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Developer tests MTP speedup on Mac, finds mixed results

A developer tested the performance of Multi-Token Prediction (MTP) on their Mac Studio, finding that it significantly speeds up code generation for certain models while slowing down others. The EAGLE-4 speculative decoding method, which inspired the test, is not compatible with Mac hardware. The developer's findings indicate that MTP can boost generation speed by up to 92% for a 27B parameter model but can also decrease performance by 19% for a 35B MoE model, with potential changes to output text quality. AI

IMPACT MTP offers potential speedups for local LLM inference on Apple Silicon, but performance gains are model-dependent.

RANK_REASON Developer tests a technique (MTP) on local hardware, comparing it to a released but incompatible method (EAGLE-4).

Read on dev.to — LLM tag →

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

Developer tests MTP speedup on Mac, finds mixed results

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Developer tests a technique (MTP) on local hardware, comparing it to a released but incompatible method (EAGLE-4).
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  1. dev.to — LLM tag TIER_1 English(EN) · Roman Tsisyk ·

    EAGLE-4 does not run on a Mac. I measured MTP instead: +92% on one model, -19% on another

    <p>A release announcement for EAGLE-4, a speculative decoding method, reported up to 3.4x faster generation for Qwen3.8-27B on four NVIDIA B300 GPUs. I run local models on a Mac Studio, and I wanted to know one thing: does it make my models faster?</p> <p>The short answer: EAGLE-…