SGLang社区技术进化里程碑与未来路线规划-蔡尚铭.pdf

1、蔡尚铭SGLang社区Core Developer2026/01/31Milestones&Recent Milestones&Recent HighlightHighlight02.02.ContentContentSGLang OverviewSGLang Overview01.01.Future Roadmap Future Roadmap(2026 Q1)(2026 Q1)03.03.SGLang OverviewSGLang is a fast serving framework for large language models and vision language models

2、.Designed to deliver low-latency and high-throughput inference across a wide range of setups,from a single GPU to large distributed clusters.Open-source,incubated by LMSYS Org and supported by a vibrant community with widespread industry adoption,powering over 300,000 GPUs worldwide.Milestones&Recen

3、t Feature HighlightMilestone:Large-scale DeploymentMilestone:Hierarchical KV Caching IntegrationMilestone:Reinforcement Learning IntegrationMilestone:New models day-0 supportSGL DiffusionAccelerate image and video generation for diffusion models for production level servingMajor model support:LLaDA,

4、Wan,Hunyuan,Qwen-Image,Qwen-Image-Edit,FluxIntegrate highly-optimized sgl-kernel amd advanced parallelism techniquesCollaboration with the FastVideoteam/AntGroupSpecBundle&SpecForge v0.2:SpecForge:A framework for training draft models that integrate natively with SGLangScalable Distributed Training,

5、Memory-Efficient TrainingSpecBundle:a collection of production-grade EAGLE-3 model checkpoints trained on large-scale datasets.Native Support for Advanced Model Architectures:Llama 4,DeepSeek,Qwen3 MoE,GTP-OSSCollaborated with multiple industry partners-including Ant,Meituan,Nex-AGI,and EigenAIMini-

6、SGLangA lightweight yet high-performance inference framework sharing the high-level systemarchitectures as SGLangTwo main objectives:providing learning resources and enabling fast prototyping for research.https:/ Disaggregation for VLMA novel architecture that separates vision en