head to head · open source
vllm vs txtai
vllm has 96,158 GitHub stars, 24,317 forks, 7,953 open issues and last shipped yesterday. txtai has 13,062 stars, 960 forks, 9 open issues and last shipped 2 days ago. vllm leads on adoption by 636% (96,158 vs 13,062 stars). vllm is written in Python under Apache-2.0; txtai is written in Python under Apache-2.0. vllm has attracted 25% as many forks as stars, txtai 7%. 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.
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Side by side
| vllm | txtai | |
|---|---|---|
| GitHub stars | ★ 96K | ★ 13K |
| License | Apache-2.0 | Apache-2.0 |
| Written in | Python | Python |
| Last push | 2026-11-02 | 2026-11-01 |
| Forks | ⑂ 24K | ⑂ 960 |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick vllm if
- You weight community size — 96K 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
pick txtai if
- You want the txtai 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 txtai fits your workflow better
About vllm
Easy, fast, and cheap LLM serving for everyone 🔥 We have built a vLLM website to help you get started with vLLM. Please visit vllm.ai to learn more. For events, please visit vllm.ai/events to join us. About vLLM is a fast and easy to use library for LLM inference and serving. Originally developed in the Sky Computing Lab at UC Berkeley, vLLM has grown into one of the most active open source AI projects built and maintained by a diverse community of many dozens of academic institutions and companies from over 2000 contributors. vLLM is fast with: State of the art serving throughput Efficient management of…
About txtai
All in one AI framework txtai is an all in one AI framework for semantic search, LLM orchestration and language model workflows. The key component of txtai is an embeddings database, which is a union of vector indexes (sparse and dense), graph networks and relational databases. This foundation enables vector search and/or serves as a powerful knowledge source for large language model (LLM) applications. Build autonomous agents, retrieval augmented generation (RAG) processes, multi model workflows and more. Summary of txtai features: 🔎 Vector search with SQL, object storage, topic modeling, graph analysis and…
read the full txtai overview →
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Frequently asked questions
Is vllm or txtai more popular?
vllm has 96,158 GitHub stars and txtai has 13,062. vllm has the larger community by that measure.
Are vllm and txtai free?
Both are open source. vllm is licensed under Apache-2.0 and txtai under Apache-2.0. Neither carries a licence fee.
What is the difference between vllm and txtai?
vllm is written in Python and txtai 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 txtai?
Choose vllm if you want the larger community (96,158 stars) or its Apache-2.0 licence terms. Choose txtai if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.