head to head · open source

vllm vs rag_api

vllm has 92,055 GitHub stars, 22,349 forks, 7,953 open issues and last shipped today. rag_api has 901 stars, 403 forks, 45 open issues and last shipped 1 months ago. vllm leads on adoption by 10,117% (92,055 vs 901 stars). vllm is written in Python under Apache-2.0; rag_api is written in Python under MIT. vllm has attracted 24% as many forks as stars, rag_api 45%. vllm 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.

vllm ★ 92K rag_api ★ 901 category AI & Machine Learning

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Side by side

	vllm	rag_api
GitHub stars	★ 92K	★ 901
License	Apache-2.0	MIT
Written in	Python	Python
Last push	2026-09-18	2026-08-15
Forks	⑂ 22K	⑂ 403
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 rag_api if

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

full rag_api 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 rag_api

ID based RAG FastAPI Overview This project integrates Langchain with FastAPI in an Asynchronous, Scalable manner, providing a framework for document indexing and retrieval, using PostgreSQL/pgvector. Files are organized into embeddings by file id . The primary use case is for integration with LibreChat, but this simple API can be used for any ID based use case. The main reason to use the ID approach is to work with embeddings on a file level. This makes for targeted queries when combined with file metadata stored in a database, such as is done by LibreChat. The API will evolve over time to employ different queryi…

read the full rag_api overview →

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

Frequently asked questions

Is vllm or rag_api more popular?

vllm has 92,055 GitHub stars and rag_api has 901. vllm has the larger community by that measure.

Are vllm and rag_api free?

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

What is the difference between vllm and rag_api?

vllm is written in Python and rag_api 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 rag_api?

Choose vllm if you want the larger community (92,055 stars) or its Apache-2.0 licence terms. Choose rag_api if its feature set, stack or MIT licence fits better. Both are self-hostable.