Alternatives to Vllm
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vLLM is an open-source high-throughput and memory-efficient LLM inference and serving engine, created by Woosuk Kwon, Zhuohan Li, and colleagues at UC Berkeley in 2023. vLLM's breakthrough innovation is PagedAttention — a memory management technique inspired by virtual memory paging in OS kernels that eliminates memory fragmentation in the KV cache, increasing GPU memory utilization from ~60% (with naive continuous batching) to 96%+.
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