head to head · open source

vllm vs unbody

vllm has 92,055 GitHub stars, 22,349 forks, 7,953 open issues and last shipped yesterday. unbody has 524 stars, 47 forks, 3 open issues and last shipped 5 months ago. vllm leads on adoption by 17,468% (92,055 vs 524 stars). vllm is written in Python under Apache-2.0; unbody is written in TypeScript under Apache-2.0. vllm has attracted 24% as many forks as stars, unbody 9%. 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 unbody ★ 524 category AI & Machine Learning

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Side by side

vllm unbody
GitHub stars ★ 92K ★ 524
License Apache-2.0 Apache-2.0
Written in Python TypeScript
Last push 2026-09-18 2026-04-14
Forks ⑂ 22K ⑂ 47
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 unbody if

  • You want the unbody feature set and don't need the biggest community
  • You prefer the Apache-2.0 license terms
  • Your stack matches TypeScript
  • You evaluated both and unbody fits your workflow better

full unbody 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 unbody

Unbody is an Apache 2.0, TypeScript, modular open source backend for building AI native software that is designed for knowledge rather than static data, and it is aimed at developers and teams that want to self host the ingestion, indexing and retrieval layer behind chat, search and agentic applications.

read the full unbody overview →

More in AI & Machine Learning

OpenClaw ★ 390K Hermes Agent ★ 247K Ollama ★ 181K Dify ★ 156K Open WebUI ★ 152K langchain ★ 147K

Related comparisons

ollama vs vllm llama-cpp vs vllm openclaw vs ollama ollama vs llama-cpp ollama vs gpt4all ollama vs llama-index ollama vs localai open-webui vs gpt4all openclaw vs hermes-agent openclaw vs opencode openclaw vs n8n openclaw vs open-webui openclaw vs lobechat openclaw vs anythingllm hermes-agent vs opencode hermes-agent vs n8n openclaw vs dify openclaw vs multica openclaw vs langgraph n8n vs dify dify vs langflow dify vs open-webui dify vs langchain dify vs ponytail

More Machine Learning Infrastructure projects

Compare either of these against the rest of the Machine Learning Infrastructure field.

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

Frequently asked questions

Is vllm or unbody more popular?

vllm has 92,055 GitHub stars and unbody has 524. vllm has the larger community by that measure.

Are vllm and unbody free?

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

What is the difference between vllm and unbody?

vllm is written in Python and unbody in TypeScript. 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 unbody?

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