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LMDeploy vs MLC LLM

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

Not the right match-up?
LM LMDeploy Toolkit for compressing and serving large language models VS ML MLC LLM Universal LLM deployment engine for any hardware
FeatureLMDeployMLC LLM
Deploy effortUnder-an-hour setupRead-the-docs project
Health score92 · Excellent95 · Excellent
CategoryLocal LLM RunnersLocal LLM Runners
LicenseApache-2.0Apache-2.0
LanguagePythonPython
Setup difficultyHardHard
Min. RAM16,384 MB4,096 MB
Deploymentdocker, sourcesource, binary
GitHub stars★ 8,097★ 23,185
First released20232023
ReplacesOpenAI API, Hugging Face Inference EndpointsOpenAI API

What are LMDeploy and MLC LLM?

LMDeploy

LMDeploy is an inference and serving toolkit from the OpenMMLab ecosystem for deploying large language models efficiently. It offers quantization, a high-throughput serving engine, and an OpenAI-compatible API.

  • High-throughput inference engine
  • Weight quantization support
  • OpenAI-compatible serving
  • Multi-GPU deployment

MLC LLM

MLC LLM is a machine learning compiler and runtime that deploys language models natively across GPUs, CPUs, browsers, and mobile devices. It enables high-performance self-hosted inference on diverse hardware.

  • Compile models for any hardware
  • Native GPU acceleration
  • Browser and mobile runtimes
  • OpenAI-compatible serving

Read the full MLC LLM guide →

LMDeploy vs MLC LLM: key differences

Both projects are written in Python. MLC LLM is the lighter option, starting around 4,096 MB of RAM against 16,384 MB for LMDeploy. MLC LLM has the considerably larger community, at 23,185 GitHub stars versus 8,097. LMDeploy lists first-class Docker deployment; MLC LLM does not.

Why pick each one

Choose LMDeploy if…

  • Released under the Apache-2.0 license
  • First-class Docker support for quick deployment
  • Mature project with 8.1k GitHub stars
  • Written in Python
LMDeploy details

Choose MLC LLM if…

  • Runs on diverse hardware
  • Mobile and browser deployment
  • Strong inference performance

Watch out for

  • Models need compilation
  • Complex toolchain setup
MLC LLM details

Frequently asked questions

Is LMDeploy or MLC LLM better?

Neither is universally better. MLC LLM has the larger community; both share a hard setup difficulty, so the decision comes down to features and licensing.

Are LMDeploy and MLC LLM free and open-source?

Yes. LMDeploy is licensed under Apache-2.0 and MLC LLM under Apache-2.0. Both can be self-hosted at no software cost.

Can I run LMDeploy and MLC LLM with Docker?

LMDeploy: yes. MLC LLM: check the project docs for container support.

Which is lighter on resources, LMDeploy or MLC LLM?

MLC LLM has the smaller minimum footprint at 4,096 MB of RAM, compared to about 16,384 MB for LMDeploy. Real-world usage depends on library size, user count, and enabled features.

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