vllm-project/vllm
A high-throughput and memory-efficient inference and serving engine for LLMs
What it does
vLLM is an open-source engine that makes running large AI language models (like GPT or Llama) dramatically faster and cheaper, allowing companies to serve AI-powered features to many users at once without breaking the bank. Think of it as a high-performance traffic system for AI — instead of each request waiting in line, it efficiently batches and processes thousands of queries simultaneously.
Why it matters for PMs
For any company building AI-powered products, the cost and speed of running language models is often the biggest barrier to scaling — vLLM directly attacks that problem, meaning teams can ship faster, serve more users, and spend less on cloud compute. With 70,000+ stars and support for virtually every major AI model (GPT, Llama, DeepSeek, Qwen), it has become a de facto industry standard, making it a critical dependency to understand if you're evaluating AI infrastructure or competitive positioning.
Early stage — limited signal data
Score updated Feb 18, 2026
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