SGLang

TL;DR

Fast serving with RadixAttention for prefix caching. Optimized for structured generation.

Use when

  • +Structured outputs needed
  • +Heavy prefix reuse
  • +RAG applications

Skip when

  • -Simple text generation
  • -Non-NVIDIA hardware

SGLang is a structured generation language and serving framework. It features RadixAttention for efficient prefix caching and a programming model for complex LLM programs.

Features

- **RadixAttention**: Radix tree-based prefix caching - **Structured Generation**: Constrained decoding - **High Performance**: Comparable to vLLM - **Programming Model**: DSL for LLM workflows

Best For

- RAG pipelines - Structured outputs (JSON) - Multi-turn conversations

Code Examples

SGLang structured generationpython
import sglang as sgl

@sgl.function
def json_gen(s):
    s += "Generate JSON: " + sgl.gen("json", regex=r'\{.*\}')

References