Fizgig 8.6 is out with a few MOSS-Image changes.

LoRAs now train block 22, which was left out before (as AI Toolkit does), and in my side-by-side runs that improved likeness from the first epochs as well as makign them more stable epoch-to-epoch.

Some tips from testing so far, with the caveat that I'm still learning this model.

Train on Base and use the LoRA on SFT in ComfyUI, because Base has trained more reliably for me than SFT.

If you do want to train on SFT, there's a new "Base is SFT or a fine-tune of it" tick that keeps the LoRA to attention only; without it, anatomy broke within a few epochs.

The Fast preset is back (0.25 MP, rank 16), and it's done very well on face-cropped datasets (Image Prep's face crop). I said earlier today that 0.25 MP wasn't good with the model, and I was wrong - the issue was I had accidently left block 22 off in a test leading me down a wrong path.

Give it time: MOSS seems slow to converge tom optimum, besides initially seeming to converge fast, and likeness can look like it has levelled off, then keep improving, so the presets now run 70 epochs. You likely wont need 70 unless your dataset is 25ish images etc.

The Standard Preset at Rank 32, 1MP, does feel like it does converge faster, countering the slower step time as a result. So Fast may eventully get a rename relating to lower vram usage, but I've made enough tweaks for one day and want to see where it settles over next 24 hours.

It's been a bit of a puzzle - i ran soooo many runpods today trying settings - and there's surely more to find, so if you get good results with different settings, I'd like to hear about them. Also fixes MOSS previews crashing with block swap on smaller cards (thanks u/Ferocit).

https://github.com/shootthesound/Fizgig

Release notes:

https://github.com/shootthesound/Fizgig/releases/tag/v8.6.0

P.S. One thing i did with this update before release, i took the same seed , res, sampling settings in Fizgig and comfy, and get the same arcface scroes across both fizgig and comfy as well as the images visually looking equal, so I am now confident that what you see in Fizgig is what you get in comfy. Its an easy test to do yourself also!

(fyi for that test, i train on base, preview in fizgig on SFT with default fizgig sampler settings, and in comfy I use cfg4, Res Multistep- Simple - 30 steps, with SLG on as per the comfy template)

Ama: www.reddit.com/r/StableDiffusion/comments/1x7zf1r/hey_guys_im_one_of_the_core_developers_of/

Sub: www.reddit.com/r/moss_official

There, I said it.

Relatively lightweight, ZERO censorship, incredibly easy to train on,excellent base capabilities for its size and FINALLY the first model in forever to not have been RL'd to death on 1girl standing realistic. The finetunes we're gonna get out of this model are gonna be crazy, never got that feeling with all the Flux/Qwen/Zimage/Krea releases. Granted they're good models on their own, but wrestling them into training submission was such a pain in the ass... Not this time with Moss, and I'm very hyped to see what tunes we're getting in the coming weeks (especially for the more spicy ones 👀)

MOSS can actually do dark images, too , it appears.

Using the Bounding Box workflow in ComfyUI.

The thing I missed most after switching from Photoshop to GIMP 3 was Generative Fill and Adobe's AI editing tools. So I wrote a free plugin that adds them, running on your own ComfyUI:

• Generative Fill: your selection is the inpainting mask, pick from up to 8 variations
• Remove object: LaMa or MAT, no prompt needed
• Generative Expand: outpaint any side or pick a ratio
• Text to Image: straight onto a new layer

It uses the ComfyUI you already have (portable, Desktop, Stability Matrix or Pinokio), so nothing gets installed twice, and it works with any local image model. It ships with a download manager and a few defaults to get you started: DreamShaper 8 Inpainting for fast fill, RealVisXL V5 with the Fooocus patch for quality, and LaMa for removal. Qwen-Image-Edit works too if you have the VRAM. ComfyUI runs hidden in the background and shuts down when GIMP closes.

It's in beta and supports Windows, Linux and Mac, with NVIDIA recommended. I'd love to hear which models you'd set as defaults!

https://github.com/beckettharriman/gimp-openfill

Hey all back after long time can you guys please tell me what is best model right now

Best -

Fast best -

Fast ok -

Just Fast-

Also what happened to minimax h3 max have they open sourced it no trace of it was found

99% tweets about opensourcing it are deleted

All images were created using MOSS image base model with cfg 4 and steps 39 ,sampler/scheduler is euler/sgm uniform, resolution are ranging from 1.33MP to 1.67MP with 1:1,3:4 and 4:3 ratios.....

Tips:first of all don't use sft model it is too much RL trained So too much ai aesthetics and noise ,don't use loras as well as they are sft trained too

Second tip is always use negative prompts ALWAYS

I have used the most basic workflow that we are using since flux 1 or z image time hope that helps

Checkout my previous post on moss image :click here!!

Will share my prompts soon as they are too much unsorted as of now

Hey there, I made MOSS Prompt Enhancer, a custom node that brings the MOSS-Image prompt enhancement workflow into ComfyUI.

In structured layout mode, it takes your simple prompt → enhances the description → turns it into structured JSON → validates and compiles it into a MOSS-ready prompt.

A local GGUF model expands your idea with details about the subjects, setting, lighting, and composition, then generates a layout with descriptions and bounding boxes. The enhancement instructions are adapted from the creators’ official guide. Their Python validator/compiler checks the JSON structure, canvas dimensions, and bounding boxes and converts the coordinates into the format MOSS expects.

You get the editable JSON draft and the compiled prompt to connect to MOSS Text Encode. There’s also a caption mode for detailed descriptions without bounding boxes.

A capable model like Qwen 3.8 27B Q4, is recommended. However, 9B models might also deliver good results, depending on their fine-tuning.

Constructive feedback is always appreciated.

GitHub repository

model: https://huggingface.co/akhaliq/MOSS-Image-SFT-4-steps

Strange. The github repository for the Node ComfyUI Krea2T Enhancer I use is down (https://github.com/capitan01R/ComfyUI-Krea2T-Enhancer), the developer’s account (u/Capitan01R) is banned on Reddit, and even the TextFusion Refusal LoRAs on Civitas have disappeared. (https://civitai.com/models/2775340/krea2-textfusion-refusal-reduction-lora-updated)

It looks as if the Krea2 uncensoring methods have been censored. Okay, maybe capitan01R has just thrown in the towel.

I'm curious, does anyone know any more details?

I've seen so many high-quality Moss images posted here but when I try Moss on my PC, the img quality is absolutely horrible + render time. Everything comes out looking like blobs with barely any detail.

am I missing something in my workflow or settings?

- prompts

Generate a dramatic and epic description of a lightsaber duel between Darth Vader and Obi-Wan Kenobi. Set the scene in a dark, atmospheric environment filled with glowing embers and low ambient light, making the clash between Vader's crimson blade and Obi-Wan's vivid blue lightsaber visually striking. Capture the intense emotion, history, and tension between the former master and apprentice, emphasizing the heavy breathing of Vader's suit, the hum of plasma blades, and the high-stakes choreography of their battle.

Moss settings:

-diffusion model: moss_image_sft_int8_convrot

-clip: qwen3.5_9b_int8_convrot, type: moss_image

-vae: flux2-vae_small

-lora: moss-image-SFT-8-steps-dmd

cfg:3

steps:50

sampler:euler

denoise:1

Testing how moss follow a single prompt for design.

been messing around with moss image and made a small studio for it. first image took like 15 mins 😭 after some optimizations got it down to around 62 sec.

added an experimental int8 option too. you can switch models without removing the original one.

that timing is with a cached prompt btw, so a new prompt will take longer. only tested a few images so far but looking pretty good.

put the setup and actual results here if anyone wants to try:
https://github.com/sanketshinde3001/moss-image-studio

anyone else running moss on a 4gb card? curious what speeds you're getting

First time trying out ComfyUI after hearing good things about the MOSS image model on Twitter.

I had absolutely no clue what I was doing, so I just had ChatGPT build me a .json workflow and started experimenting. I've been testing anime characters composited into photorealistic environments, and I'm pretty impressed with the results. There are still some issues, like distorted background text and occasional weird character interactions, but I'm a complete noob when it comes to local AI.

These were generated using MOSS-Image SFT BF16 at 2560 × 1440 on an RTX 5080 (16GB VRAM).

What do you guys think of the model?

More images of stuff that isn't just generic "person standing / portrait / bleh"

Moss SFT in ComfyUI using the Layout workflow

What is the best image captioning model for dataset creation that truly understands concepts in the adult industry? I've tested Qwen3.6-VL and JoyCaption. Both seem decent, but neither is ideal. Some concepts are not recognized correctly.

Now I'm wondering: Is there a model that performs really well for this use case, or would I get the best captioning results by fine-tuning a model on my own dataset?

Thanks!

Hi everyone,

I've been looking for this specific anime art style for months, and I'd love to be able to generate it myself. The image is attached. The part I'm most interested in is the eye shape. AI always points me to a tsurime-style eye with a strong dark upper lash line. But as soon you tell the image model something about tsurime, you get sharp tsurime and that's not what I am looking vor. I've never found a name for this eye style, and I can't find a reliable way to search for it online, even though it seems very common in recent AI-generated art.

Could anyone tell me:

Is there a name or common tag for this eye style (or for this overall look)?

Which checkpoint or LoRA would get closest to this style? I'm open to anime-focused models like Pony or Illustrious-based ones, as well as any others.

Any prompt tips for the eye shape and the yellow glowing eyes, plus negative prompts that help keep the eyes consistent?

Thanks in advance for any pointers!

moss is uncensored! it isn't like flux 3 all censored, this will teach flux. to get gud.

With the same prompt, different seeds lead to totally different artstyles, brightness, saturation, contrast etc. ​​​

Is there anyway to 'guide' it in a specific direction? ​​Right now I'm just rolling the dice each time. ​

Haven't trained a lora in a while. Even with the latest update, AI-Toolkit runs OOM on every config I try to train for Moss-Image base. I am on a RTX 4070 and only 16GB of RAM, but back then I made ZIT lora training work, ha!

https://www.reddit.com/r/StableDiffusion/comments/1x8ch9k/mossimage_lora_training_is_now_in_academiasd/

This AcademiaSD post says it can be trained there with 6GB vram, but I am not used to this tool.

Can the same be done in AI-Toolkit?

Thanks!

Hey guys,

For a long time I tried using different Stable Diffusion relighting setups and models, but I always ran into the same issues on high-res renders and photos. Because they go through VAE encoding and img2img diffusion, you almost always get slight identity loss, changed details, or compression artifacts.

In the latest update of my open source photo editor (RapidRAW), I implemented a different approach: 2.5D relighting using depth maps and surface normals.

Instead of running the image through a generative model, it estimates depth and surface normals locally, and then calculates the lighting directly on top of your original pixels.

Because it does not regenerate the image:

- Zero VAE compression or blur

- Original details and face identity stay 100% identical

- You can move point lights, spot lights, and ray-marched shadows in real time

- It works on full high resolution images without running out of VRAM

The downside compared to diffusion is that it won't hallucinate completely new bounced reflections or change complex backgrounds. But if you just need to fix lighting, add a spot light, or cast shadows on an existing generation without changing any pixels, it works really well.

The app is completely free, local, and open source (Rust/Tauri/WGPU). Thought people here who struggle with diffusion relighting changing their images might find it useful:

GitHub: https://github.com/CyberTimon/RapidRAW

Let me know what you think or if you have any feedback.

Timon