SGLang
A fast open-source serving runtime with structured generation and high throughput.
SGLang is a serving engine that pairs high throughput with a structured-generation front-end: efficient handling of constrained output, complex prompting patterns, and shared prefixes through prefix caching.
It is a strong choice for serving the latest large open models, and is often quick to support new architectures.
Where it fits
A fit for high-throughput self-hosted serving, especially with structured output or heavy shared-prefix workloads.
Where it does not fit
Overkill for a single-user local model, where a simple runtime is far less effort.
Alternatives to SGLang
The closest options on the map, and where each fits instead.
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vLLM Inference engine
The right engine when you self-host a model under real concurrency and need to use GPU capacity efficiently.
Unlike SGLang Maturity: established
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Text Generation Inference Inference engine
A fit for production self-hosted serving, especially for teams already deep in the Hugging Face ecosystem.
Unlike SGLang Maturity: established
Pairs with
Commonly used alongside it.
