Large language models (LLMs) have recently demonstrated significant success across a wide range of domains. Their extensive pre-training on vast quantities of information available on the internet endows them with a broad and general understanding of many areas. This presents an opportunity to apply LLMs to the networking domain, such as assisting human operators in maintaining data centers or helping security analysts respond to network attacks in time-sensitive environments. However, it remains unclear if LLMs possess the necessary understanding of the networking domain. To evaluate this, we assess LLMs’ ability to reason about networking by testing their performance on the Cisco Certified Network Associate ( CCNA ), Cisco Certified Support Technician (CCST) and the Microsoft Networking Foundations (N.F) certifications, industry-leading exam. Our findings reveal that various open and closed weights models can pass the CCNA certification but encounter difficulties when answering questions that require advanced reasoning.
Manocchio et al. (Sun,) studied this question.