A ComfyUI custom node package for the OmniGen2 multimodal generation model.

Notice: This project is no longer maintained.

ComfyUI-OmniGen2 is archived because official support for OmniGen2 has been added to ComfyUI (see commit ec70ed6aea05c3a380ad0e15d8221c7bf61be7bb). Please refer to the official implementation and tutorial for the latest usage:

• Official implementation: https://github.com/comfyanonymous/ComfyUI/commit/ec70ed6aea05c3a380ad0e15d8221c7bf61be7bb
• Official tutorial: https://docs.comfy.org/tutorials/image/omnigen/omnigen2

We recommend using the official nodes and documentation for better compatibility and future support.

OmniGen2 is an open-source, state-of-the-art multimodal generative model supporting text-to-image, image editing, in-context generation, and visual understanding. It features decoupled text/image decoding, robust visual reasoning, and efficient inference with advanced offloading and quantization options. OmniGen2 achieves competitive results on both understanding and generation tasks, and is designed for research and creative applications.

• Visual Understanding: Strong image analysis and Q&A capabilities
• Text-to-Image Generation: High-fidelity, prompt-driven image synthesis
• Instruction-Guided Image Editing: Precise, instruction-based image modifications
• In-Context Generation: Flexible composition and blending of multiple images and instructions
• Efficient Inference: Supports CPU/GPU offload, batch generation, and memory optimization

• Easy Model Loading: Load models from local folders or HuggingFace with auto-download and correct folder structure
• CPU Offload Support: Enable sequential or model offload for low-VRAM environments

OmniGen2 models are stored in models/omnigen2/. The ComfyUI-OmniGen2 node will auto-download from HuggingFace if not found locally, or you can download manually:

# Option 1: Use git lfs (recommended for HuggingFace)
cd models/omnigen2
git lfs install
git clone https://huggingface.co/OmniGen2/OmniGen2

# Option 2: Use huggingface-cli
pip install huggingface_hub
huggingface-cli download OmniGen2/OmniGen2 --local-dir OmniGen2 --local-dir-use-symlinks False

# Option 3: Use ModelScope (for users in China)
pip install modelscope
cd models/omnigen2
modelscope download --model OmniGen2/OmniGen2 --local_dir OmniGen2

Note: If you are in a restricted network environment, manual download is recommended. Place the model folder under models/omnigen2/ with the folder name matching the last part of the repo_id (e.g., OmniGen2).

Install required Python packages:

pip install -r requirements.txt

For optimal performance, you may also install:

pip install flash-attn==2.7.4.post1 --no-build-isolation

Restart ComfyUI to load the new nodes.

• Set your prompt, image size, and other parameters

• Provide one or more input images to the OmniGen2Sampler node
• Use the prompt to describe the desired edit or composition
• Adjust image_guidance_scale for more/less faithfulness to the input image(s)

• Use the model in Q&A or analysis mode (see upstream OmniGen2 documentation for advanced usage)

• Loads the OmniGen2 pipeline from a local folder or HuggingFace
• Supports precision selection (fp32, fp16, bf16) and CPU offload options
• Auto-downloads model if not found locally

• Performs text-to-image, image editing, or in-context generation
• Accepts up to 3 input images (as ComfyUI IMAGE tensors)
• Returns a single ComfyUI IMAGE tensor (compatible with downstream nodes)
• All image conversions are handled automatically

• VRAM Usage: BF16 is recommended for best speed/memory tradeoff; enable offload for low-VRAM GPUs
• Batch Generation: Set num_images_per_prompt > 1 for multiple outputs; results are collaged automatically
• Image Guidance: Increase image_guidance_scale for more faithful edits; decrease for more creative results
• Negative Prompts: Use the negative_prompt field to avoid unwanted artifacts
• Troubleshooting: If HuggingFace download fails, check your network/proxy/DNS or download manually

• OmniGen2 Official Repo
• HuggingFace Model
• Technical Report
• Project Page

This project is licensed under the Apache 2.0 License. Please refer to the official license terms for the use of the OmniGen2 model.

• Try manual download and place the model in models/omnigen2/ with the correct folder name
• Check your network, proxy, and DNS settings

Contributions are welcome! Please submit issues or pull requests for bug fixes, features, or documentation improvements.