Tag: Speculative Decoding

4 articles

• Speculative Decoding in Production: Reducing LLM Decode Latency with Draft-Verify

  A systematic guide to Speculative Decoding's Draft-Verify mechanism, covering vLLM and TensorRT-LLM integration, metric tuning, applicability boundaries, and production deployment checks to reduce decode latency and avoid overhead from low acceptance rates.

  07/01/2026 LLM / Inference Optimization / Speculative Decoding / LLM Serving / Engineering Practice

• Speculative Decoding in Production: Reducing LLM Latency with Draft Models

  A systematic guide to Speculative Decoding for LLM inference: principles, engineering trade-offs, model selection, monitoring metrics, and common pitfalls. Learn when and how to deploy draft models for latency reduction.

  06/30/2026 LLM / Inference Optimization / Speculative Decoding / LLMOps / Performance Engineering

• Speculative Decoding in Production: Reducing LLM Per-User Latency with EAGLE and Draft Models

  A practical guide to Speculative Decoding for LLM inference: draft generation, parallel verification, acceptance length, and production metrics. Compares Draft Model, Medusa, and EAGLE with rollout and rollback checklists.

  06/30/2026 LLM Inference / Speculative Decoding / vLLM / EAGLE

• Speculative Decoding in Production: Why Low QPS Speeds Up but High Load Slows Down

  A production-oriented analysis of speculative decoding's benefit boundaries, covering draft models, verification, acceptance rate, request load, and batching, with a pre-deployment checklist.

  06/29/2026 LLM Inference / Speculative Decoding / vLLM / TensorRT-LLM / Performance Optimization