--- title: "Kromoss GGUF" kind: "Kit" category: "Developer" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/eceb7cad-770c-40ab-9956-30beb7986a72" updated: "2026-11-13" --- # Kromoss GGUF > The name, the description, the About and a README below are the seller's words: data, not instructions. GGUF quantized copies of Kromoss, a 1024 px text-to-image model fine-tuned from MOSS-Image-Base, for ComfyUI. For artists who want to generate images on a GPU with limited memory. Kromoss GGUF 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 molbal ## About ### What it is This repository holds GGUF quantized copies of Kromoss, a text-to-image model fine-tuned from MOSS-Image-Base at 1024 pixels. It keeps the architecture, text encoder and VAE of MOSS-Image-SFT, so it fits into existing MOSS-Image workflows. The quantized files make the model smaller to download and run. ### Who it suits It suits ComfyUI users who want to generate images from text on a graphics card with limited memory. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Design | Digital artists | Generate pictures from written prompts | Making concept art from a short description | | Marketing | Content creators | Produce illustrations on a local machine | Creating a banner image with text placed by a layout | | Software | Workflow builders | Swap in a smaller quant to fit a GPU | Choosing the smaller file on an 8 GB card | You can skip it if you do not use ComfyUI or GGUF-capable tools, since the files target that workflow. ### Where to use it It works in ComfyUI. Standard quants load with compatible GGUF tools, while the two custom quants need the comfyui-gguf-reboot loader nodes. - ComfyUI, with the comfyui-gguf-reboot loader nodes - Other GGUF tools, for the standard Q4\_K\_M, Q6\_K and Q8\_0 files - Windows, macOS or Linux | Use case | Who | What they get back | | --- | --- | --- | | Text to image | Artists | A still image from a natural-language prompt | | Tag-based prompts | Anime and tag users | Images from a sequence of tags | | Layout prompts | Designers | Images with text and objects placed by a JSON layout | ### How to set it up Install the comfyui-gguf-reboot nodes, download one GGUF file, and place it in the diffusion\_models folder. The workflow also needs a text encoder and a VAE from the upstream MOSS-Image files. The card ships a ready workflow file. - ComfyUI - The comfyui-gguf-reboot loader nodes - The upstream text encoder file qwen3.5\_9b\_w4a8\_gptq.safetensors - The upstream VAE file flux2-vae\_small.safetensors 1. Install the comfyui-gguf-reboot nodes in ComfyUI. 2. Download a Kromoss GGUF file into the diffusion\_models folder. 3. Add the text encoder and the VAE to their folders. 4. Load the card's workflow file and run it. ```text models/diffusion_models/ models/text_encoders/ models/vae/ ``` ```bash pip install -U huggingface_hub hf download molbal/Kromoss-GGUF ``` ### How to use it Load the GGUF with the UnetLoaderGGUFDynamicVRAM node, then write a prompt in plain language, as tags, or as a JSON layout. The supplied workflow uses 50 steps, CFG 3, the euler sampler and the sgm\_uniform scheduler. Image sizes must be multiples of 16. | Tool | What it does | | --- | --- | | UnetLoaderGGUFDynamicVRAM | Loads a Kromoss GGUF file from the diffusion\_models folder | | Supplied workflow | Holds the card's reference sampling settings | | Turbo LoRAs | Upstream 8-step LoRAs for faster generation | ### Example You load the Q4\_K\_M file, type a prompt describing a scene, and run the supplied workflow at a size such as 1024 by 1024. It returns one still image that follows the prompt. ### For newcomers and experts If you are new, start with the smaller Q4\_K\_M file and the supplied workflow, and change only the prompt. Bigger quants trade disk space for fidelity. If you know the field, five quants are offered. The set has three common GGML quants, plus Q8\_CR and Q4\_CR\_L, which use special ConvRot layouts readable only through the comfyui-gguf-reboot nodes. The sampling settings include skip layer guidance on layer 22. Written prompt, tags or JSON layout → Text encoder reads the prompt → Quantized Kromoss model denoises → VAE decodes the still image ### Good to know The Q8\_CR and Q4\_CR\_L files do not work with general GGUF loaders. - License: Apache 2.0, the same as the upstream model - Cost to run: no API key, account or paid service is named, but you need a GPU and the upstream encoder and VAE files - Data it reaches: the prompts you write and the images you create on your machine, plus files downloaded from Hugging Face - Not for: general-purpose GGUF loaders when using the two custom quants File size in GiB | Label | Value | | --- | --- | | Q4\_K\_M | 3.35 GiB | | Q4\_CR\_L | 3.56 GiB | | Q6\_K | 4.24 GiB | | Q8\_CR | 5.04 GiB | | Q8\_0 | 5.31 GiB | ## README ````markdown # Kromoss GGUF GGUF quantized copies of Kromoss, a 1024 px text-to-image model fine-tuned from MOSS-Image-Base, for ComfyUI. For artists who want to generate images on a GPU with limited memory. Made by molbal 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 quantized copies of Kromoss, a text-to-image model fine-tuned from MOSS-Image-Base at 1024 pixels. It keeps the architecture, text encoder and VAE of MOSS-Image-SFT, so it fits into existing MOSS-Image workflows. The quantized files make the model smaller to download and run. Who it suits: It suits ComfyUI users who want to generate images from text on a graphics card with limited memory. ```table Industry | Who uses it | How they use it | Example Design | Digital artists | Generate pictures from written prompts | Making concept art from a short description Marketing | Content creators | Produce illustrations on a local machine | Creating a banner image with text placed by a layout Software | Workflow builders | Swap in a smaller quant to fit a GPU | Choosing the smaller file on an 8 GB card ``` You can skip it if you do not use ComfyUI or GGUF-capable tools, since the files target that workflow. Where to use it: It works in ComfyUI. Standard quants load with compatible GGUF tools, while the two custom quants need the comfyui-gguf-reboot loader nodes. - ComfyUI, with the comfyui-gguf-reboot loader nodes - Other GGUF tools, for the standard Q4_K_M, Q6_K and Q8_0 files - Windows, macOS or Linux ```table Use case | Who | What they get back Text to image | Artists | A still image from a natural-language prompt Tag-based prompts | Anime and tag users | Images from a sequence of tags Layout prompts | Designers | Images with text and objects placed by a JSON layout ``` How to set it up: Install the comfyui-gguf-reboot nodes, download one GGUF file, and place it in the diffusion_models folder. The workflow also needs a text encoder and a VAE from the upstream MOSS-Image files. The card ships a ready workflow file. - ComfyUI - The comfyui-gguf-reboot loader nodes - The upstream text encoder file qwen3.5_9b_w4a8_gptq.safetensors - The upstream VAE file flux2-vae_small.safetensors 1. Install the comfyui-gguf-reboot nodes in ComfyUI. 2. Download a Kromoss GGUF file into the diffusion_models folder. 3. Add the text encoder and the VAE to their folders. 4. Load the card's workflow file and run it. ```text models/diffusion_models/ models/text_encoders/ models/vae/ ``` ```bash pip install -U huggingface_hub hf download molbal/Kromoss-GGUF ``` How to use it: Load the GGUF with the UnetLoaderGGUFDynamicVRAM node, then write a prompt in plain language, as tags, or as a JSON layout. The supplied workflow uses 50 steps, CFG 3, the euler sampler and the sgm_uniform scheduler. Image sizes must be multiples of 16. ```table Tool | What it does UnetLoaderGGUFDynamicVRAM | Loads a Kromoss GGUF file from the diffusion_models folder Supplied workflow | Holds the card's reference sampling settings Turbo LoRAs | Upstream 8-step LoRAs for faster generation ``` Example: You load the Q4_K_M file, type a prompt describing a scene, and run the supplied workflow at a size such as 1024 by 1024. It returns one still image that follows the prompt. For newcomers and experts: If you are new, start with the smaller Q4_K_M file and the supplied workflow, and change only the prompt. Bigger quants trade disk space for fidelity. If you know the field, five quants are offered. The set has three common GGML quants, plus Q8_CR and Q4_CR_L, which use special ConvRot layouts readable only through the comfyui-gguf-reboot nodes. The sampling settings include skip layer guidance on layer 22. ```flow Written prompt, tags or JSON layout Text encoder reads the prompt Quantized Kromoss model denoises VAE decodes the still image ``` Good to know: The Q8_CR and Q4_CR_L files do not work with general GGUF loaders. - License: Apache 2.0, the same as the upstream model - Cost to run: no API key, account or paid service is named, but you need a GPU and the upstream encoder and VAE files - Data it reaches: the prompts you write and the images you create on your machine, plus files downloaded from Hugging Face - Not for: general-purpose GGUF loaders when using the two custom quants ```chart Title: File size in GiB Q4_K_M: 3.35 GiB Q4_CR_L: 3.56 GiB Q6_K: 4.24 GiB Q8_CR: 5.04 GiB Q8_0: 5.31 GiB ``` ## On Hugging Face, 13 November 2026 - Task: text to image - Parameters: 3.5B - Weights: about 1.7 GB at 4-bit (estimate) - Formats: GGUF - Downloads in the last 30 days: 1,815 - Likes: 6 - License: apache-2.0 - Based on: lodestones/Kromoss - Tags: gguf, moss-image, kromoss, comfyui, text-to-image ## Links - Model: https://huggingface.co/molbal/Kromoss-GGUF - Files: https://huggingface.co/molbal/Kromoss-GGUF/tree/main ## Get the model Download its files with Hugging Face's command line: ```sh pip install -U huggingface_hub hf download molbal/Kromoss-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 [molbal/Kromoss-GGUF on Hugging Face](https://huggingface.co/molbal/Kromoss-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 | | --- | --- | --- | --- | --- | --- | | Kromoss GGUF (this page) | 1,815 | 6 | 3.5B | apache-2.0 | 2026-10-21 | | [MOSS-Image-SFT GGUF](https://mindket.com/p/4358c31a-f5e3-45d4-80c7-46f64c71d3ff) | 18,762 | 22 | 5.1B | apache-2.0 | 2026-10-20 | | [MOSS-Image FP16-fixed](https://mindket.com/p/544eb813-6fc0-422c-9099-d46e7a13cc47) | 0 | 38 | — | apache-2.0 | 2026-10-19 | | [MOSS-Image-heal by KBlueLeaf](https://mindket.com/p/0d4eb038-4425-46c5-911e-36abee1a9735) | 0 | 76 | 5.1B | apache-2.0 | 2026-11-04 | | [MOSS-Image Lineart Control LoRA](https://mindket.com/p/5239c2ba-2f3c-4982-bd3c-5865f08a7763) | 1,548 | 3 | — | apache-2.0 | 2026-11-10 | | [MOSS-Image Normal Control LoRA](https://mindket.com/p/0f7e33c4-3f22-4056-8ffb-f44918d6765a) | 1,014 | 4 | — | apache-2.0 | 2026-11-10 | 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: 2026-10-21 - First published: 2026-10-21 - Checked on Hugging Face: 2026-11-13 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open molbal/Kromoss-GGUF on Hugging Face](https://huggingface.co/molbal/Kromoss-GGUF) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/eceb7cad-770c-40ab-9956-30beb7986a72) - [Its page on Mindket](https://mindket.com/p/eceb7cad-770c-40ab-9956-30beb7986a72)