head to head · open source

vllm vs infinity

vllm has 92,028 GitHub stars, 22,335 forks, 7,953 open issues and last shipped yesterday. infinity has 4,708 stars, 445 forks, 126 open issues and last shipped 9 days ago. vllm leads on adoption by 1,855% (92,028 vs 4,708 stars). vllm is written in Python under Apache-2.0; infinity is written in C++ under Apache-2.0. vllm has attracted 24% as many forks as stars, infinity 9%. 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 infinity ★ 4.7K category AI & Machine Learning

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Side by side

vllm infinity
GitHub stars ★ 92K ★ 4.7K
License Apache-2.0 Apache-2.0
Written in Python C++
Last push 2026-09-17 2026-09-09
Forks ⑂ 22K ⑂ 445
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 infinity if

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

full infinity 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 infinity

Infinity is an Apache 2.0, C++ database in the AI and machine learning infrastructure ecosystem. It is an AI native database for large language model applications, including search, recommendation, question answering, conversational AI, copilot, content generation, and retrieval augmented generation. The project targets matching and ranking rich data types inside one system, rather than combining separate vector, text, and reranking components.

read the full infinity overview →

More in AI & Machine Learning

OpenClaw ★ 390K Hermes Agent ★ 246K Ollama ★ 181K Dify ★ 156K Open WebUI ★ 152K langchain ★ 147K

Related comparisons

ollama vs vllm llama-cpp vs vllm ollama vs llama-cpp ollama vs gpt4all ollama vs llama-index ollama vs localai ollama vs pageindex ollama vs langfuse openclaw vs hermes-agent openclaw vs open-webui openclaw vs lobechat openclaw vs anythingllm openclaw vs cherry-studio openclaw vs nanobot openclaw vs jan openclaw vs librechat dify vs langchain dify vs ponytail langchain vs ponytail dify vs graphify langchain vs graphify ponytail vs graphify dify vs claude-mem dify vs ragflow

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 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 infinity more popular?

vllm has 92,028 GitHub stars and infinity has 4,708. vllm has the larger community by that measure.

Are vllm and infinity free?

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

What is the difference between vllm and infinity?

vllm is written in Python and infinity in C++. 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 infinity?

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