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SGLang

High-performance serving framework for LLMs with RadixAttention

★ 30,000 GitHub Apache-2.0 sglang LLM & Chat

Überblick

High-performance serving framework for LLMs with RadixAttention

Anforderungen

Min vCPU
1
Min RAM
1024 MB
Min Disk
10 GB
Rec vCPU
2
Rec RAM
2048 MB
Rec Disk
20 GB

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2 vCPU · 4096 MB · 40 GB

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2 vCPU · 4096 MB · 40 GB

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Docker Compose

# Generated by Run This Ai — docker-compose.yml
services:
  sglang:
    image: lmsysorg/sglang:latest
    restart: unless-stopped
    ports:
      - 8080:8080
    volumes:
      - ./data/sglang:/data

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SGLang: install

SGLang

High-performance serving framework for LLMs with RadixAttention

Prerequisites

  • Docker installed (version 24.0+)
  • Docker Compose (version 2.20+)
  • At least 1GB RAM (2GB recommended)

Quick start with Docker

# Pull the image
docker pull lmsysorg/sglang:latest

# Run the container
docker run -d --name sglang -p 8080:8080 lmsysorg/sglang:latest

Key features

SGLang: overview

SGLang

High-performance serving framework for LLMs with RadixAttention

Key features

What it's good for

SGLang runs entirely on your own infrastructure — your data never leaves your server.

Verwandte Tools

Ollama

Run large language models locally

Open WebUI

User-friendly WebUI for LLMs (Ollama, OpenAI API)

llama.cpp

LLM inference in C/C++

Jan

Open-source ChatGPT replacement — run LLMs locally with full control and privacy

Llamafile

Distribute and run LLMs as single-file executables — no installation needed

LocalAI

Open-source AI engine — run any model (LLM, vision, voice, image, video) on any hardware, no GPU required