LMDeploy vs Wllama
A side-by-side comparison of two self-hosted local llm runners options — licensing, setup difficulty, resource needs, and what each one replaces.
| Feature | LMDeploy | Wllama |
|---|---|---|
| Deploy effort | Under-an-hour setup | Read-the-docs project |
| Health score | 92 · Excellent | 84 · Excellent |
| Category | Local LLM Runners | Local LLM Runners |
| License | Apache-2.0 | MIT |
| Language | Python | TypeScript |
| Setup difficulty | Hard | Medium |
| Min. RAM | 16,384 MB | 512 MB |
| Deployment | docker, source | source |
| GitHub stars | ★ 8,097 | ★ 1,309 |
| First released | 2023 | 2024 |
| Replaces | OpenAI API, Hugging Face Inference Endpoints | OpenAI API |
What are LMDeploy and Wllama?
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
Wllama
Wllama is an open-source WebAssembly binding for llama.cpp that allows large language models to run entirely inside the browser. It can be hosted as a static site to provide fully client-side AI inference.
- Browser-based inference
- WebAssembly powered
- No server needed
- Static site deployable
LMDeploy vs Wllama: key differences
LMDeploy is written in Python, while Wllama is built with TypeScript. Licensing differs — Apache-2.0 for LMDeploy versus MIT for Wllama. Wllama is the lighter option, starting around 512 MB of RAM against 16,384 MB for LMDeploy. LMDeploy has the considerably larger community, at 8,097 GitHub stars versus 1,309. LMDeploy lists first-class Docker deployment; Wllama 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
Choose Wllama if…
- Released under the MIT license
- Active community (1.3k GitHub stars)
- Written in TypeScript
- Lightweight — runs in 512 MB RAM
Frequently asked questions
Is LMDeploy or Wllama better?
Neither is universally better. LMDeploy has the larger community, while Wllama is simpler to set up (medium difficulty). Choose based on the comparison table above and your own setup.
Are LMDeploy and Wllama free and open-source?
Yes. LMDeploy is licensed under Apache-2.0 and Wllama under MIT. Both can be self-hosted at no software cost.
Can I run LMDeploy and Wllama with Docker?
LMDeploy: yes. Wllama: check the project docs for container support.
Which is lighter on resources, LMDeploy or Wllama?
Wllama has the smaller minimum footprint at 512 MB of RAM, compared to about 16,384 MB for LMDeploy. Real-world usage depends on library size, user count, and enabled features.