{
  "@context": "https://schema.org",
  "@type": "TechArticle",
  "@id": "https://anchorfact.org/kb/long-context-models",
  "headline": "Long-Context Language Models: Beyond 1M Tokens",
  "description": "Modern LLMs process context windows of 100K-2M tokens — entire books, codebases, or years of conversation history. Gemini 1.5 Pro demonstrated >99% retrieval accuracy across 1M tokens, proving usable long-context capability.",
  "dateCreated": "2026-05-24T02:49:13.629Z",
  "dateModified": "2026-05-24",
  "author": {
    "@type": "Organization",
    "name": "AnchorFact"
  },
  "publisher": {
    "@type": "Organization",
    "name": "AnchorFact",
    "url": "https://anchorfact.org"
  },
  "license": "https://creativecommons.org/licenses/by/4.0/",
  "anchorfact:confidence": "high",
  "anchorfact:generationMethod": "ai_assisted",
  "citation": [
    {
      "@type": "CreativeWork",
      "name": "Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context",
      "sameAs": "https://arxiv.org/abs/2403.05530"
    },
    {
      "@type": "CreativeWork",
      "name": "RULER: What's the Real Context Size of Your Long-Context Language Models?",
      "sameAs": "https://arxiv.org/abs/2405.07704"
    }
  ]
}