Deepseek has significantly enhanced the reasoning capabilities of large language models (LLMs). The original Deepseek models, comprising 650 billion parameters, require substantial GPU resources for deployment. A notable advancement is the distillation of Deepseek's knowledge into smaller models such as LLama, Qwen, and others.
However, the critical question remains: what is the safety score of these distilled models compared to other prominent models? In this report, we conducted a light safety assessment relative to other well-known models, providing insights for the industry to safely experiment with distilled models.
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