Introducing the EdgeFirst Model Zoo

EdgeFirst has introduced a public Model Zoo designed to provide reproducible, hardware-specific edge AI benchmarks rather than relying on peak TOPS ratings or model-card results from unrelated systems. It includes detection and instance-segmentation variants of YOLOv5, YOLOv8, YOLO11, and YOLO26, with nano, small, and medium models in ONNX FP32 and INT8 formats as well as accelerator-specific compiled artifacts. The zoo publishes 837 validation sessions across platforms including NXP, Hailo, NVIDIA Jetson, Qualcomm, Apple, CUDA, and x86 and Arm CPUs, with each result linked to its model artifact, dataset version, timing trace, configuration, and host details. The results emphasize that performance depends on factors beyond accelerator silicon, such as board memory, thermal conditions, software stacks, graph-decoder choices, and pipelined throughput behavior. EdgeFirst positions the collection as a transparent example of its Studio and Profiler workflow, which users can apply to their own models, datasets, and candidate hardware before making long-term silicon-selection decisions.

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