LMDeploy vs Ollama
A side-by-side comparison of two self-hosted local llm runners options — licensing, setup difficulty, resource needs, and what each one replaces.
Ollama
Run large language models locally with a simple CLI and API
| Feature | LMDeploy | Ollama |
|---|---|---|
| Deploy effort | Under-an-hour setup | ≈5-minute setup |
| Health score | 92 · Excellent | 100 · Excellent |
| Category | Local LLM Runners | Local LLM Runners |
| License | Apache-2.0 | MIT |
| Language | Python | Go |
| Setup difficulty | Hard | Easy |
| Min. RAM | 16,384 MB | 8,192 MB |
| Deployment | docker, source | docker, binary, bare-metal |
| GitHub stars | ★ 8,097 | ★ 181,557 |
| First released | 2023 | 2023 |
| Replaces | OpenAI API, Hugging Face Inference Endpoints | ChatGPT, OpenAI API |
What are LMDeploy and Ollama?
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
Ollama
Ollama lets you download, run, and manage open large language models such as Llama, Mistral, Gemma, and Qwen on your own machine. It provides a simple command line interface and a built-in REST API so other tools can use local models.
- One-command model downloads
- OpenAI-compatible API
- GPU and CPU support
- Modelfile customization
LMDeploy vs Ollama: key differences
LMDeploy is written in Python, while Ollama is built with Go. Licensing differs — Apache-2.0 for LMDeploy versus MIT for Ollama. Ollama is the lighter option, starting around 8,192 MB of RAM against 16,384 MB for LMDeploy. Ollama has the considerably larger community, at 181,557 GitHub stars versus 8,097.
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 Ollama if…
- Extremely easy to set up
- Large model library
Watch out for
- Limited fine-grained inference tuning
Frequently asked questions
Is LMDeploy or Ollama better?
Ollama is the stronger all-round pick: it has both the larger community and the simpler easy setup. Consider LMDeploy if its specific feature set fits your needs better.
Are LMDeploy and Ollama free and open-source?
Yes. LMDeploy is licensed under Apache-2.0 and Ollama under MIT. Both can be self-hosted at no software cost.
Can I run LMDeploy and Ollama with Docker?
LMDeploy: yes. Ollama: yes.
Which is lighter on resources, LMDeploy or Ollama?
Ollama has the smaller minimum footprint at 8,192 MB of RAM, compared to about 16,384 MB for LMDeploy. Real-world usage depends on library size, user count, and enabled features.