SGLang
A serving framework for running large language models and multimodal models on your own GPUs.
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About SGLang
SGLang is a serving framework for large language models and multimodal models. You run it on your own hardware with GPUs, and it serves the model to other programs and users. It is aimed at people who host models themselves and care about throughput.
The repository includes Docker files, benchmark scripts, examples and a model gateway component for routing requests. Setup and tuning assume familiarity with GPU servers and Python tooling, so it suits developers and operators more than casual desktop users.
Strengths
- Built for high-throughput model serving
- Handles both language and multimodal models
- Docker files and benchmark tooling included
- Large and very active project
Limitations
- Needs capable GPU hardware
- Aimed at servers and developers rather than desktop chat use
Details
- Pricing
- FreeFree to download and run from its public repository.
- License
- Open source, license not stated
- Developer
- The SGLang contributors
- Platforms
- Self-hosted, Command line
- How it runs
- Downloadable app, Self-hosted
- Account
- Not required
- Best suited for
- Developers and teams serving language models on their own GPU servers
- Categories
- Local AI tools, Developer tools
- Last verified
- Added
- Provenance
- Facts checked against the developer's own pages and store listings, 1 sources on file.
Alternatives to SGLang
Compare allSoftware that can replace SGLang for an important use case, and what changes if you switch.
vLLM
High-throughput, memory-efficient inference and serving engine for LLMs.
vLLM is an Apache-2.0 high-throughput, memory-efficient serving engine for Linux, aimed at developers deploying models on appropriate GPU hardware, much like SGLang.
Xinference
An open-source inference server for running language, speech and multimodal models through one API.
Xinference serves language, speech and multimodal models behind one GPT-compatible API, and runs on a laptop or scales to servers on macOS and Linux.
LocalAI
Serve language, image and speech models on your own hardware.
LocalAI is MIT-licensed and serves language, image and speech models with compatible APIs for common AI services, rather than focusing on high-throughput GPU serving.
TabbyAPI
A lightweight, OpenAI-compatible API server for running ExLlama-format language models on your own hardware.
TabbyAPI is a lightweight OpenAI-compatible server that only serves ExLlama-format models, trading SGLang's broad model support for a smaller footprint.
llama.cpp
The C++ engine most local AI apps are built on, running language models on ordinary hardware.
llama.cpp runs quantised models as a single binary with CPU and GPU hybrid inference and a built-in server, suiting ordinary hardware rather than GPU server fleets.
Ollama
The simplest way to pull down an open language model and run it on your own machine, from one command or a desktop app.
Ollama downloads and runs models with one command and serves a localhost REST API, targeting single machines on Windows, macOS and Linux rather than GPU servers.
SGLang as an alternative
Listings that name SGLang as an alternative.
GPUStack
An open-source GPU cluster manager for serving AI models with vLLM and SGLang on your own hardware.
SGLang is an open-source high-throughput serving framework for language and multimodal models, used directly rather than through GPUStack's cluster manager.
Similar software
Related functionality, not necessarily a direct replacement.
nvitop
Interactive terminal viewer for NVIDIA GPUs and the processes running on them.
Open WebUI
A self-hosted chat interface that talks to Ollama and any OpenAI-compatible API, so your local models get a proper front end.
LlamaFactory
Web UI and command-line toolkit for fine-tuning over 100 open language and vision-language models.
