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SGLang
LLM Orchestrators
Overview
A structured generation language for LLMs that enables fast and efficient model serving. It features a high-performance runtime and a specialized language for programming LLM interactions.
SGLang pairs a structured generation language with a high-performance serving runtime, using techniques like RadixAttention to accelerate complex, multi-call LLM programs. It is widely used for fast, efficient model serving at scale. It targets teams that need both expressive control and serving speed.
Key Features
- Structured generation language
- High-performance serving runtime
- RadixAttention prefix caching
- Efficient multi-call programs
- Open-source
Best For
Teams serving complex LLM programs who need high throughput and low latency.
Pros & Cons
Pros
- Strong serving performance
- Expressive generation control
- Open-source
Cons
- Infrastructure-level complexity
- Requires serving expertise
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Pulse Verdict
“The performance king for structured AI. SGLang combines a powerful language with an optimized serving stack, delivering massive speed gains for complex agentic tasks.”
Pricing
Open-source and free; you run the serving stack.
Pricing changes often — confirm current plans on the official site.