{
  "id": 16554903,
  "title": "Green Code or Costly Code? Evaluating the Energy Costs of Iterative LLM-Based Code Optimizations",
  "url": "https://urgent.news/2026/10/23/green-code-or-costly-code-evaluating-the-energy-costs-of-iterative",
  "topic": "ai",
  "section": "AI",
  "published": "2026-10-23T16:58:01.000Z",
  "source": {
    "name": "arXiv cs.AI",
    "slug": "arxiv-cs-ai",
    "url": "https://arxiv.org/abs/2610.32891v1"
  },
  "original_language": "en",
  "account": null,
  "summary": "Large Language Models (LLMs) are increasingly used to optimize code for performance. This practice often assumes that improvements in execution speed naturally translate into overall lower energy consumption. We challenge this assumption empirically by measuring whether performance-optimized code produced by LLM self-refinement pipelines is also energy-efficient relative to canonical human…",
  "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."
}