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DeepSeek V4 Flash 8-bit MLX optimized for Apple Silicon, boosting speed

By PulseAugur Editorial · [1 sources] ·

A user on Reddit shared optimizations made to the DeepSeek V4 Flash 8-bit MLX model using oMLX on Apple Silicon. The modifications, implemented by Codex, focused on enabling native DeepSeek MoE Metal kernels for 8-bit affine configurations and optimizing route sorting and decode kernels. These changes resulted in significant speed improvements, with prefill speeds increasing by approximately 1.6x and decode speeds by about 3x, while aiming to maintain model accuracy. AI

IMPACT User-driven optimizations can accelerate local LLM deployment on consumer hardware.

RANK_REASON User-driven optimization of an existing open-source model for specific hardware, not a primary release from a frontier lab.

Read on r/LocalLLaMA →

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

DeepSeek V4 Flash 8-bit MLX optimized for Apple Silicon, boosting speed

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User-driven optimization of an existing open-source model for specific hardware, not a primary release from a frontier lab.
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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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infra, model release
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High
Clearly on-topic for AI-industry coverage.
Story freshness
82 days old
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COVERAGE [1]

  1. r/LocalLLaMA TIER_1 English(EN) · /u/No_Run8812 ·

    I asked Codex to optimize DeepSeek V4 Flash 8-bit MLX on oMLX. Got ~1.6x prefill and ~3x decode speedup.

    <!-- SC_OFF --><div class="md"><p>Follow-up to my earlier posts:</p> <ul> <li>Should I sell my Mac Studio? <a href="https://www.reddit.com/r/MacStudio/s/GK7QP8Lg87">https://www.reddit.com/r/MacStudio/s/GK7QP8Lg87</a></li> <li>Kimi benchmark: <a href="https://www.reddit.com/r/Loca…

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