Model reference · open weights
Ming-Image-0.1-Design is an open-weight image model from inclusionAI. Ming-Image-0.1-Design (BF16) weighs 52.9 GB; the smallest configuration that runs it is L40S 48 GB.
For self-hosting, compare this build's requirements below with the GPU you plan to rent.
Summary of the inclusionAI/Ming-Image-0.1-Design model card, 2026-10-01
What it is
| Released by | inclusionAI |
|---|---|
| Released | 2026-09-17 |
| Parameters | 6.2B |
| VRAM | 52.9 GB for the weights |
What it runs on
| Card | One image | Memory |
|---|---|---|
| RTX 3060 12 GB … RTX 5090 32 GB | does not fit | |
| L40S 48 GB | tight (encoders offloaded) | 44.0 GB |
| A100 80 GB | fits | 78.2 GB |
| H100 80 GB | fits | 78.1 GB |
| RTX PRO 6000 Blackwell 96 GB | fits | 93.8 GB |
| DGX Spark (GB10) 128 GB unified | fits | 107 GB |
| H200 141 GB | fits | 138 GB |
| B200 180 GB | fits | 176 GB |
From the model card
🧩 ModelScope · 🤗 Hugging Face · 📄 Blog · 🖥️ Demo 🎨 Design Skill · 📊 PPT Skill
Ming-Image-0.1-Design is a 6B text-to-image model for UI, infographics, posters, and other text-rich visual designs. It generates complete visual compositions and supports RGBA output with transparent backgrounds.
Use the companion Ming-Image repository for installation and inference:
git clone https://github.com/inclusionAI/Ming-Image
cd Ming-Image
pip install -r requirements.txt
python infer.py \
--model inclusionAI/Ming-Image-0.1-Design \
--task text-to-image \
--prompt assets/t2i_four_seasons_cabin_prompt.json \
--resolution 2048 \
--output-dir outputs/t2i
Prompt enhancement (PE) can use Ling-3.0-flash-VL or qwen3.8-27B; see
text-to-image prompt rewriting.
For transparent-background generation, prepend exactly one of the recommended RGBA phrases. See the transparent-background generation tip.
We recommend the following inference frameworks to serve the model:
The public inference code maps text-to-image resolution requests to the supported 1024 or 2048 bucket.
The checkerboard is used only to preview transparency; it is not part of the generated RGBA images.
This model is released under the MIT License.
Quoted from the model card on Hugging Face. The full card is behind the Hugging Face link above.
Running it yourself
Rent a machine by the hour. ComfyUI is installed on it. Open ComfyUI through the tunnel and load the workflow from the model's card on Hugging Face; choose this model's file in its loader.
# on your rented machine (the ssh line is on its page in the console)
# get REPO FILE FOLDER: one file into /workspace/models/FOLDER, where ComfyUI loads it from
get() { hf download "$1" "$2" --local-dir /workspace/hf-files && mkdir -p "/workspace/models/$3" && mv "/workspace/hf-files/$2" "/workspace/models/$3/$4"; }
# the model (4.1 GB)
get inclusionAI/Ming-Image-0.1-Design transformer/diffusion_pytorch_model-00001-of-00005.safetensors diffusion_models
get inclusionAI/Ming-Image-0.1-Design connector/model-00002-of-00002.safetensors text_encoders
get inclusionAI/Ming-Image-0.1-Design vae/diffusion_pytorch_model.safetensors vae
start-comfyui# on your computer, in a second terminal: ComfyUI in your browser at http://localhost:8188
# HOST, PORT and BOOKING are your machine's, from its page in the console
ssh -o HostKeyAlias=axforge-BOOKING -o StrictHostKeyChecking=accept-new -L 8188:localhost:8188 dev@HOST -p PORT