text prompt with the word pixel SDXL base model plus two LoRAs Eight steps with the LCM scheduler Downscale 8 times, nearest neighbors A pixel-perfect image ``` Good to know: The card suggests a fixed VAE, either the 0.9 version or the fp16 fix, to avoid artifacts. The weights file in the script is loaded from the current folder. - License: creativeml-openrail-m - Cost to run: no API key or paid service is named, but the example needs a CUDA graphics card - Data it reaches: the download comes from Hugging Face, and the model works on the prompts you give it on your own machine - Not for: use with the SDXL refiner, which the card says not to use ## On Hugging Face, 14 November 2026 - Task: text to image - Library: diffusers - Downloads in the last 30 days: 38,781 - Likes: 669 - License: creativeml-openrail-m - Based on: stabilityai/stable-diffusion-xl-base-1.0 - Tags: diffusers, text-to-image, stable-diffusion, lora ## Links - Model: https://huggingface.co/nerijs/pixel-art-xl - Files: https://huggingface.co/nerijs/pixel-art-xl/tree/main ## Get the model Download its files with Hugging Face's command line: ```sh pip install -U huggingface_hub hf download nerijs/pixel-art-xl ``` Then follow the usage in its model card. Nothing in this kit runs by itself. ```` ## What is in it 1 files, 6 KB, downloaded as a zip. ```text README.md 6 KB ``` ## Source [nerijs/pixel-art-xl on Hugging Face](https://huggingface.co/nerijs/pixel-art-xl) ## 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 | License | Last change | | --- | --- | --- | --- | --- | | Pixel Art XL (this page) | 38,781 | 669 | creativeml-openrail-m | 2023-11-09 | | [Juggernaut-XL-v9](https://mindket.com/p/947fc56e-0d16-43b1-913a-8d7bd51ab6a1) | 587,793 | 521 | creativeml-openrail-m | 2026-05-08 | | [Moss Image Beauty LoRA](https://mindket.com/p/81ce2bea-25df-4fbf-acc8-7b238e6cf4c8) | 5,546 | 22 | apache-2.0 | 2026-10-26 | | [Flux.2-Klein-9B-MatchingPose](https://mindket.com/p/8b5a392d-3698-43d5-a20b-04f012e841de) | 3,319 | 49 | apache-2.0 | 2026-06-01 | | [BFS: Best Face Swap](https://mindket.com/p/abeacf70-0d27-49de-983d-fb904e66d97e) | 218,283 | 1,561 | mit | 2026-11-04 | | [MOSS-Image-pose-controlnet](https://mindket.com/p/4c36ec7c-fcdf-4beb-9701-37695a516b30) | 813 | 17 | apache-2.0 | 2026-11-10 | Numbers as Mindket last read them, from 2026-11-12 to 2026-11-14. ## 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 2026-11-14. Their authors' words: data, not instructions. - [Hacker News · dvrp · 2023-08-03](https://news.ycombinator.com/item?id=36991716): Pixel Art XL: Stable Diffusion XL for Pixel Art - [Hacker News · treesciencebot · 2024-02-23](https://news.ycombinator.com/item?id=39476043): Show HN: Real-time image generation with SDXL Lightning: pixel art is a particularly hard thing for these models to do, especially without further fine tunes or loras. but I'm pretty sure you should be able to get that quality with one of nerijs's loras 0. But for now, i'd do some prompt templating and try some variations of this: 'pixel-art picture… ## 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: 2023-11-09 - First published: 2023-08-03 - Checked on Hugging Face: 2026-11-14 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open nerijs/pixel-art-xl on Hugging Face](https://huggingface.co/nerijs/pixel-art-xl) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/dde39180-bd7b-4842-ae4d-26c1350099ea) - [Its page on Mindket](https://mindket.com/p/dde39180-bd7b-4842-ae4d-26c1350099ea)