{
  "@context": "https://schema.org",
  "@type": "TechArticle",
  "@id": "https://anchorfact.org/kb/llm-inference-optimization",
  "headline": "LLM Inference Optimization: From FlashAttention to Speculative Decoding",
  "description": "LLM inference optimization has made serving trillion-parameter models economically viable. FlashAttention eliminates the memory bottleneck; speculative decoding accelerates generation 2-3x; KV-cache optimization reduces memory by 8x.",
  "dateCreated": "2026-05-24T02:49:13.627Z",
  "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": "FlashAttention: Fast and Memory-Efficient Exact Attention",
      "sameAs": "https://arxiv.org/abs/2205.14135"
    },
    {
      "@type": "CreativeWork",
      "name": "Fast Inference from Transformers via Speculative Decoding",
      "sameAs": "https://arxiv.org/abs/2211.17192"
    }
  ]
}