ExLlama vs Llama Stack
A side-by-side comparison of two self-hosted self-hosted ai options — licensing, setup difficulty, resource needs, and what each one replaces.
| Feature | ExLlama | Llama Stack |
|---|---|---|
| Deploy effort | Read-the-docs project | Under-an-hour setup |
| Health score | 23 · At risk | 92 · Excellent |
| Category | Self-Hosted AI | Self-Hosted AI |
| License | MIT | MIT |
| Language | Python | Python |
| Setup difficulty | Hard | Medium |
| Min. RAM | 8,192 MB | 4,096 MB |
| Deployment | source | docker, source |
| GitHub stars | ★ 2,946 | ★ 8,437 |
| First released | 2023 | 2024 |
| Replaces | OpenAI API | OpenAI API |
What are ExLlama and Llama Stack?
ExLlama
ExLlama is a standalone Python/C++/CUDA implementation for running quantized GPTQ Llama models with low VRAM use on modern GPUs. It is the predecessor to ExLlamaV2 and focuses on fast, memory-efficient local inference.
- Low VRAM GPTQ inference
- CUDA-accelerated
- Standalone library
- Fast token generation
Llama Stack
Llama Stack from Meta defines and implements a set of standardized APIs for inference, RAG, agents, safety and evaluation, with multiple provider backends. It can be self-hosted as a unified server for building local generative AI applications.
- Standardized AI APIs
- Pluggable provider backends
- Agents and RAG support
- Self-hostable server
ExLlama vs Llama Stack: key differences
Both projects are written in Python. Llama Stack is the lighter option, starting around 4,096 MB of RAM against 8,192 MB for ExLlama. Llama Stack has the considerably larger community, at 8,437 GitHub stars versus 2,946. Llama Stack lists first-class Docker deployment; ExLlama does not.
Why pick each one
Choose ExLlama if…
- Released under the MIT license
- Active community (2.9k GitHub stars)
- Written in Python
Choose Llama Stack if…
- Released under the MIT license
- First-class Docker support for quick deployment
- Mature project with 8.4k GitHub stars
- Written in Python
Frequently asked questions
Is ExLlama or Llama Stack better?
Llama Stack is the stronger all-round pick: it has both the larger community and the simpler medium setup. Consider ExLlama if its specific feature set fits your needs better.
Are ExLlama and Llama Stack free and open-source?
Yes. ExLlama is licensed under MIT and Llama Stack under MIT. Both can be self-hosted at no software cost.
Can I run ExLlama and Llama Stack with Docker?
ExLlama: check the project docs for container support. Llama Stack: yes.
Which is lighter on resources, ExLlama or Llama Stack?
Llama Stack has the smaller minimum footprint at 4,096 MB of RAM, compared to about 8,192 MB for ExLlama. Real-world usage depends on library size, user count, and enabled features.