Unverified50% confidenceFactExact time
小尺寸模型（SLM）通常将参数量控制在70亿至200亿之间，通过知识蒸馏、量化和强化学习对齐等技术在压缩参数量的前提下保持能力
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Long-term
Relevance
7/20/2026
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Related Claims
VerifiedSmall Language Models (SLMs) generally refer to models with parameter counts between 1B and 7B.75% similarUnverifiedKnowledge distillation technology enables small models to extract a considerable proportion of capability from large models, undermining the validity of fixed compute thresholds as a proxy metric for capability.71% similarUnverified随着模型参数规模从亿级扩展到千亿级，LLM展现出涌现能力，包括多步推理、类比迁移和不确定性表达68% similarUnverified模型微调能将知识永久写入模型权重，但需要大量标注数据、算力成本高、迭代周期长68% similarUnverifiedLightweight models are compressed in scale through knowledge distillation and model pruning techniques; knowledge distillation has the small model mimic the output probability distribution of the large model, while pruning removes network weights that contribute least to the output.67% similar
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