sglang and vllm
These are competitors offering different optimization approaches—vLLM prioritizes memory efficiency and throughput through PagedAttention, while SGLang emphasizes programmability and structured generation through its domain-specific language for LLM control flow.
About sglang
sgl-project/sglang
SGLang is a high-performance serving framework for large language models and multimodal models.
This project helps developers and MLOps engineers efficiently deploy and manage large language and multimodal AI models. It takes trained AI models and hardware resources as input, then optimizes their performance to deliver faster and more cost-effective AI inference. It's designed for technical professionals building and operating AI-powered applications.
About vllm
vllm-project/vllm
A high-throughput and memory-efficient inference and serving engine for LLMs
This project helps machine learning engineers and developers efficiently deploy and serve large language models (LLMs) in production environments. You provide your chosen LLM and receive a high-throughput, memory-optimized inference service ready for use. It's designed for ML engineers, MLOps specialists, and developers who need to integrate LLM capabilities into applications without sacrificing speed or cost efficiency.
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