head to head · open source

vllm vs kitops

vllm has 92,028 GitHub stars, 22,335 forks, 7,953 open issues and last shipped yesterday. kitops has 1,416 stars, 185 forks, 50 open issues and last shipped 2 days ago. vllm leads on adoption by 6,399% (92,028 vs 1,416 stars). vllm is written in Python under Apache-2.0; kitops is written in Go under Apache-2.0. vllm has attracted 24% as many forks as stars, kitops 13%. 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 kitops ★ 1.4K category AI & Machine Learning

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Side by side

vllm kitops
GitHub stars ★ 92K ★ 1.4K
License Apache-2.0 Apache-2.0
Written in Python Go
Last push 2026-09-17 2026-09-16
Forks ⑂ 22K ⑂ 185
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 kitops if

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

full kitops 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 kitops

KitOps is an open source DevOps tool governed by the CNCF for packaging, versioning, and securely sharing AI/ML projects. It lives in the Kubernetes AI/ML and MLOps ecosystem, and it builds on the OCI technology used by containers. A KitOps package, called a ModelKit, bundles model weights, datasets, code, and configuration into a versioned, layered artifact that can be stored in an existing container registry.

read the full kitops 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 kitops more popular?

vllm has 92,028 GitHub stars and kitops has 1,416. vllm has the larger community by that measure.

Are vllm and kitops free?

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

What is the difference between vllm and kitops?

vllm is written in Python and kitops in Go. 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 kitops?

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