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SGLang

Free

Fast structured generation and serving runtime for LLMs.

Open SourceAPISelf-hostedPython SDK

Tool Info

Categories
Serving · Infrastructure
Developer
SGLang
License
Open Source
Official Website
sgl-project.github.io
Repository
sgl-project/sglang
Official Docs

Overview

SGLang is a serving framework optimized for structured LLM generation.

Uses RadixAttention for efficient KV cache reuse.

v0.5.21 (2026-10-02) adds a Decisions API (`/v1/decisions`) that serves an LLM or VLM as a low-latency classifier and scorer, a System One–compatible `/v1/systemone` route for decision-model clients, and a Score API (`/v1/score`) that scores all candidates in one request. Prefill/decode-disaggregated instances can switch roles without a restart, and the prefix cache runs on a Rust core by default.

Pricing

Free tier available
Free (open source)

Pros

  • Very fast inference
  • Structured output focus
  • Strong benchmarks

Best For

Structured generationHigh-performance servingRadixAttention workloads

When NOT to Use

  • Newer than vLLM
  • Smaller community

Community Insights

Real implementation experiences shared by AI practitioners.

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Related Tools

Ollama
Local model runner with simple command and HTTP interface.
vLLM
High-throughput LLM inference engine with PagedAttention.
LM Studio
Desktop app for running local LLMs with a chat interface.

Alternatives

vLLM
High-throughput LLM inference engine with PagedAttention.
TensorRT-LLM
NVIDIA library for optimized LLM inference on TensorRT.

Tags

#inference#serving#structured-outputs

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