{
  "schema_version": 1,
  "builder_plan": {
    "scenario": "Your self-hosted model spends too long generating answers token by token.",
    "change": "Check whether a compatible draft model and serving integration exist before renting compute.",
    "baseline": "The same target with speculation off, then your existing drafter if you have one.",
    "steps": [
      "Locate the paper's implementation and check its license, model support, data needs, and hardware requirements. Stop here if you cannot obtain the required artifacts.",
      "Save a small set of representative product tasks and expected outcomes. Keep evaluation tasks out of any training or tuning, and choose quality and cost limits before running.",
      "Run the baseline and the proposed change on identical inputs. Keep other settings fixed and repeat paired runs to expose variation.",
      "Save per-task outputs, failures, timings, and all usage costs. Review regressions before expanding the test."
    ],
    "measure": "Accepted draft length, tokens per second, tail latency, output quality, and total GPU cost.",
    "decision": "Keep the change only if it meets your preselected quality and latency limits and improves the metric you care about after setup and operating costs. Otherwise retain the baseline. This is an exploration plan, not a validated recommendation."
  },
  "builder_review": null,
  "arxiv_id": "2610.21436",
  "title": "HyCo: Hybrid Drafting for Cost-Efficient Mobile-Cloud Speculative Decoding",
  "summary": "HyCo replaces server-side speculative decoding (where the server runs its own sequential drafting steps) with a hybrid scheme: the server model's MTP head and one SLM pass run on the client's mobile NPU, with the server shipping hidden states, embeddings, and KV entries instead of executing those steps. Costs include quantization and a restricted vocabulary to fit both drafters on the NPU, a 1K-token context window, increased device compute and network transfer, and an ε-threshold relaxation that no longer exactly preserves the verifier's sampling distribution. It can fail under poor network conditions (single-client LTE/5G results may not transfer), when quality-sensitive workloads reject the relaxed distribution, and on devices lacking the required NPU capabilities.",
  "rationale": "The gains are real but contingent on mobile-NPU client hardware, a device-cloud split architecture, and single-client network conditions that a reader with one 24 GB GPU or API-based serving does not control, so it is worth tracking rather than deploying.",
  "technique": "Hybrid device-cloud speculative decoding with MTP head",
  "family": "decodificacao_especulativa",
  "recommendation": "observar",
  "published": "2026-10-15",
  "as_of": "2026-10-18",
  "editorial_status": "indexed",
  "source_url": "https://arxiv.org/abs/2610.21436",
  "independent_implementations": 0,
  "total_implementations": 0,
  "stars": 0,
  "citations": null,
  "claims": [
    {
      "claim_id": "claim-01",
      "statement": "HyCo replaces server-side speculative decoding (where the server runs its own sequential drafting steps) with a hybrid scheme: the server model's MTP head and one SLM pass run on the client's mobile NPU, with the server shipping hidden states, embeddings, and KV entries instead of executing those steps. Costs include quantization and a restricted vocabulary to fit both drafters on the NPU, a 1K-token context window, increased device compute and network transfer, and an ε-threshold relaxation that no longer exactly preserves the verifier's sampling distribution. It can fail under poor network conditions (single-client LTE/5G results may not transfer), when quality-sensitive workloads reject the relaxed distribution, and on devices lacking the required NPU capabilities.",
      "basis": "inferred",
      "result": "",
      "baseline": "",
      "conditions": "",
      "source_url": "https://arxiv.org/abs/2610.21436",
      "source_page": null,
      "source_excerpt": ""
    },
    {
      "claim_id": "claim-02",
      "statement": "Reduces server GPU time per output token by 38.6% on Spec-Bench and 29.2% on 32K-token summarization versus server-side MTP self-speculation (27.7% and 11.9% without sampling relaxation); 1.9x faster delivery than an SLM-only drafter.",
      "basis": "inferred",
      "result": "",
      "baseline": "",
      "conditions": "",
      "source_url": "https://arxiv.org/abs/2610.21436",
      "source_page": null,
      "source_excerpt": ""
    }
  ],
  "exposure_map": [
    {
      "dimension": "quality",
      "basis": "not_evaluated",
      "finding": "",
      "interpretation": "",
      "limitation": "",
      "next_check": "",
      "source_url": "",
      "source_page": null,
      "source_excerpt": ""
    },
    {
      "dimension": "compute",
      "basis": "not_evaluated",
      "finding": "",
      "interpretation": "",
      "limitation": "",
      "next_check": "",
      "source_url": "",
      "source_page": null,
      "source_excerpt": ""
    },
    {
      "dimension": "latency",
      "basis": "not_evaluated",
      "finding": "",
      "interpretation": "",
      "limitation": "",
      "next_check": "",
      "source_url": "",
      "source_page": null,
      "source_excerpt": ""
    },
    {
      "dimension": "operations",
      "basis": "not_evaluated",
      "finding": "",
      "interpretation": "",
      "limitation": "",
      "next_check": "",
      "source_url": "",
      "source_page": null,
      "source_excerpt": ""
    },
    {
      "dimension": "compatibility",
      "basis": "not_evaluated",
      "finding": "",
      "interpretation": "",
      "limitation": "",
      "next_check": "",
      "source_url": "",
      "source_page": null,
      "source_excerpt": ""
    },
    {
      "dimension": "security",
      "basis": "not_evaluated",
      "finding": "",
      "interpretation": "",
      "limitation": "",
      "next_check": "",
      "source_url": "",
      "source_page": null,
      "source_excerpt": ""
    },
    {
      "dimension": "data_and_training",
      "basis": "not_evaluated",
      "finding": "",
      "interpretation": "",
      "limitation": "",
      "next_check": "",
      "source_url": "",
      "source_page": null,
      "source_excerpt": ""
    },
    {
      "dimension": "reproducibility",
      "basis": "not_evaluated",
      "finding": "",
      "interpretation": "",
      "limitation": "",
      "next_check": "",
      "source_url": "",
      "source_page": null,
      "source_excerpt": ""
    }
  ],
  "risks": [],
  "minimum_test": [],
  "open_questions": [],
  "independent_tests": [],
  "lab_reproductions": [],
  "report_available": false,
  "validation_tier": "unknown",
  "evidence_tier": "unknown",
  "infrastructure_basis": "unknown",
  "equations": [],
  "equations_status": "not_fetched",
  "core_kind": "",
  "equations_fetched_at": "",
  "equations_source_url": "",
  "equations_source_sha256": "",
  "exposures_reviewed_at": "",
  "exposures_source_sha256": ""
}