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User seeks to pool GPUs and RAM across two PCs for LLM inference

By PulseAugur Editorial · [1 sources] ·

A user on Reddit is seeking advice on how to best utilize two PCs for running large language models, specifically focusing on how to pool their resources. The user has one PC with 94GB of RAM and two GPUs (a 5070 TI and a 3060 with 12GB), and a second PC with 64GB of RAM. They are considering connecting the PCs via Ethernet and using llama.cpp's RPC functionality to combine their processing power, or if it would be more effective to keep the GPUs in the primary PC and use the second PC solely for additional RAM. AI

RANK_REASON This is a user query on a forum about hardware configuration for running LLMs, not a news event.

Read on r/LocalLLaMA →

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

User seeks to pool GPUs and RAM across two PCs for LLM inference

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This is a user query on a forum about hardware configuration for running LLMs, not a news event.
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COVERAGE [1]

  1. r/LocalLLaMA TIER_1 English(EN) · /u/No_Cartographer3953 ·

    Two PCs but one with only RAM? or divide GPUs across pcs?

    <!-- SC_OFF --><div class="md"><p>PC1:<br /> -94gb DDR5</p> <p>-5070 TI + 3060 (12gb) gpus (using a motherboard that is specifically designed for duel gpus</p> <p>PC2:</p> <p>64gb DD4 RAM</p> <p>PC1 is new, I've been running strata for running larger MoEs but I'm curious about tr…

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