Unverified50% confidenceFactExact time
The breadth and density of world knowledge are largely determined by the scale of pretrained weights and are difficult to make up through fine-tuning, so small models often exhibit the trait of "knowing how to do things but knowing little."
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50%
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Long-term
Relevance
10/22/2026
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Related Claims
UnverifiedOne user pointed out that small models have a natural bottleneck in knowledge breadth: although advances in agent mechanisms have brought a leap from chatbots to practical agents, what ultimately makes large models stand out is their rich knowledge reserves.73% similarVerifiedThe core capabilities of large language models are reasoning and question answering, but they lack memory and their knowledge has a temporal cutoff at the time of training.73% similarUnverifiedSmall models have limited knowledge capacity and are more prone to fabricating content on factual questions.73% similarUnverifiedNative large models only possess knowledge from their training period and often produce incorrect answers about events that occurred after training.73% similar
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