Standard OPS · Intel Core Ultra

The Intel AI Boost NPU runs at ~11 TOPS (INT8), which is enough for typical computer vision workloads (object detection at 30+ FPS, face recognition, simple classification) without loading the CPU. For comparison, running the same models on the CPU would consume 60-80% CPU capacity and prevent the system from doing other work simultaneously. The NPU also draws significantly less power.

YOLOv8 (object detection), FaceNet (face recognition), Whisper (speech-to-text), age/gender classifiers, and various OpenVINO model zoo models. We can pre-load and configure these for orders of 20+ units. For custom models, we provide an Intel OpenVINO development guide.

For sustained moderate AI workloads (1080p video analytics, face detection in classrooms, retail analytics), the NPU + Arc IGP combination is more power-efficient and lower-cost than a discrete-GPU solution while delivering comparable real-world throughput. For heavy AI workloads (4K real-time inference, complex multi-stream analysis), a discrete GPU is still better — but those workloads usually exceed the OPS form factor's thermal budget anyway.

Intel's Core Ultra platform is the foundation for their AI PC roadmap through at least 2028. Long-term BIOS, driver, and software support is excellent. Our partner factories committed to multi-year production runs of this SKU.

Currently +$80–$150 per unit vs. the SZO-OPS-i7-13G, depending on configuration. The premium reflects the newer silicon and NPU capability. For non-AI workloads, the i7-13G is still the best value. For AI-related signage/kiosk workloads, the Ultra pays for itself in reduced cloud API costs and improved responsiveness.