head to head · open source

vllm vs Helicone

vllm has 92,202 GitHub stars, 22,428 forks, 7,953 open issues and last shipped today. Helicone has 6,165 stars, 672 forks, 156 open issues and last shipped 4 days ago. vllm leads on adoption by 1,396% (92,202 vs 6,165 stars). vllm is written in Python under Apache-2.0; Helicone is written in TypeScript under Apache-2.0. vllm has attracted 24% as many forks as stars, Helicone 11%. vllm was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 2 topic tags (gpt, 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 Helicone ★ 6.2K category AI & Machine Learning

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Side by side

vllm Helicone
GitHub stars ★ 92K ★ 6.2K
License Apache-2.0 Apache-2.0
Written in Python TypeScript
Last push 2026-09-20 2026-09-16
Forks ⑂ 22K ⑂ 672
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 Helicone if

  • You want the Helicone 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 Helicone fits your workflow better

full Helicone 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 Helicone

Helicone is an open source AI gateway and LLM observability platform for AI engineers who need to monitor, evaluate, and experiment with applications built on large language models.

read the full Helicone overview →

More in AI & Machine Learning

OpenClaw ★ 390K Hermes Agent ★ 247K Ollama ★ 181K Dify ★ 157K Open WebUI ★ 153K langchain ★ 147K

Related comparisons

ollama vs vllm openclaw vs ollama ollama vs llama-cpp ollama vs odysseus 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 comfyui openclaw vs odysseus openclaw vs lobechat openclaw vs anythingllm 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 Helicone more popular?

vllm has 92,202 GitHub stars and Helicone has 6,165. vllm has the larger community by that measure.

Are vllm and Helicone free?

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

What is the difference between vllm and Helicone?

vllm is written in Python and Helicone 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 Helicone?

Choose vllm if you want the larger community (92,202 stars) or its Apache-2.0 licence terms. Choose Helicone if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.