{
  "id": 17905453,
  "title": "Capacity Planning for Resource-Constrained Clinical LLM Serving",
  "url": "https://urgent.news/2026/10/31/capacity-planning-for-resource-constrained-clinical-llm-serving",
  "topic": "ai",
  "section": "AI",
  "published": "2026-10-31T17:41:35.000Z",
  "source": {
    "name": "arXiv cs.AI",
    "slug": "arxiv-cs-ai",
    "url": "https://arxiv.org/abs/2611.01152v1"
  },
  "original_language": "en",
  "account": null,
  "summary": "Deploying large language models (LLMs) under a fixed accelerator budget requires jointly deciding how computational capacity is allocated across model sizes and how incoming requests are routed across that capacity. Although prior work has extensively studied LLM routing and serving efficiency, the relative importance of fleet composition and routing under resource constraints remains less…",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}