MATLOWAI/MOSS-Image-SFT-DeBand-int8

MOSS-Image SFT DeBand (int8)

MOSS-Image SFT with its vertical color stripes ("banding") fixed, as single files you load like any other model: no LoRAs, no custom nodes. Each file is 5.4 GB int8 (the same format as Comfy-Org's int8_convrot files) and loads with the stock Load Diffusion Model node.

These are the merged, ready-to-run versions of MATLOWAI/MOSS-Image-SFT-DeBand. That repo has the LoRAs, the full results and the write-up.

Pick one

File	What it is	Steps
moss_image_sft_deband_int8_convrot.safetensors	DeBand: banding fixed, closest to SFT. Start here.	25
moss_image_sft_deband_plus_int8_convrot.safetensors	DeBand+: stronger fix. Best for wide images (1536 px+) and big smooth skies; changes the look a little more.	25
moss_image_sft_deband_fast_dmd035_int8_convrot.safetensors	DeBand Fast: DeBand with lodestones' 8-step DMD LoRA baked in at 0.35.	10

How to use

1. Put the file in ComfyUI/models/diffusion_models/.
2. You also need the MOSS-Image text encoder and VAE from Comfy-Org/MOSS-Image:
   • qwen3.5_9b_int8_convrot.safetensors → models/text_encoders
   • flux2-vae.safetensors → models/vae
3. Drag workflows/moss_deband_int8.json into ComfyUI. Pick your file in Model and the same Version at the top; the version sets the steps.

Already have a MOSS-Image workflow? Just swap the model for one of these and use 25 steps (10 for Fast). Settings used here: ER-SDE sampler, CFG 3, Temporal Score Rescaling and skip-layer guidance (layers 22, 24).

Want 4–8 steps? The Turbo presets need the rapid-moss custom nodes, so they can't be merged into one file, and they only work near 1 MP (bigger sizes tile). For big images, DeBand Fast here is the quick option. See the rapid-moss workflow in the main repo.

Examples

Same prompt and seed (11), 768×1024. The color view removes brightness and boosts color 5×, which makes the stripes easy to see. Banding: about 1.0 = clean.

Fjord sky

Goose at the checkout

Oil still life

Perfume bottle

How close is int8 to full weights?

Each cell is banding · similarity to the same setup in bf16 (SSIM; plain int8 SFT is compared with bf16 SFT, DeBand with the bf16 Quality preset, and so on).

Model	Fog forest	Fjord sky	Goose	Oil still life	Perfume bottle	Mean
SFT int8 (no fix)	2.48 · 95%	2.38 · 98%	2.19 · 83%	2.07 · 93%	1.34 · 98%	2.09 · 93%
DeBand	1.15 · 93%	1.64 · 99%	1.29 · 73%	1.44 · 93%	1.28 · 98%	1.36 · 91%
DeBand+	1.04 · 97%	0.94 · 99%	1.22 · 76%	1.35 · 98%	1.20 · 96%	1.15 · 93%
DeBand Fast	1.22 · 69%	1.39 · 84%	1.21 · 40%	1.07 · 68%	1.12 · 81%	1.20 · 68%

• DeBand and DeBand+ match bf16 closely: about as close as Comfy-Org's int8 SFT is to bf16 SFT. The banding scores match the bf16 presets (1.39 and 1.09 on average).
• DeBand Fast drifts more from bf16 Fast: at 10 steps small weight differences move details the way a nearby seed would. The quality and the banding fix are the same.
• Wide images behave the same as bf16 (tested on the fjord sky): DeBand+ stays clean at 1536 and 2048 px wide; plain DeBand still shows faint wavy stripes on the sky there.

How they were made

• DeBand / DeBand+: Comfy-Org's int8 SFT with layers 37–41 (DeBand) or 32–41 (DeBand+) copied from Comfy-Org's int8 Base. No requantization; every tensor comes straight from their files. The full-weight equivalent is the banding-fix LoRAs.
• DeBand Fast: bf16 SFT with layers 37–41 from Base, plus lodestones' 8-step DMD LoRA (lora_latest) at 0.35, quantized to the same int8 format (per-channel int8, ConvRot 256). This recipe reproduces Comfy-Org's int8 SFT file to within one int8 step on fewer than 0.001% of weights.

SHA-256:

• DeBand 25082f19aaa11a4ebb3309080b5dd8bce59f0557bfd542976a7d6287e4869634
• DeBand+ da4e363d8206f41ffacf95787d7e0a67414dc3adb0636f27de338071d85f9cb5
• DeBand Fast ae5470cc8afb6a1b632d19ad28156c47ce9631fdceb69f3239ccceccd03a1e33

Limitations

• Small test set: five prompts at one seed, two prompts for wide images. Seeds swing the banding score a lot.
• Needs a ComfyUI recent enough to load Comfy-Org's int8_convrot MOSS-Image files.
• DeBand Fast trades some SFT detail for speed, like the Fast preset it comes from.

Credits

• OpenMOSS for MOSS-Image Base and SFT (Apache-2.0), and Comfy-Org for the int8 ConvRot files these are built from.
• lodestones for the 8-step DMD LoRA baked into DeBand Fast (Apache-2.0).
• Kijai for the SFT-difference LoRAs and the note that started the banding investigation.