vLLM

vLLM offers a high-throughput, memory-efficient solution for deploying Large Language Models (LLMs) with ease. It provides a drop-in OpenAI-compatible API, enabling instant integration across various platforms. With PagedAttention, vLLM maximizes throughput, ensuring peak GPU utilization through advanced scheduling and continuous batching.

The engine is designed to be cost-efficient, reducing inference costs by optimizing hardware usage, making high-performance LLMs accessible to everyone. Installation is straightforward, supporting Python 3.10+ with recommendations for Python 3.12+.

vLLM supports a wide range of hardware, offering a unified API that ensures compatibility across platforms. It also features the latest open-source models, optimized and ready for production.

The community-driven project is supported by notable sponsors like Alibaba Cloud, AWS, Google Cloud, and more, ensuring robust development and testing resources. Whether you're new or experienced, the vLLM community is ready to assist with fast, friendly responses.