# GAUSS: A Workload-Aware Analytical and Monte-Carlo Simulator for LLM Inference Serving

> Полный текст доступен на английском

**Published:** 30 октября 2026 г.
**Author:** Srikant Bharadwaj, Ankur Mallick, Spyridon Mastorakis, Anjaly Parayil, Dhruv Deshmukh, Victor Ruehle
**Source:** arXiv — cs.AI
**Language:** en-US
**HTML:** https://aiqazaqstan.com/ru/articles/gauss-a-workload-aware-analytical-and-monte-carlo-simulator-for-llm-infe

arXiv:2610.37989v1 Announce Type: new Abstract: Large language model (LLM) inference has become an operational workload that fleets must provision, monitor, and bill against latency service-level objectives (SLOs). A single throughput number cannot answer the questions operators…

> Материал агрегирован из первоисточника: **arXiv — cs.AI**
> [Читать полностью в arXiv — cs.AI](https://arxiv.org/abs/2610.37989)

**Теги:** #arXiv

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