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Qwen3.5-122B model fits 64GB RAM, offering better quality at slower speeds

By PulseAugur Editorial · [1 sources] ·

A user on r/LocalLLaMA shared their experience running the Qwen3.5-122B model with UD-Q2_K_XL quantizations on a system with 64GB of RAM. This setup allows the larger model to fit into memory, offering significantly better response quality and internal knowledge compared to smaller models like Qwen3 Next 80B. However, this comes at the cost of reduced generation speed, approximately 2.9 tokens/second, and a substantial decrease in prompt processing speed, making it unsuitable for agentic tasks. AI

IMPACT Demonstrates trade-offs in local LLM deployment, balancing model size and quality against performance constraints.

RANK_REASON User experience post about running a specific model configuration locally.

Read on r/LocalLLaMA →

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

Qwen3.5-122B model fits 64GB RAM, offering better quality at slower speeds

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User experience post about running a specific model configuration locally.
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model release
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High
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56 days old
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COVERAGE [1]

  1. r/LocalLLaMA TIER_1 English(EN) · /u/misha1350 ·

    Maxing out 64GB of RAM - Qwen3.5 122B A10B at UD-Q2_K_XL w/ MTP fully replaced Qwen3 Next 80B at UD-Q4_K_XL for me

    <!-- SC_OFF --><div class="md"><p>I've got 64GB of regular RAM, and I ran Qwen3 Next 80B at UD-Q4_K_XL, enjoying both nice performance and a lot better internal knowledge than Qwen3.5 35B A3B, which itself is better than Qwen3.6 35B A3B. With DDR4, I get 8.5 tok/s on average,</p>…

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