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Techniques that dynamically insert new requests into active inference batches to maintain high hardware utilization.
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vLLM is a high-throughput inference engine designed for the efficient serving and execution of large language models. It functions as a production-ready distributed model server, providing standard API protocols for online serving while also supporting offline batch processing. The system is built to maximize token gen