PulseAugur
EN
LIVE 17:18:19

Users discuss running large language models on 192GB RAM systems

A Reddit user is seeking recommendations for large language models that can run on systems with 192GB of RAM, specifically mentioning their positive experience with Qwen3.5-397B. They have also made custom modifications to llama.cpp to improve performance for hybrid recurrent models and are looking to fix issues with tool calls and KV cache. The user is interested in other large models such as GLM 4.7 357B, Deepseek V4 Flash 284B, and Tencent Hy3 295B, and is asking the community about their experiences and comparisons. AI

IMPACT Provides insights into the practicalities and challenges of running very large language models locally, informing hardware choices and software optimization for advanced users.

RANK_REASON User-generated discussion about running large language models on consumer hardware, not a primary release or significant industry event.

Read on r/LocalLLaMA →

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

Users discuss running large language models on 192GB RAM systems

COVERAGE [1]

  1. r/LocalLLaMA TIER_1 (TL) · /u/CentrifugalMalaise ·

    192GB gang - what are you running?

    <!-- SC_OFF --><div class="md"><p>Understandably, most chat is around models that fit in 16/32GB VRAM. I totally get that. And I think Qwen3.6-27B is awesome. But, a while back, I bought an M2 Ultra Mac Pro specifically for AI, so my main interest is in models in that size-region…