vLLM: An Efficient Inference Engine for Large Language Models [pdf]
Researchers have released vLLM, a new inference engine designed to efficiently serve large language models by optimizing memory management and batching. The system achieves up to 24x higher throughput than existing solutions like HuggingFace Transformers and NVIDIA FasterTransformer. This development addresses critical bottlenecks in deploying LLMs for real-time applications, making high-performance model serving more accessible.
large-language-models, artificial-intelligence, machine-learning, ai-infrastructure, ai-tools