head to head · open source
llama_index vs vllm-omni
llama_index has 52,202 GitHub stars, 8,162 forks, 770 open issues and last shipped yesterday. vllm-omni has 6,855 stars, 1,747 forks, 1,977 open issues and last shipped yesterday. llama_index leads on adoption by 662% (52,202 vs 6,855 stars). llama_index is written in Python under MIT; vllm-omni is written in Python under Apache-2.0. llama_index has attracted 16% as many forks as stars, vllm-omni 25%. llama_index was the more recently maintained of the two, and both are self-hostable with no licence fee.
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 | vllm-omni | |
|---|---|---|
| GitHub stars | ★ 52K | ★ 6.9K |
| License | MIT | Apache-2.0 |
| Written in | Python | Python |
| Last push | 2026-09-17 | 2026-09-17 |
| Forks | ⑂ 8.2K | ⑂ 1.7K |
| 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 vllm-omni if
- You want the vllm-omni feature set and don't need the biggest community
- You prefer the Apache-2.0 license terms
- Your stack matches Python
- You evaluated both and vllm-omni 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 vllm-omni
vLLM Omni is an Apache 2.0 Python framework from the vLLM project that extends vLLM's text only inference engine to serve omni modality models — text, image, audio, video, and action — for teams that need to run diffusion transformers, autoregressive models, and realtime duplex pipelines from a single serving stack.
read the full vllm-omni overview →
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Frequently asked questions
Is llama_index or vllm-omni more popular?
llama_index has 52,202 GitHub stars and vllm-omni has 6,855. llama_index has the larger community by that measure.
Are llama_index and vllm-omni free?
Both are open source. llama_index is licensed under MIT and vllm-omni under Apache-2.0. Neither carries a licence fee.
What is the difference between llama_index and vllm-omni?
llama_index is written in Python and vllm-omni 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 vllm-omni?
Choose llama_index if you want the larger community (52,202 stars) or its MIT licence terms. Choose vllm-omni if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.