HaDeS MOSS Suite Workflows
This page gathers my ComfyUI workflows for MOSS-Image, each one a new version here. They are built around the HaDeS MOSS Suite nodes and kept simple enough to load and run. Every setting in them comes from measurements, not guesswork, and the measurements are public in the suite's tools/RESULTS.md.
More workflows will follow (merging, LoRA tools, layout prompts...). Follow the page to get them as they come out.
Easy ControlNet Workflow Quick Start Guide
Hey everyone! Here is the ControlNet workflow for MOSS-Image built around the latest v0.6.0 release of the HaDeS MOSS Suite.
This version introduces the dedicated MOSS Control (color / depth) node, specifically designed to handle MOSS's unique 384-channel concat adapter architecture properly.
Requirements & Downloads
Custom Node Suite:
HaDeS MOSS Suite (
v0.6.0+). Install via ComfyUI Manager or git clone into yourcustom_nodes/folder.
ControlNet Adapter:
Grab the Depth adapter by thedeoxen: MOSS-Image-depth-controlnet on Hugging Face. Put the
.safetensorsin yourmodels/loras/directory.
Speed / Turbo LoRA:
HaDeS MOSS Turbo — drops inference down to 8–10 steps without killing quality:
Available on Civitai or Hugging Face.
Base Setup:
MOSS-Image UNet (
moss_image_sft_int8_convrot.safetensorsor bf16/fp8).Text encoder (
qwen3.5_9b_w4a8_gptq.safetensors/ typemoss_image).VAE (
flux2-vae_small.safetensors– 128 channels).Any depth preprocessor of your choice (e.g.
DepthAnythingV2).
How to Use the Workflow
Load your reference photo into the
Load Imagenode.Depth map: Passed from the preprocessor straight into the
depth_mapsocket ofMOSS Control (color / depth).Color map & Reproducing 1:1 vs New Looks:
Near 1:1 Replica: Plug the original image into
color_mapand setcolor_modetoas given. It encodes the real photo’s VAE latent into the color channels, keeping the original lighting, contrast, and tones intact (no post-processing LUTs or color grading needed!).Palette / Layout Transfer: Keep the original image plugged into
color_map, but setcolor_modetoflat regions(8colors,4.0blur). This flattens the reference into color zones, letting the prompt reshape the clothing and textures while preserving the global palette.Depth Only (Fresh generation): Leave
color_mapunplugged and setcolor_modetooff (depth only). MOSS will only follow the geometry and generate everything else from scratch based on your prompt.
Control Strength:
Start at
1.0(the nominal trained weight). You rarely need to push it beyond1.0–1.1.
Turbo Sampling:
If using HaDeS MOSS Turbo, set your sampler to 8–10 steps, Euler, and Beta / Simple scheduler with CFG 1.0. (Push CFG to 1.1/1.2 if you need negative prompt).
Check the map preview directly out of the node's maps output to see exactly what’s being fed to the VAE. Have fun experimenting!
Simple Turbo Image to Image Workflow Example with Prompt Enhancer.
Check out this example workflow for HaDeS-MOSS-Suite: Simple Turbo Image to Image Workflow Example with Prompt Enhancer. It provides an at-a-glance look at how versatile the Prompt Enhancer can be for guiding your image-to-image pipeline, with full telemetry and HaDeS Turbo LoRA integration shown in the preview.
Introducing HaDeS MOSS Suite LoRa Toolkit v0.1
LoRa Merger Node
LoRa Extractor
LoRa Resize
Especially designed for MOSS IMAGE.
Simple Layout Editor v0.1
Simple workflow example of how to use the MOSS Layout Editor and the MOSS Layout Node.
Simple Turbo 8 steps + Upscale x2 v0.2
NEW NODES ADDED!!
MOSS Multi LoRa
MOSS Prompt Enhancer
MOSS Image Saver
Simple Turbo 8 steps + Upscale x2 v0.1
A simple MOSS-Image workflow: generate at 8 steps with our turbo LoRA, then optionally double the size.
Each step is a group that you switch on or off with the Fast Group Bypasser. Groups 2 and 3 are off by default, so you only render the 1024 image until you turn one of them on.
The turbo LoRA used here: HaDeS MOSS Turbo 8-steps v0.7 → [Civitai link to the Turbo model page], (also on Hugging Face: https://huggingface.co/DeVilDoNia/HaDeS-MOSS-Turbo).
What you need
- HaDeS MOSS Suite (ComfyUI Manager or https://github.com/Devildonia/HaDeS-MOSS-Suite)
- rgthree-comfy for the Fast Group Bypasser
- Models:
- diffusion_models: moss_image_sft_bf16 (or int8_convrot)
- text_encoders: qwen3.5_9b_int8_convrot
- vae: flux2-vae
- loras: HaDeS-MOSS-Turbo-8steps-v0.7
- upscale_models: RealESRGAN_x2plus.pth



