llama.cpp 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.
llama.cpp
High-performance LLM inference in plain C/C++
VS
Wllama
Run LLM inference directly in the browser with WebAssembly
| Feature | llama.cpp | Wllama |
|---|---|---|
| Deploy effort | Under-an-hour setup | Read-the-docs project |
| Health score | 100 · Excellent | 84 · Excellent |
| Category | Local LLM Runners | Local LLM Runners |
| License | MIT | MIT |
| Language | C++ | TypeScript |
| Setup difficulty | Hard | Medium |
| Min. RAM | 8,192 MB | 512 MB |
| Deployment | binary, bare-metal, docker | source |
| GitHub stars | ★ 129,361 | ★ 1,309 |
| First released | 2023 | 2024 |
| Replaces | OpenAI API | OpenAI API |
What are llama.cpp and Wllama?
llama.cpp
llama.cpp is a C/C++ inference engine for running LLaMA-family and many other models efficiently on CPUs and GPUs. It pioneered the GGUF quantized model format and powers a large portion of the local-AI ecosystem.
- GGUF quantization
- Runs on modest hardware
- Built-in HTTP server
- Broad GPU backend support
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
llama.cpp vs Wllama: key differences
Llama.cpp is written in C++, while Wllama is built with TypeScript. Wllama is the lighter option, starting around 512 MB of RAM against 8,192 MB for llama.cpp. Llama.cpp has the considerably larger community, at 129,361 GitHub stars versus 1,309. Llama.cpp lists first-class Docker deployment; Wllama does not.
Why pick each one
Choose llama.cpp if…
- Runs on modest CPUs
- Broad hardware support
- Pioneered GGUF quantization
Watch out for
- Command-line focused
- Frequent breaking changes
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 llama.cpp or Wllama better?
Neither is universally better. llama.cpp 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 llama.cpp and Wllama free and open-source?
Yes. llama.cpp is licensed under MIT and Wllama under MIT. Both can be self-hosted at no software cost.
Can I run llama.cpp and Wllama with Docker?
llama.cpp: yes. Wllama: check the project docs for container support.
Which is lighter on resources, llama.cpp or Wllama?
Wllama has the smaller minimum footprint at 512 MB of RAM, compared to about 8,192 MB for llama.cpp. Real-world usage depends on library size, user count, and enabled features.