SGLang-Diffusion
A high-performance inference engine and serving stack for diffusion models, built as an extension of the SGLang framework. Designed for image, video, and other generative tasks, it supports both offline batch processing and real-time serving, with optimizations for parallelization and execution path efficiency.
Timeline (last 90 days)
SGLang-Diffusion is a high-performance inference engine and serving stack designed specifically for diffusion models, covering the complete pipeline from request scheduling to parallel model execution.
The SGLang-Diffusion project was announced by Yihao Wang and Kevin Mee from the SGLang team.
SGLang-Diffusion supports both offline batch processing and real-time workloads.
SGLang-Diffusion's technical directions include serving optimization for different parallelization schemes, execution path design, and serving frontier diffusion models on SGLang.
Yihao Wang and Kevin Mee will present SGLang-Diffusion at the PyTorch Conference to be held on October 20–21, 2026, in San Jose, California, USA.
Public information about SGLang-Diffusion remains limited, with further technical details pending disclosure at the conference.
All Facts (6)
SGLang-Diffusion is a high-performance inference engine and serving stack designed specifically for diffusion models, covering the complete pipeline from request scheduling to parallel model execution.
50%UnverifiedThe SGLang-Diffusion project was announced by Yihao Wang and Kevin Mee from the SGLang team.
50%UnverifiedSGLang-Diffusion supports both offline batch processing and real-time workloads.
50%UnverifiedSGLang-Diffusion's technical directions include serving optimization for different parallelization schemes, execution path design, and serving frontier diffusion models on SGLang.
50%UnverifiedPublic information about SGLang-Diffusion remains limited, with further technical details pending disclosure at the conference.
50%UnverifiedYihao Wang and Kevin Mee will present SGLang-Diffusion at the PyTorch Conference to be held on October 20–21, 2026, in San Jose, California, USA.
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