head to head · open source

vllm vs Agenta

vllm has 92,202 GitHub stars, 22,428 forks, 7,953 open issues and last shipped today. Agenta has 4,766 stars, 674 forks, 309 open issues and last shipped today. vllm leads on adoption by 1,835% (92,202 vs 4,766 stars). vllm is written in Python under Apache-2.0; Agenta is written in TypeScript under a custom or non-standard licence. vllm has attracted 24% as many forks as stars, Agenta 14%. 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 Agenta ★ 4.8K category AI & Machine Learning

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Side by side

vllm Agenta
GitHub stars ★ 92K ★ 4.8K
License Apache-2.0 Custom / other
Written in Python TypeScript
Last push 2026-09-20 2026-09-20
Forks ⑂ 22K ⑂ 674
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 Agenta if

  • You want the Agenta feature set and don't need the biggest community
  • You prefer the Custom / other license terms
  • Your stack matches TypeScript
  • You evaluated both and Agenta fits your workflow better

full Agenta 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 Agenta

Agenta is an open source workspace where a team builds, runs, and improves AI agents by chatting with them, intended for individuals and teams that want agent automation without moving every task onto metered API billing.

read the full Agenta overview →

More in AI & Machine Learning

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

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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 Agenta more popular?

vllm has 92,202 GitHub stars and Agenta has 4,766. vllm has the larger community by that measure.

Are vllm and Agenta free?

Both are open source. vllm is licensed under Apache-2.0, and Agenta has no licence declared in this registry. Both are free to self-host.

What is the difference between vllm and Agenta?

vllm is written in Python and Agenta 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 Agenta?

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