{
  "id": "speculative-decoding",
  "code": "PTL-0217",
  "term": "Speculative Decoding",
  "aliases": [
    "speculative sampling",
    "assisted generation"
  ],
  "category": "foundations",
  "definition": "Speculative decoding is an inference technique in which a smaller, faster draft model proposes several next tokens and the large target model checks them in a single parallel pass, accepting or correcting them so that generation is faster while the output distribution stays the same as sampling from the target model alone.",
  "description": "Because the target model verifies several drafted tokens per forward pass instead of generating one token per pass, decoding needs fewer sequential calls to the large model. A sampling rule that accepts or rejects each drafted token is what preserves the target model's distribution. The speedup depends on how often the draft model's guesses are accepted. A closely related method was published shortly afterwards under the name speculative sampling.",
  "example": null,
  "broader": [],
  "narrower": [],
  "related": [
    "kv-cache",
    "greedy-decoding",
    "knowledge-distillation"
  ],
  "introduced": 2022,
  "added": "2026-10-20",
  "sources": [
    {
      "title": "Fast Inference from Transformers via Speculative Decoding",
      "authors": "Leviathan et al.",
      "year": 2022,
      "url": "https://arxiv.org/abs/2211.17192"
    },
    {
      "title": "Accelerating Large Language Model Decoding with Speculative Sampling",
      "authors": "Chen et al.",
      "year": 2023,
      "url": "https://arxiv.org/abs/2302.01318"
    }
  ],
  "url": "https://protologue.com/t/speculative-decoding/",
  "citation": "Protologue. (2026). Speculative Decoding. In Protologue: A Taxonomy of Prompting and LLM Techniques (v1.4.0, PTL-0217). https://protologue.com/t/speculative-decoding/"
}