MTPLX vs oMLX: Mac setup and MTP speed test

This tutorial compares MTPLX with oMLX for a local LLM workflow on an M-series Apple Silicon Mac. The speaker explains multi-token prediction as a drafter proposing tokens for a verifier to check. He then describes MTPLX's claim that its native MTP runtime builds this functionality into one model without requiring a separate second model.

The setup covers installation through a DMG or Homebrew, downloading models and tuning them for the Mac. Gemma 4 and Qwen 3.6 appear in the tuning demonstration. To compare inference engines, the speaker adds the MTPLX model directory to oMLX and configures Pi Coding Agent to use the same model. He then switches Pi to MTPLX and repeats a project review prompt that excludes node modules.

The speaker reports almost 23% higher token generation throughput with MTPLX. He also thinks prefill and response time improved, but provides no separate measurement for those claims. Both inference engines, OBS and other programs were running during the comparison, so the result reflects this particular setup rather than a controlled benchmark or a guaranteed speed increase.

He also reports having to manage context windows closely in oMLX and says he has not yet seen the same trouble with MTPLX. That observation is preliminary: he describes MTPLX as very new and plans to try it as his daily driver.