Hugging Face· Platform

Efficient Request Queueing – Optimizing LLM Performance

The article discusses the problem of request queuing in LLM inference engines and presents a solution using fair scheduling with separate queues per user and model, and dynamic rate limiting to keep the backend queue short.

From the source

Serving LLMs to many applications and users in parallel is challenging because they compete for limited GPU resources. This article is the first in a series on LLM performance, based on our experience with serving self-hosted LLMs at TNG Technology Consulting GmbH. In the first part, we focus on the impact of queuing and discuss different scheduling strategies.

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Announced

02 Apr 2025 13:33 UTC

Detected

03 Aug 2026 21:12 UTC (+488d after)