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18 Dec 2025Form Number
LP2260PDF size
34 pages, 1.6 MBSubscribed to LP2260.
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Abstract
Lenovo ThinkEdge for AI provides a comprehensive blueprint for deploying real-time AI inference workloads at the edge using Lenovo’s ThinkEdge server portfolio. As data volumes generated by sensors, cameras, and IoT devices continue to grow, traditional data center and cloud-centric AI solutions face increasing challenges related to latency, bandwidth constraints, and data sovereignty.
This reference architecture addresses those challenges by enabling local AI processing at the edge, reducing response times, and improving operational efficiency across industries such as retail, manufacturing, healthcare, smart cities, and financial services. The document outlines validated hardware configurations and sizing models, workload-optimized AI frameworks—including vLLM, TensorRT-LLM, and OpenVINO—and integrated lifecycle management tools such as Lenovo XClarity One and Lenovo Open Cloud Automation.
Aligned with Lenovo’s Hybrid AI strategy, this architecture supports scalable edge deployments that integrate seamlessly with centralized training and analytics in the data center or cloud, enabling organizations to operationalize AI where real-time intelligence delivers the greatest impact.
Table of Contents
Introduction
Solution Overview
Edge Location in a Hybrid AI Platform
Lenovo ThinkEdge Server Portfolio
Standard Models Guide
Test Overview
Test Results
Life Cycle Management Software
Summary
Appendix: Lenovo Bill of Materials
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Change History
Changes in the December 18, 2025 update:
- Updating to 2nd Generation of Edge Standard Models
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