LLM VRAM Guide: What Models Fit on 8GB to 80GB GPUs

This guide breaks down the VRAM requirements for running various Large Language Models (LLMs) on common GPU sizes, focusing on 4-bit quantization and reasonable context lengths. It details which models fit on 8GB, 16GB, 24GB, 48GB, and 80GB VRAM configurations, noting that factors like quantization and context length significantly impact memory usage. The breakdown highlights that 8GB can run 7B-9B models, 16GB is practical for 13B-14B models, 24GB accommodates 30B-class models (especially MoE architectures), 48GB is the entry point for 70B models, and 80GB offers significant headroom for larger models or higher precision. AI

IMPACT Helps users determine hardware needs for running LLMs locally, impacting adoption and accessibility for individuals and budget-conscious production environments.

RANK_REASON The item provides practical guidance on hardware requirements for running existing LLMs, rather than announcing a new model or research breakthrough.

Read on dev.to — LLM tag →

• graphics processing unit
• L4 GPU
• Llama-3.1:8b
• Nvidia
• Qwen-3.5 9B
• VRAM

• infra

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