Splendid Cisco 300-640 Exam Questions - Pass Exam Confidently [2026]

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Cisco 300-640 Exam Syllabus Topics:

SectionObjectives
Data Center Networking for AI Workloads- High-performance fabric design
  • 1. Low-latency switching and routing considerations
    • 2. Leaf-spine architecture in AI environments
      - Cisco Data Center networking technologies
      • 1. Cisco ACI integration concepts
        • 2. Cisco Nexus platform concepts
          Data Center AI Infrastructure Fundamentals- AI/ML workload requirements in data centers
          • 1. Data pipeline and workload characteristics
            • 2. Compute, GPU, and acceleration concepts
              Compute and Storage for AI Infrastructure- Storage systems
              • 1. Distributed storage concepts
                • 2. High-throughput storage for AI training data
                  - Compute architecture
                  • 1. GPU-based compute nodes
                    • 2. HPC-style scaling considerations
                      Security and Governance in AI Data Centers- Infrastructure security
                      • 1. Network segmentation and policy enforcement
                        • 2. Secure access to AI workloads
                          AI Infrastructure Deployment and Operations- Deployment models
                          • 1. Hybrid AI infrastructure integration
                            • 2. On-premises AI clusters
                              - Operations and lifecycle management
                              • 1. Performance tuning and optimization
                                • 2. Monitoring and observability

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                                  Cisco Implementing Cisco Data Center AI Infrastructure Sample Questions (Q24-Q29):

                                  NEW QUESTION # 24
                                  What describes inference traffic patterns in AI deployments?

                                  Answer: D

                                  Explanation:
                                  Inference traffic is associated with using a trained model to generate predictions or responses from new input data. In AI deployments, this commonly supports real-time or near-real-time decision making, such as classification, recommendations, detection, or automated responses.


                                  NEW QUESTION # 25
                                  Drag and Drop Question
                                  An engineer must configure vNIC templates for a UCS X-Series deployment. Drag and drop the policy types from the left onto the corresponding configuration settings on the right. Not all options are used.

                                  Answer:

                                  Explanation:


                                  NEW QUESTION # 26
                                  A national law firm is deploying a RAG solution for their legal research team to more efficiently use their 50 TB of confidential data and documents when preparing new contracts and briefs.
                                  They decided on a UCS X-Series chassis equipped with four GPUs and six X210c servers. Which storage solution fits this deployment?

                                  Answer: D

                                  Explanation:
                                  A RAG deployment with 50 TB of confidential documents requires scalable shared storage that can be accessed by multiple UCS X210c servers. An IP-based storage array provides centralized capacity, shared access, and operational simplicity for storing and retrieving large datasets used by the RAG pipeline.


                                  NEW QUESTION # 27
                                  A financial company plans to deploy an AI training and inference infrastructure to support its customers. The team must use a solution that provides 96 GPUs, aligns with NVIDIA-compliant reference architectures, and enables cloud-based management of the entire on-premises network environment. Which Cisco solution meets the requirements?

                                  Answer: D

                                  Explanation:
                                  Cisco HyperFabric AI Small AI Cluster matches the 96-GPU requirement because the validated HyperFabric reference architecture uses 12 Cisco UCS C885A M8 servers with NVIDIA HGX for a total of 96 GPUs. Cisco Nexus HyperFabric is also cloud-managed and compliant with NVIDIA Enterprise Reference Architecture, enabling centralized management of the on-premises AI network, GPU servers, and storage.


                                  NEW QUESTION # 28
                                  A network architect designs connectivity for a new Cisco AI POD operating in Intersight Managed Mode. To ensure high availability and aggregate bandwidth for external network traffic, a port channel must be established using multiple 100 GbE uplink ports on the fabric interconnects to connect to the upstream core switch infrastructure. Which specific policy, applied through the domain profile, must be modified to define and configure this port channel on the fabric interconnects for the desired uplink connectivity?

                                  Answer: B

                                  Explanation:
                                  In Cisco Intersight Managed Mode, fabric interconnect port roles and uplink port channels are defined in the port policy associated with the UCS domain profile. Modifying the port policy allows the engineer to configure multiple 100 GbE uplink ports as a port channel for aggregated bandwidth and high availability toward the upstream network.


                                  NEW QUESTION # 29
                                  ......

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