SHSelfHostIndex

MLX LM vs SGLang

A side-by-side comparison of two self-hosted self-hosted ai options — licensing, setup difficulty, resource needs, and what each one replaces.

Not the right match-up?
ML MLX LM Run and fine-tune LLMs locally on Apple Silicon with MLX VS SG SGLang Fast serving framework for LLMs and vision-language models
FeatureMLX LMSGLang
Deploy effortRead-the-docs projectUnder-an-hour setup
Health score89 · Excellent99 · Excellent
CategorySelf-Hosted AISelf-Hosted AI
LicenseMITApache-2.0
LanguagePythonPython
Setup difficultyMediumHard
Min. RAM16,384 MB16,384 MB
Deploymentsource, binarydocker, kubernetes, bare-metal
GitHub stars★ 7,117★ 36,383
First released20242024
ReplacesOpenAI APIOpenAI API

What are MLX LM and SGLang?

MLX LM

MLX LM is a Python package from Apple's MLX project for running and fine-tuning large language models efficiently on Apple Silicon. It provides a command-line interface and HTTP server for local text generation entirely on-device.

  • Native Apple Silicon inference
  • LoRA fine-tuning
  • OpenAI-compatible server
  • Model quantization

SGLang

SGLang is a high-performance serving framework for large language and vision-language models. It features a fast runtime with RadixAttention and a flexible programming language for complex LLM applications.

  • RadixAttention caching
  • Structured generation
  • OpenAI-compatible server
  • Multi-GPU scaling

Read the full SGLang guide →

MLX LM vs SGLang: key differences

Both projects are written in Python. Licensing differs — MIT for MLX LM versus Apache-2.0 for SGLang. SGLang has the considerably larger community, at 36,383 GitHub stars versus 7,117. SGLang lists first-class Docker deployment; MLX LM does not.

Why pick each one

Choose MLX LM if…

  • Released under the MIT license
  • Mature project with 7.1k GitHub stars
  • Written in Python
MLX LM details

Choose SGLang if…

  • Very high throughput
  • RadixAttention prefix caching
  • Vision model support

Watch out for

  • Serious GPU required
  • Complex tuning options
SGLang details

Frequently asked questions

Is MLX LM or SGLang better?

Neither is universally better. SGLang has the larger community, while MLX LM is simpler to set up (medium difficulty). Choose based on the comparison table above and your own setup.

Are MLX LM and SGLang free and open-source?

Yes. MLX LM is licensed under MIT and SGLang under Apache-2.0. Both can be self-hosted at no software cost.

Can I run MLX LM and SGLang with Docker?

MLX LM: check the project docs for container support. SGLang: yes.

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