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M1 Max inference engines benchmarked: rapid-mlx leads

By PulseAugur Editorial · [1 sources] ·

A hobbyist benchmarked several inference engines on an M1 Max MacBook Pro using the Qwen3.5-4B model. The results, submitted to the mlx-chronos community benchmark, indicate that rapid-mlx offers the best performance in terms of speed and memory efficiency. The user is now employing rapid-mlx to serve the Qwen35b-A3b model. AI

IMPACT Provides practical insights for local LLM deployment on Apple Silicon, highlighting efficient inference engines.

RANK_REASON User-generated benchmark comparing multiple inference engines on specific hardware and model. [lever_c_demoted from research: ic=1 ai=0.7]

Read on r/LocalLLaMA →

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

M1 Max inference engines benchmarked: rapid-mlx leads

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0 / 100
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User-generated benchmark comparing multiple inference engines on specific hardware and model. [lever_c_demoted from research: ic=1 ai=0.7]
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Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
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product, other
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High
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109 days old
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COVERAGE [1]

  1. r/LocalLLaMA TIER_1 English(EN) · /u/jarec707 ·

    Benchmarked inference engines for M1 Max 64gb-results & analysis

    <!-- SC_OFF --><div class="md"><p>I'm a hobbyist on a budget, and am using a M1 Max MacBook Pro for local inference, with Hermes Agent. I've endlessly researched which inference engines to use, and there's probably no right answer.</p> <p>This caught my attention today: <a href="…

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