vllm-omni/docs/user_guide/diffusion/step_execution.md

Step Execution

Step execution is an opt-in diffusion execution mode enabled with step_execution=True when constructing Omni.

It is not a generic diffusion toggle for every pipeline. Only pipelines that implement the stepwise contract support it today.

Quick Start

from vllm_omni import Omni
from vllm_omni.inputs.data import OmniDiffusionSamplingParams

omni = Omni(
    model="Qwen/Qwen-Image",
    step_execution=True,
)

outputs = omni.generate(
    "A cat sitting on a windowsill",
    OmniDiffusionSamplingParams(
        num_inference_steps=50,
    ),
)

Supported Pipelines

Pipeline	Example models	Step execution
QwenImagePipeline	Qwen/Qwen-Image, Qwen/Qwen-Image-2512	Yes
All other diffusion pipelines	QwenImageEditPipeline, QwenImageEditPlusPipeline, QwenImageLayeredPipeline, GLM-Image, Wan, Flux, etc.	No

Current Limitations

• step_execution currently supports batch_size=1 only.
• cache_backend is not supported together with step execution.
• Unsupported pipelines fail early during model loading.
• Request-mode extras such as KV transfer are not wired into step mode yet.

When To Use It

Use step execution only when you specifically need the pipeline to run through its stepwise request state machine. For normal diffusion inference, leave it disabled unless your workflow depends on this mode.

If you are looking for general diffusion speedups, see Diffusion Acceleration Overview.

Troubleshooting

If model loading fails with a message mentioning prepare_encode(), denoise_step(), step_scheduler(), and post_decode(), the selected pipeline does not support step execution.

For Model Authors

If you want to add step execution support to a new diffusion pipeline, see the implementation guide: Diffusion Step Execution Design.