vllm: Fast, Low‑Memory LLM Inference for Scalable AI Products
From the repo · “A high-throughput and memory-efficient inference and serving engine for LLMs”
Run large language models (LLMs) quickly and efficiently
"A founder wants to build a language translation feature for their travel agency's website. They use vllm to host their LLM model and set up an API endpoint to translate user input in real-time, allowing them to deliver instant results."
- •When you need to serve LLMs in a production environment with high traffic
- •When you want to reduce the memory footprint of your LLM deployment
- •When you need to integrate LLMs with other AI services or microservices
python -m vllm.serve --model-name bert-base-uncased --port 8000
Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.
Expect 20–40 minutes in a terminal — or let your AI agent drive it.
mkdir -p ~/.claude/skills/vllm && curl -fsSL https://workflowstacks.com/api/skills/vllm/claude-skill -o ~/.claude/skills/vllm/SKILL.mdOpens the app with this repo with the prompt ready to go — no copy-paste needed.
Vllm: Fast, Low‑Memory LLM Inference for Scalable AI Products is a very large Python project (~1M lines across 3062 code files, plus 1717 test files). It is a full software project: use it through its install path rather than reading it end to end. Last commit this month, Apache-2.0 license, has a test suite.
Users get fast LLM results
- 1README.mdStart here — what it does and how to install it
- 2AGENTS.mdThe instructions the AI actually follows
- 3pyproject.tomlDependencies and the commands it exposes
- 4vllm/__init__.pyInside vllm/ — the main logic begins here
- 5examples/__init__.pyA worked example — copy this to get going
Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.
Expect 20–40 minutes in a terminal — or let your AI agent drive it.
mkdir -p ~/.claude/skills/vllm && curl -fsSL https://workflowstacks.com/api/skills/vllm/claude-skill -o ~/.claude/skills/vllm/SKILL.mdOpens the app with this repo with the prompt ready to go — no copy-paste needed.
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