bytedance/USO

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

1235 stars · 77 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

USO is ByteDance's open-source unified style- and subject-driven image generation model based on diffusion (FLUX), combining any subject with any style via disentangled and reward learning. It ships inference code, model weights, a Hugging Face demo, ComfyUI workflows, and plans for training code and datasets.

Use cases

• generate images of a specific subject in a specific artistic style
• style transfer that preserves subject identity
• create stylized portraits with natural, non-plastic faces
• combine reference character with reference art style
• run subject-driven customization on a consumer GPU
• use USO in ComfyUI workflows

When to choose

• you need both subject consistency and style fidelity in one model
• you want a research-grade open model with weights and benchmarks (USO-Bench)
• you work with ComfyUI or Hugging Face and want drop-in FLUX-based customization

When to avoid

• you need text-to-image generation without reference images
• you cannot run GPU inference (~16GB VRAM minimum in fp8 mode)
• you need training code today - it is promised but not yet fully released

Facets

library · maturity active

image-processing machine-learning stable-diffusion image-processing artificial-intelligence computer-vision python style-transfer subject-driven-generation diffusion-model flux comfyui reward-learning cvpr-paper customization gpu docker

Member repositories

For agents

markdown · JSON · MCP: product_card(name="bytedance/USO")