head to head · open source
llama_index vs dstack
llama_index has 52,202 GitHub stars, 8,162 forks, 770 open issues and last shipped yesterday. dstack has 2,252 stars, 262 forks, 68 open issues and last shipped yesterday. llama_index leads on adoption by 2,218% (52,202 vs 2,252 stars). llama_index is written in Python under MIT; dstack is written in Python under MPL-2.0. llama_index has attracted 16% as many forks as stars, dstack 12%. llama_index was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 1 topic tag (fine-tuning), so they are genuine substitutes rather than adjacent tools.
Two open source projects, one decision. Both are free and self-hostable — the differences are community size, license terms, language stack and release pace.
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Side by side
| llama_index | dstack | |
|---|---|---|
| GitHub stars | ★ 52K | ★ 2.3K |
| License | MIT | MPL-2.0 |
| Written in | Python | Python |
| Last push | 2026-09-17 | 2026-09-17 |
| Forks | ⑂ 8.2K | ⑂ 262 |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick llama_index if
- You weight community size — 52K stars and counting
- You want the MIT license terms
- Your stack matches Python
- You value the larger contributor base for long-term maintenance
pick dstack if
- You want the dstack feature set and don't need the biggest community
- You prefer the MPL-2.0 license terms
- Your stack matches Python
- You evaluated both and dstack fits your workflow better
About llama_index
LlamaIndex is an MIT licensed, open source Python framework for building agentic applications — retrieval augmented generation systems, agents and multi agent workflows — on top of private documents and data, and it is aimed at AI engineers and teams who need to connect large language models to their own sources of context.
read the full llama_index overview →
About dstack
dstack is an open source Python project in the AI and machine learning infrastructure ecosystem. It is a unified control plane for GPU provisioning and orchestration that works with GPU clouds, Kubernetes, and on prem clusters. The project supports NVIDIA, AMD, Google TPU, and Tenstorrent accelerators, and it is compatible with open source tools and frameworks.
read the full dstack overview →
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Frequently asked questions
Is llama_index or dstack more popular?
llama_index has 52,202 GitHub stars and dstack has 2,252. llama_index has the larger community by that measure.
Are llama_index and dstack free?
Both are open source. llama_index is licensed under MIT and dstack under MPL-2.0. Neither carries a licence fee.
What is the difference between llama_index and dstack?
llama_index is written in Python and dstack in Python. The practical differences are community size, licence terms, language stack and release cadence — all compared in the table above.
Which should I choose, llama_index or dstack?
Choose llama_index if you want the larger community (52,202 stars) or its MIT licence terms. Choose dstack if its feature set, stack or MPL-2.0 licence fits better. Both are self-hostable.