---
title: MOSS_Image_INT6_INT4
canonical_url: "https://www.modelscope.cn/models/tsolful/MOSS_Image_INT6_INT4"
md_url: "https://www.modelscope.cn/models/tsolful/MOSS_Image_INT6_INT4.md"
repository: tsolful/MOSS_Image_INT6_INT4
last_updated: 2026-10-17
license: apache-2.0
pipeline_tag: text-to-image-synthesis
tasks:
  - text-to-image-synthesis
base_model:
  - OpenMOSS-Team/MOSS-Image-Base
  - OpenMOSS-Team/MOSS-Image-SFT
  - Comfy-Org/MOSS-Image
base_model_relation: finetune
library_name:
  - lora
  - safetensors
  - pytorch
frameworks:
  - pytorch
downloads: 32
stars: 0
tags:
  - text-to-image
  - comfyui
  - diffusion
  - diffusion-single-file
  - moss-image
  - int4
  - int6
  - quantized
---

# MOSS_Image_INT6_INT4

> MOSS_Image_INT6_INT4 - tsolful 在 ModelScope 开源的模型。MOSS-Image Base & SFT (INT6 W6A8 & INT4 W4A8) for ComfyUI

tsolful/MOSS_Image_INT6_INT4 是 ModelScope 魔搭社区上的text-to-image-synthesis模型，采用 apache-2.0 许可，基于 OpenMOSS-Team/MOSS-Image-Base、OpenMOSS-Team/MOSS-Image-SFT、Comfy-Org/MOSS-Image 构建。

- **Repository**: tsolful/MOSS_Image_INT6_INT4
- **License**: apache-2.0
- **Tasks**: text-to-image-synthesis
- **Base model**: OpenMOSS-Team/MOSS-Image-Base, OpenMOSS-Team/MOSS-Image-SFT, Comfy-Org/MOSS-Image
- **Tags**: text-to-image, comfyui, diffusion, diffusion-single-file, moss-image, int4, int6, quantized
- **Downloads**: 32
- **Stars**: 0
- **Last updated**: 2026-10-17

Source: https://www.modelscope.cn/models/tsolful/MOSS_Image_INT6_INT4

---

# MOSS-Image Base & SFT (INT6 W6A8 & INT4 W4A8) for ComfyUI

Repackaged model files for ComfyUI with low-bit quantized versions of both **MOSS-Image-Base** and **MOSS-Image-SFT**.

The original models are:

- [OpenMOSS-Team/MOSS-Image-Base](https://huggingface.co/OpenMOSS-Team/MOSS-Image-Base)
- [OpenMOSS-Team/MOSS-Image-SFT](https://huggingface.co/OpenMOSS-Team/MOSS-Image-SFT)

The official ComfyUI repackage (BF16 and INT8 ConvRot diffusion models, text encoders and VAE) is at [Comfy-Org/MOSS-Image](https://huggingface.co/Comfy-Org/MOSS-Image).

## Files

* `diffusion_models/moss_image_base_W6A8.safetensors`: the MOSS-Image-Base diffusion transformer as a single file in ComfyUI's native INT6 W6A8 format.
* `diffusion_models/moss_image_base_W4A8.safetensors`: the MOSS-Image-Base diffusion transformer as a single file in ComfyUI's native INT4 W4A8 (codebook) format.
* `diffusion_models/moss_image_sft_W6A8.safetensors`: the MOSS-Image-SFT diffusion transformer as a single file in ComfyUI's native INT6 W6A8 format.
* `diffusion_models/moss_image_sft_W4A8.safetensors`: the MOSS-Image-SFT diffusion transformer as a single file in ComfyUI's native INT4 W4A8 (codebook) format.

The text encoder and VAE are not included here. Download them from [Comfy-Org/MOSS-Image](https://huggingface.co/Comfy-Org/MOSS-Image):

* [`text_encoders/qwen3.5_9b_int8_convrot.safetensors`](https://huggingface.co/Comfy-Org/MOSS-Image/blob/main/text_encoders/qwen3.5_9b_int8_convrot.safetensors) or [`text_encoders/qwen3.5_9b_w4a8_gptq.safetensors`](https://huggingface.co/Comfy-Org/MOSS-Image/blob/main/text_encoders/qwen3.5_9b_w4a8_gptq.safetensors)
* [`vae/flux2-vae.safetensors`](https://huggingface.co/Comfy-Org/MOSS-Image/blob/main/vae/flux2-vae.safetensors)

## Model storage paths

Place the files in the following folders:

```text
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 diffusion_models/
│   │   ├── moss_image_base_W6A8.safetensors
│   │   ├── moss_image_base_W4A8.safetensors
│   │   ├── moss_image_sft_W6A8.safetensors
│   │   └── moss_image_sft_W4A8.safetensors
│   ├── 📂 text_encoders/
│   │   ├── qwen3.5_9b_int8_convrot.safetensors
│   │   └── qwen3.5_9b_w4a8_gptq.safetensors
│   └── 📂 vae/
│       └── flux2-vae.safetensors
```

Load the diffusion model with ComfyUI's **Load Diffusion Model** node, the same way as the [Comfy-Org](https://huggingface.co/Comfy-Org/MOSS-Image) files. The tensor names match Comfy-Org's repackage, and the quantization settings are stored in ComfyUI's native `_quantization_metadata` header, so no extra loader is needed.

The original model recommends 50 steps, CFG 3, shift 5, and negative-branch skipping at layer 22.
I've have been finding good results at a minimum of 25 steps, CFG 3, and negative-branch skipping at layer 22 (with the shift node at 5 the results are identical without the node)

## Conversion details

The large layers of all 42 transformer blocks (168 layers) are stored at 6 bits (W6A8) or 4 bits (W4A8) instead of 16 bits. Small, sensitive parts such as the embedders, modulation, output layer and norms stay at full precision. Converted with my [ComfyUI-INT8-Fast (fork)](https://github.com/tsolful/ComfyUI-INT8-Fast). Requires `comfy-kitchen >= 0.2.37` on [ComfyUI v0.38.0](https://www.reddit.com/r/comfyui/comments/1wtxujx/comfyui_v0380/) or newer.

### How it compares

| Format | File size | Size vs BF16 | Size vs INT8 | Weight error vs BF16 |
|---|---|---|---|---|
| BF16 ([Comfy-Org](https://huggingface.co/Comfy-Org/MOSS-Image)) | 10.2 GB | 100 % | 188 % | 0 % |
| INT8 ConvRot ([Comfy-Org](https://huggingface.co/Comfy-Org/MOSS-Image)) | 5.4 GB | 53 % | 100 % | ~1 % (estimated) |
| **W6A8** (this repo) | ~4.4 GB | ~43 % | ~81 % | **2.3 %** |
| **W4A8** (this repo) | ~3.3 GB | ~33 % | ~62 % | **7.3 %** |

**Image prediction difference vs BF16 (SFT model):**

| Format | First step (pure noise) | By step 4 |
|---|---|---|
| W6A8 | 5.6 % | 3.2 % |
| W4A8 | 13.2 % | 9.5 % |

* **W6A8:** about 19 % smaller than INT8 and very close to BF16. Images should be nearly identical.
* **W4A8:** about 38 % smaller than INT8, with roughly 3× the error of W6A8. Expect more visible differences in layout and fine detail.
* The difference is largest at the first, noisiest step and shrinks after that.

Check output quality for your own prompts and workflows before relying on it.

## License

The original model is released under the Apache License 2.0.