Same Model, Same Hardware, 24 Times the Throughput: What vLLM Actually Does and Why It Matters
中文摘要
vLLM显著提升大语言模型推理吞吐量，相同硬件下最高可达24倍，对LLM生产部署至关重要。
English Summary
vLLM dramatically boosts language model inference throughput by up to 24 times on the same hardware, proving crucial for efficient LLM production deployment.
Original Excerpt
The sequence is familiar to anyone who has moved a language model from experimentation to production. Continue reading on Medium »