head to head · open source

vllm vs llama_index

vllm has 92,028 GitHub stars, 22,335 forks, 7,953 open issues and last shipped yesterday. llama_index has 52,202 stars, 8,162 forks, 770 open issues and last shipped yesterday. vllm leads on adoption by 76% (92,028 vs 52,202 stars). vllm is written in Python under Apache-2.0; llama_index is written in Python under MIT. vllm has attracted 24% as many forks as stars, llama_index 16%. vllm was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 1 topic tag (llm), 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.

vllm ★ 92K llama_index ★ 52K category AI & Machine Learning

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Side by side

	vllm	llama_index
GitHub stars	★ 92K	★ 52K
License	Apache-2.0	MIT
Written in	Python	Python
Last push	2026-09-17	2026-09-17
Forks	⑂ 22K	⑂ 8.2K
Self-hosting	Yes	Yes
Data ownership	Your server	Your server

pick vllm if

You weight community size — 92K stars and counting
You want the Apache-2.0 license terms
Your stack matches Python
You value the larger contributor base for long-term maintenance

full vllm profile →

pick llama_index if

You want the llama_index feature set and don't need the biggest community
You prefer the MIT license terms
Your stack matches Python
You evaluated both and llama_index fits your workflow better

full llama_index profile →

About vllm

vLLM is a high throughput, memory efficient Python library for LLM inference and serving, built for ML engineers and platform teams who need to run open weight models on their own hardware at production scale.

read the full vllm overview →

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 →

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vllm vs Ollama vllm vs llama.cpp vllm vs GPT4All vllm vs LocalAI vllm vs PageIndex vllm vs Langfuse vllm vs cognee vllm vs taipy vllm vs dagster vllm vs zvec vllm vs langchain4j vllm vs txtai

Frequently asked questions

Is vllm or llama_index more popular?

vllm has 92,028 GitHub stars and llama_index has 52,202. vllm has the larger community by that measure.

Are vllm and llama_index free?

Both are open source. vllm is licensed under Apache-2.0 and llama_index under MIT. Neither carries a licence fee.

What is the difference between vllm and llama_index?

vllm is written in Python and llama_index 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, vllm or llama_index?

Choose vllm if you want the larger community (92,028 stars) or its Apache-2.0 licence terms. Choose llama_index if its feature set, stack or MIT licence fits better. Both are self-hostable.