# JupyterLab vs llama.cpp

> Two self-hosted projects, compared on the numbers selfhost.directory tracks live: score, popularity, release cadence and setup effort.

| | JupyterLab | llama.cpp |
|---|---|---|
| Score | 78/100 | 93/100 ✓ |
| Rank in category | #1 of 3 in Data Science | #2 of 25 in LLM Inference |
| GitHub stars | 15 379 | 132 699 ✓ |
| Stars, last 30 days | +59 | +3 244 ✓ |
| Stable releases, 12 months | 12 | 1467 ✓ |
| Latest release | v4.7.0b0 · 28 Oct 2026 | b11981 · 29 Oct 2026 |
| Setup | Easy ✓ | Moderate |
| Official Docker image | No | Yes ✓ |
| License | BSD-3-Clause | MIT |
| Main language | Typescript | C++ |

## Which one should you pick?

llama.cpp scores 93/100 against 78/100 for JupyterLab, so it is the safer default.

llama.cpp ships more often: 1467 stable releases in the past year, against 12 for JupyterLab.

If you want the quickest setup, JupyterLab is easier to run; llama.cpp needs more configuration.

llama.cpp is growing faster right now (+3 244 stars in 30 days).

## Details

- [JupyterLab](https://selfhost.directory/project/jupyterlab) (markdown: https://selfhost.directory/project/jupyterlab.md)
- [llama.cpp](https://selfhost.directory/project/llamacpp) (markdown: https://selfhost.directory/project/llamacpp.md)

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Source: https://selfhost.directory/compare/jupyterlab-vs-llamacpp