{
  "id": 13622,
  "url": "https://arxiv.org/abs/2607.22083v1",
  "title": "Nanbeige4.2-3B: Unlocking Agentic Capabilities in a Compact Mode",
  "summary": "We present Nanbeige4.2-3B, a compact general agentic model with 3B non-embedding parameters. It delivers strong performance across code-agent, office-agent, and complex tool-use tasks while maintaining highly competitive reasoning capabilities in mathematics, coding, and science. Nanbeige4.2-3B is pretrained from scratch on 28T tokens with a Looped Transformer that reuses the layer stack to increase capacity without adding parameters. For SFT data and trajectory construction, we expand the diver",
  "authors": "Nanbeige Lab, :, Chen Yang, Chengrui Huang, Fufeng Lan, Hanhui Chen et al.",
  "category": "research",
  "topics": "agents-autonomy",
  "orgs": null,
  "regions": null,
  "published_at": "2026-07-24T08:33:26.000Z",
  "fetched_at": "2026-07-27T05:10:06.638Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/13622",
  "original_url": "https://arxiv.org/abs/2607.22083v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}