sglang-diffusion-add-model

To add a diffusion model to SGLang, integrate the Diffusers pipeline by analyzing reference components, configuring pipeline stages, updating registries, and validating output quality against the source implementation.

Integrating Diffusers pipelines into SGLang requires adapting preprocessing, scheduling, conditioning, and decoding stages while ensuring weight compatibility and tensor parallelism support within the multimodal runtime.

Yes, SGLang supports tensor and sequence parallelism for diffusion models. You must configure parallel execution alongside model components and pipeline stages during the integration process.

Noisy diffusion model output indicates a failed integration. You must validate output quality by comparing intermediate tensors and final generated images against the reference Diffusers implementation to identify mismatches.

Validating video generation models in SGLang involves comparing intermediate tensors and decoded outputs against the reference Diffusers pipeline to ensure generated videos are not noisy and meet stage contract requirements.

Yes, SGLang supports integrating text-to-image, image-to-image, and video diffusion models. You can reuse compatible pipeline stages and model components when adding the new Diffusers variant.