vLLM continuous batching boosts throughput 2.91×

towardsdatascience.com16 min read

An analysis of vLLM serving performance demonstrates that continuous batching improves throughput by up to 2.91× over static batching on highly variable workloads. The author finds that output-length variance and whether the request queue empties are the primary factors determining the scheduler's benefit, while engine and memory management improvements also contribute to overall performance gains. Open article →