{
  "schema_version": "1.0",
  "scope": "audited display values retained after repository cleanup; local, diagnostic, and published values remain distinguished by metric labels and the sparse comparison column",
  "models": [
    {"model_id":"AD01","model_name":"MLPerf Tiny Deep AutoEncoder (DCASE 2020 ToyCar)","metric":"AUC / pAUC (max_fpr=0.1)","fp32":"0.876001 / 0.764121","quantized":"0.840250 / 0.720049","delta":"-0.035750 / -0.044071","published_comparison":"공개 FP32 AUC/pAUC 0.876001/0.764121; 측정값 동일"},
    {"model_id":"LM04","model_name":"BERT-tiny RAID text detector ONNX","metric":"AUROC / TPR@FPR 5% / 1% (RAID-extra OOD)","fp32":"0.667078 / 0.318983 / 0.233873","quantized":"0.668862 / 0.322615 / 0.235853","delta":"+0.001785 / +0.003632 / +0.001981","published_comparison":""},
    {"model_id":"OD06","model_name":"EfficientDet-Lite0 int8/float32 v1","metric":"COCO bbox mAP (AP@[0.50:0.95])","fp32":"24.8751%","quantized":"24.2822%","delta":"-0.5929 pp","published_comparison":""},
    {"model_id":"OD07","model_name":"EfficientDet-Lite2 int8/float32 v1","metric":"COCO bbox mAP (AP@[0.50:0.95])","fp32":"31.8594%","quantized":"31.4191%","delta":"-0.4403 pp","published_comparison":""},
    {"model_id":"SG06","model_name":"DeepLabV3-MobileNetV2 width 1.0 Pascal train_aug","metric":"mIoU","fp32":"75.6398%","quantized":"74.1290%","delta":"-1.5108 pp","published_comparison":"공개 FP32 mIoU 75.32%; 측정 75.6398% (+0.3198 pp)"},
    {"model_id":"SG07","model_name":"DeepLabV3-MobileNetV2 width 0.5 Pascal train_aug","metric":"mIoU","fp32":"70.6473%","quantized":"69.6191%","delta":"-1.0282 pp","published_comparison":"공개 FP32 mIoU 70.19%; 측정 70.6473% (+0.4573 pp)"},
    {"model_id":"SG08","model_name":"EdgeTPU-DeepLab-slim width 0.75 Cityscapes","metric":"mIoU (CamVid cross-dataset)","fp32":"50.6498%","quantized":"51.1600%","delta":"+0.5102 pp","published_comparison":""},
    {"model_id":"SP01","model_name":"MLPerf Tiny DS-CNN KWS reference","metric":"Top-1 accuracy","fp32":"91.86%","quantized":"91.66%","delta":"-0.2045 pp","published_comparison":"공개 시험 정확도 약 92%; 측정 FP32 91.86%, 양자화 91.66% (근접)"},
    {"model_id":"SP02","model_name":"MLPerf Tiny streaming wakeword 1D DS-CNN","metric":"FP / FN (1 s)","fp32":"5 / 6","quantized":"4 / 6","delta":"-1 / +0","published_comparison":""},
    {"model_id":"SP08","model_name":"TensorFlow Lite Micro micro_speech tiny_conv","metric":"Top-1 accuracy (yes/no subset)","fp32":"94.05%","quantized":"94.05%","delta":"+0.0000 pp","published_comparison":""},
    {"model_id":"SP09","model_name":"Arm ML-Zoo clustered DS-CNN Large INT8","metric":"Top-1 accuracy","fp32":"95.06%","quantized":"94.70%","delta":"-0.3590 pp","published_comparison":""},
    {"model_id":"VC01","model_name":"MLPerf Tiny Visual Wake Words MobileNetV1 0.25","metric":"Top-1 accuracy","fp32":"85.10%","quantized":"85.60%","delta":"+0.5000 pp","published_comparison":""},
    {"model_id":"VC02","model_name":"MLPerf Tiny CIFAR-10 ResNet8","metric":"Top-1 accuracy","fp32":"87.00%","quantized":"87.00%","delta":"+0.0000 pp","published_comparison":""},
    {"model_id":"VC03","model_name":"TensorFlow MobileNetV1 alpha=0.25 224","metric":"Top-1 / Top-5 accuracy","fp32":"49.80% / 74.20%","quantized":"48.00% / 72.80%","delta":"-1.8000 pp / -1.4000 pp","published_comparison":""},
    {"model_id":"VC04","model_name":"TensorFlow MobileNetV1 alpha=0.5 224","metric":"Top-1 / Top-5 accuracy","fp32":"63.30% / 84.90%","quantized":"60.70% / 83.20%","delta":"-2.6000 pp / -1.7000 pp","published_comparison":""},
    {"model_id":"VC05","model_name":"ST MobileNetV2 alpha=0.35 224","metric":"Top-1 accuracy","fp32":"58.13%","quantized":"56.77%","delta":"-1.3600 pp","published_comparison":""},
    {"model_id":"VC06","model_name":"ST MobileNetV2 alpha=0.50 PyTorch 224 QDQ","metric":"Top-1 accuracy","fp32":"66.20%","quantized":"65.31%","delta":"-0.8900 pp","published_comparison":""},
    {"model_id":"VC09","model_name":"ONNX Model Zoo SqueezeNet 1.0 INT8","metric":"Top-1 / Top-5 accuracy","fp32":"56.85% / 79.87%","quantized":"56.48% / 79.76%","delta":"-0.3700 pp / -0.1100 pp","published_comparison":""},
    {"model_id":"VC11","model_name":"Google MediaPipe EfficientNet-Lite0 224 INT8","metric":"Top-1 accuracy","fp32":"75.10%","quantized":"74.40%","delta":"-0.7000 pp","published_comparison":""},
    {"model_id":"VC12","model_name":"ONNX Model Zoo MobileNetV2 1.0 INT8","metric":"Top-1 / Top-5 accuracy","fp32":"69.48% / 89.26%","quantized":"68.30% / 88.44%","delta":"-1.1800 pp / -0.8200 pp","published_comparison":""},
    {"model_id":"VC13","model_name":"ONNX Model Zoo ShuffleNetV2 x1.0 INT8","metric":"Top-1 / Top-5 error","fp32":"33.65% / 13.43%","quantized":"33.85% / 13.66%","delta":"+0.2000 pp / +0.2300 pp","published_comparison":""}
  ]
}