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LocalLLaMA users discuss stagnant prefill speeds for Qwen models

By PulseAugur Editorial · [1 sources] ·

A user on Reddit's r/LocalLLaMA community is inquiring about improvements to the prefill speed of large language models, specifically mentioning Qwen 27B and Qwen Flash Next. While decode speeds have seen significant advancements, the user notes that prefill performance appears to be lagging, potentially due to hardware limitations or trade-offs in accuracy when attempting to optimize for speed. They are seeking information on any ongoing work or clever solutions being developed to address this bottleneck. AI

IMPACT Highlights a potential bottleneck in LLM inference performance that may require further research or hardware innovation.

RANK_REASON User discussion on a technical limitation of LLMs, not a release or new development.

Read on r/LocalLLaMA →

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

LocalLLaMA users discuss stagnant prefill speeds for Qwen models

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Commentary
User discussion on a technical limitation of LLMs, not a release or new development.
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COVERAGE [1]

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

    Is anyone working on improving prefill speed? (Qwen 27b, Flash)

    <!-- SC_OFF --><div class="md"><p>I see everyone improving decode with bespoke models, like Sushi or Splash with Qwen 27b and Qwen Flash Next, and I'm running QFN now at 40tk/s on my M3 Max which is awesome.</p> <p>But prefill feels stagnant. I was trying to work on layer / atten…

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