How is vLLM used or implemented?

The framework's key innovation is PagedAttention, a memory management algorithm inspired by virtual memory in operating systems that organizes the KV cache into fixed-size blocks, dramatically reducing memory fragmentation and enabling 2x-24x throughput improvements over naive implementations. vLLM also implements continuous batching, where new requests join a running batch without waiting for the current batch to complete, maintaining high GPU utilization across varying request lengths. The framework supports hundreds of LLM architectures including Llama, Mistral, Qwen, Mixtral, Gemma, DeepSeek, and OpenAI-compatible API endpoints. vLLM is widely deployed by companies hosting their own LLM infrastructure, including AnyScale, Lambda Labs, RunPod, and Together AI. The platform str