head to head · open source

vllm vs InferenceX

vllm has 92,028 GitHub stars, 22,335 forks, 7,953 open issues and last shipped yesterday. InferenceX has 1,718 stars, 299 forks, 254 open issues and last shipped yesterday. vllm leads on adoption by 5,257% (92,028 vs 1,718 stars). vllm is written in Python under Apache-2.0; InferenceX is written in Python under Apache-2.0. vllm has attracted 24% as many forks as stars, InferenceX 17%. vllm was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 6 topic tags (amd, cuda, deepseek, inference), 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 InferenceX ★ 1.7K category AI & Machine Learning

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Side by side

vllm InferenceX
GitHub stars ★ 92K ★ 1.7K
License Apache-2.0 Apache-2.0
Written in Python Python
Last push 2026-09-17 2026-09-17
Forks ⑂ 22K ⑂ 299
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 InferenceX if

  • You want the InferenceX 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 InferenceX fits your workflow better

full InferenceX 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 InferenceX

InferenceX is an open source continuous inference benchmark research platform written in Python under the Apache 2.0 license. It lives in the machine learning infrastructure ecosystem, where teams evaluate large language model serving frameworks and accelerator systems. Formerly named InferenceMAX, the project maintains a public dashboard and a benchmark repository that track performance as inference software and hardware change.

read the full InferenceX overview →

More in AI & Machine Learning

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

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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 InferenceX more popular?

vllm has 92,028 GitHub stars and InferenceX has 1,718. vllm has the larger community by that measure.

Are vllm and InferenceX free?

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

What is the difference between vllm and InferenceX?

vllm is written in Python and InferenceX 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 InferenceX?

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