sglang
A high-performance serving framework for large language models and multimodal models, delivering low-latency and high-throughput inference.
What is sglang?
SGLang is a high-performance serving framework specifically designed for deploying and running large language models (LLMs) and multimodal models in production. It solves the problem of achieving low-latency and high-throughput inference across various hardware setups, from single GPUs to large distributed clusters. The framework includes optimizations like RadixAttention, speculative decoding, and continuous batching to maximize efficiency.
AI engineers, ML researchers, and DevOps teams who need to deploy and serve LLMs and multimodal models at scale in production environments. It is also suitable for organizations requiring efficient inference on diverse hardware, including NVIDIA, AMD, and TPU systems.
Developers choose SGLang for its exceptional performance, broad model and hardware support, and proven scalability in production. Its unique selling point is being a comprehensive, open-source framework that combines cutting-edge optimizations with extensive compatibility, making it a reliable choice for large-scale AI serving.
Overview
SGLang is a high-performance serving framework for large language models and multimodal models.
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