# Multi-Token Prediction Speculative Verification and Draft Amortization > Source-anchored research for Multi-Token Prediction Speculative Verification and Draft Amortization. Run status: COMPLETED. Parent: [Local Inference Micro-Architectures: Signaling, Quantization Superblocks, and Kernel Pipeline Scheduling](https://llms-explorer.com/tree/inference-microarchitectures-and-kernel-pipelines/) · 2 facets · 2 facts · page: https://llms-explorer.com/tree/multi-token-prediction-speculative-verification-and-draft-amortization/ ## Measurements and reference values - When speculative verification achieves an acceptance rate greater than 60%, end-to-end token generation throughput increases by 25% to 45% on memory-bandwidth-constrained devices. (high confidence) — [source](https://huggingface.co/Qwen) ## Comparisons and alternatives - Speculative decoding amortizes parameter weight memory loading across K candidate tokens by evaluating candidate sequences as a small parallel GEMM batch instead of K sequential GEMV reads. (high confidence) — [source](https://huggingface.co/Qwen)