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Hyperparameter search yields minor gains for speculative decoding

A user on Reddit's r/LocalLLaMA subreddit shared their experience with hyperparameter tuning for speculative decoding, specifically using the "draft-mtp" method with the Qwen3.6 27B model on a Strix Halo platform. Despite extensive searching with Optuna, the user found only a modest 6% improvement in tokens per second compared to default parameters. They provided a Python script and the optimal command-line arguments used in their experiment. AI

IMPACT Minor optimization insights for local LLM deployments; does not represent a significant industry shift.

RANK_REASON User-generated commentary on a technical experiment with limited broader impact.

Read on r/LocalLLaMA →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

COVERAGE [1]

  1. r/LocalLLaMA TIER_1 English(EN) · /u/Zc5Gwu ·

    MTP hyperparameter search

    <!-- SC_OFF --><div class="md"><p>TLDR; I only got a 6% improvement on tokens/sec over naïve parameters.</p> <p>I was messing around and ran a hyperparameter search with optuna over the MTP and speculative decoding options of llama-server for Qwen3.6 27b on strix halo.</p> <p>Her…