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DeepSeek V4 Flash optimized for Apple M2 Ultra, achieves 25.8 t/s

By PulseAugur Editorial · [1 sources] ·

A user has optimized the DeepSeek V4 Flash model for Apple's M2 Ultra chip, achieving significant performance gains. The repacked model is 141 GiB, smaller than public GGUF versions, and runs at 25.8 tokens/second, with peak speeds reaching 42 tokens/second. This optimization also includes SSD KV cache and dynamic lanes, supporting a 1 million token context window. AI

IMPACT Demonstrates potential for further performance gains in local LLM deployments through hardware-specific optimizations.

RANK_REASON User-driven optimization and performance report for an existing model on specific hardware. [lever_c_demoted from research: ic=1 ai=1.0]

Read on r/LocalLLaMA →

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

DeepSeek V4 Flash optimized for Apple M2 Ultra, achieves 25.8 t/s

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0 / 100
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User-driven optimization and performance report for an existing model on specific hardware. [lever_c_demoted from research: ic=1 ai=1.0]
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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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model release, infra
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High
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48 days old
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COVERAGE [1]

  1. r/LocalLLaMA TIER_1 English(EN) · /u/Agusx1211 ·

    DeepSeek V4 Flash on an M2 Ultra: repacked to 141 GiB losslessly, smaller than the Q4 GGUF, at 25.8 t/s (42 t/s peak)

    <!-- SC_OFF --><div class="md"><p>This is one more vibe slopped custom optimization for, in this case, my hardware (m2 ultra 60 cores, 192gb). It is just a fork from llama.cpp with a few changes, it achieves:</p> <p>- DeepSeek V4 Flash, no kv cache quant</p> <p>- 141GiB model, by…

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