When purchasing a used GPU for local LLM inference, prioritize VRAM capacity above all other specifications, as insufficient memory will prevent models from running entirely. Bandwidth is the second most important factor, while core count and other features are significantly less critical. Consider the GPU's driver support window, as older cards may become incompatible with newer CUDA toolkits and inference software over time. The NVIDIA RTX 3090 is highlighted as a notable option due to its 24 GB of GDDR6X VRAM and NVLink connector, though the latter's utility for inference is limited. AI
IMPACT Guides users on selecting hardware for local LLM inference, impacting the practical deployment of AI models.
RANK_REASON Article provides practical advice on selecting hardware for a specific AI task, rather than announcing a new AI model or research.
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