---
title: Boogu-Image-0.1-Turbo-8bit
canonical_url: "https://www.modelscope.cn/models/mlx-community/Boogu-Image-0.1-Turbo-8bit"
md_url: "https://www.modelscope.cn/models/mlx-community/Boogu-Image-0.1-Turbo-8bit.md"
repository: mlx-community/Boogu-Image-0.1-Turbo-8bit
last_updated: 2026-06-21
license: apache-2.0
pipeline_tag: text-to-image-synthesis
tasks:
  - text-to-image-synthesis
base_model:
  - Boogu/Boogu-Image-0.1-Turbo
base_model_relation: finetune
parameters: 4.0B
tensor_type:
  - F32
  - BF16
  - U32
library_name:
  - mlx
  - lora
  - safetensors
  - diffusers
  - pytorch
frameworks:
  - pytorch
language:
  - en
  - zh
downloads: 45
stars: 1
tags:
  - mlx
  - safetensors
  - apple-silicon
  - text-to-image
  - image-editing
  - diffusion
  - omnigen2
  - boogu
---

# Boogu-Image-0.1-Turbo-8bit

> Boogu-Image-0.1-Turbo-8bit - mlx-community 在 ModelScope 开源的模型。mlx-community/Boogu-Image-0.1-Turbo-8bit

mlx-community/Boogu-Image-0.1-Turbo-8bit 是 ModelScope 魔搭社区上的 4.0B 参数text-to-image-synthesis模型，采用 apache-2.0 许可，基于 Boogu/Boogu-Image-0.1-Turbo 构建。

- **Repository**: mlx-community/Boogu-Image-0.1-Turbo-8bit
- **License**: apache-2.0
- **Tasks**: text-to-image-synthesis
- **Parameters**: 4.0B
- **Base model**: Boogu/Boogu-Image-0.1-Turbo
- **Tags**: mlx, safetensors, apple-silicon, text-to-image, image-editing, diffusion, omnigen2, boogu
- **Downloads**: 45
- **Stars**: 1
- **Last updated**: 2026-06-21

Source: https://www.modelscope.cn/models/mlx-community/Boogu-Image-0.1-Turbo-8bit

---

# mlx-community/Boogu-Image-0.1-Turbo-8bit

MLX (int8) conversion of **[Boogu-Image-0.1-Turbo](https://huggingface.co/Boogu/Boogu-Image-0.1-Turbo)** (Apache-2.0)
for Apple Silicon. 4-step Decoupled-DMD distilled (guidance 1.0) — ~6x faster. OmniGen2-lineage pipeline (DiT + FLUX.1 VAE + FlowMatchEuler).
The **Qwen3-VL-8B-Instruct** text encoder is stock (bit-identical) — referenced from
[`mlx-community/Qwen3-VL-8B-Instruct`](https://huggingface.co/collections/mlx-community/qwen3-vl), not re-hosted.

**int8** (group_size=32, attn+FFN); quant auto-detected via `quant_config.json`. ~12.5 GB.

## Use
```bash
pip install mlx mlx-vlm && git clone https://github.com/xocialize/boogu-image-mlx && cd boogu-image-mlx && pip install -e .
```
```python
from boogu_image_mlx.pipeline_mlx import BooguImagePipeline
pipe = BooguImagePipeline.from_pretrained("<this repo dir>", "mlx-community/Qwen3-VL-8B-Instruct")
img = pipe.generate("a red panda surfing on a wave, photorealistic", steps=4, guidance=1.0)  # 4-step DMD
```
Code: https://github.com/xocialize/boogu-image-mlx