head to head · open source

vllm vs claude-context

vllm has 92,202 GitHub stars, 22,428 forks, 7,953 open issues and last shipped today. claude-context has 12,548 stars, 926 forks, 146 open issues and last shipped 2 months ago. vllm leads on adoption by 635% (92,202 vs 12,548 stars). vllm is written in Python under Apache-2.0; claude-context is written in TypeScript under MIT. vllm has attracted 24% as many forks as stars, claude-context 7%. 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 claude-context ★ 13K category AI & Machine Learning

← all 20902 open source comparisons

Side by side

vllm claude-context
GitHub stars ★ 92K ★ 13K
License Apache-2.0 MIT
Written in Python TypeScript
Last push 2026-09-20 2026-07-14
Forks ⑂ 22K ⑂ 926
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 claude-context if

  • You want the claude-context feature set and don't need the biggest community
  • You prefer the MIT license terms
  • Your stack matches TypeScript
  • You evaluated both and claude-context fits your workflow better

full claude-context 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 claude-context

Claude Context is an open source Model Context Protocol (MCP) plugin that adds semantic code search to Claude Code and other AI coding agents. It is written in TypeScript, licensed under MIT, and published to npm as @zilliz/claude context core and @zilliz/claude context mcp . The project lives in the AI coding agent ecosystem, where it plugs into MCP compatible clients such as Claude Code, OpenAI Codex CLI, Cursor, and Gemini CLI. A companion VS Code extension is distributed through the Visual Studio Marketplace as zilliz.semanticcodesearch .

read the full claude-context 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 claude-context more popular?

vllm has 92,202 GitHub stars and claude-context has 12,548. vllm has the larger community by that measure.

Are vllm and claude-context free?

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

What is the difference between vllm and claude-context?

vllm is written in Python and claude-context 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 claude-context?

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