{
  "slug": "antares-1b",
  "order": 88,
  "name": "Antares (1B)",
  "baseTitle": "Antares 1B",
  "company": "Cisco",
  "country": "United States",
  "flag": "🇺🇸",
  "date": "2026-07-21",
  "decoderType": "Dense",
  "attention": "GQA with RoPE",
  "layerMix": "40 GQA",
  "scale": "1B parameters",
  "totalParams": 1000000000,
  "activeParams": 1000000000,
  "context": "131,072",
  "contextTokens": 131072,
  "license": "Apache License 2.0",
  "kvCacheText": "80 KiB",
  "kvCacheKiB": 80,
  "kvCacheLevel": "Moderate",
  "summary": "Cisco Foundation AI's compact terminal agent uses a dense Granite 4.0 backbone and is post-trained with SFT and GRPO for vulnerability localization.",
  "keyDetail": "Retains Granite 4.0's MuP scaling multipliers and tied input/output embeddings, then adds SFT and GRPO for terminal-based vulnerability localization.",
  "image": {
    "full": "https://sebastianraschka.com/llm-architecture-gallery/images/architectures/antares-1b.webp",
    "thumb": "https://sebastianraschka.com/llm-architecture-gallery/images/architectures/thumbnails/antares-1b.webp",
    "alt": "Figure 1: Antares 1B",
    "width": 919,
    "height": 960
  },
  "articleUrl": null,
  "links": [
    {
      "label": "config.json",
      "href": "https://huggingface.co/fdtn-ai/antares-1b/blob/main/config.json",
      "title": "fdtn-ai/antares-1b"
    },
    {
      "label": "Tech report",
      "href": "https://cisco-foundation-ai.github.io/antares/technical-report.pdf",
      "title": null
    }
  ],
  "concepts": [
    {
      "slug": "gqa",
      "label": "GQA",
      "name": "Grouped-Query Attention",
      "url": "https://llm-atlas-7or.pages.dev/concepts/gqa/"
    }
  ],
  "aai": null,
  "sourceUrl": "https://sebastianraschka.com/llm-architecture-gallery/#card-antares-1b",
  "family": "dense",
  "url": "https://llm-atlas-7or.pages.dev/models/antares-1b/",
  "markdownUrl": "https://llm-atlas-7or.pages.dev/models/antares-1b.md"
}