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LLM users share experiences running models on 8GB-48GB VRAM

By PulseAugur Editorial · [1 sources] ·

A discussion on the r/LocalLLaMA subreddit explores the practicalities of running large language models (LLMs) on consumer-grade hardware with varying amounts of VRAM. Users are sharing their experiences with models on systems ranging from 8GB to 48GB of VRAM, detailing their hardware configurations, KV cache and context management strategies, and the performance they achieve. The thread aims to consolidate user experiences to understand the current landscape of local LLM deployment. AI

IMPACT Provides practical insights for individuals looking to deploy LLMs on consumer hardware.

RANK_REASON This is a user discussion thread on Reddit about hardware configurations for running LLMs, not a primary source announcement or research paper.

Read on r/LocalLLaMA →

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

LLM users share experiences running models on 8GB-48GB VRAM

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This is a user discussion thread on Reddit about hardware configurations for running LLMs, not a primary source announcement or research paper.
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107 days old
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COVERAGE [1]

  1. r/LocalLLaMA TIER_1 English(EN) · /u/Inevitable_Mistake32 ·

    What models you guys running on 8GB? 16GB VRAM? 24GB? 32GB? 48GB?

    <!-- SC_OFF --><div class="md"><p>And what are you using for kv cache and context? What kind of performance are you getting?<br /> What is your hardware? And what are you using your models for?</p> <p>I figure with how fast everything moves, its worth asking once in a while to co…

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