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Qwen3.6 35B KV cache quantization trade-offs debated

By PulseAugur Editorial · [1 sources] ·

A discussion on the r/LocalLLaMA subreddit explores the trade-offs of quantizing the KV cache for the Qwen3.6 35B model. Users are debating whether reducing the quantization level below Q8 is beneficial, considering the significant performance and memory footprint implications. AI

IMPACT This discussion highlights potential optimizations for running large language models locally, focusing on memory usage and performance trade-offs.

RANK_REASON Discussion on a subreddit about model quantization trade-offs.

Read on r/LocalLLaMA →

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

Qwen3.6 35B KV cache quantization trade-offs debated

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Discussion on a subreddit about model quantization trade-offs.
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58 days old
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COVERAGE [1]

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

    Qwen3.6 35B A3B KV cavhe quantizations memory footprint

    <table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1v0rzci/qwen36_35b_a3b_kv_cavhe_quantizations_memory/"> <img alt="Qwen3.6 35B A3B KV cavhe quantizations memory footprint" src="https://preview.redd.it/u9zzf0q057eh1.png?width=640&amp;crop=smart&amp;auto=webp&…

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