iPhone SE (2nd generation)
Geekbench ML Score
1238
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | September 14 2024 11:50 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 16.2 |
| Model | iPhone SE (2nd generation) |
| Model ID | iPhone12,8 |
| Motherboard | D79AP |
| CPU Information | |
|---|---|
| Name | Apple A13 Bionic |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 2.66 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| L1 Instruction Cache | 96.0 KB x 1 |
| L1 Data Cache | 48.0 KB x 1 |
| L2 Cache | 4.00 MB x 1 |
| Memory Information | |
|---|---|
| Size | 2.89 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
538
100.7 IPS |
|
|
Image Classification (F16)
|
100% |
643
120.3 IPS |
|
|
Image Classification (I8)
|
99% |
647
121.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
422
7.04 IPS |
|
|
Image Segmentation (F16)
|
100% |
416
6.95 IPS |
|
|
Image Segmentation (I8)
|
100% |
417
6.97 IPS |
|
|
Pose Estimation (F32)
|
100% |
3213
3.89 IPS |
|
|
Pose Estimation (F16)
|
100% |
5546
6.72 IPS |
|
|
Pose Estimation (I8)
|
100% |
5549
6.72 IPS |
|
|
Object Detection (F32)
|
100% |
569
42.5 IPS |
|
|
Object Detection (F16)
|
100% |
735
54.9 IPS |
|
|
Object Detection (I8)
|
97% |
571
42.6 IPS |
|
|
Face Detection (F32)
|
100% |
1104
13.1 IPS |
|
|
Face Detection (F16)
|
100% |
1147
13.6 IPS |
|
|
Face Detection (I8)
|
99% |
1130
13.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
1944
15.1 IPS |
|
|
Depth Estimation (F16)
|
99% |
2496
19.4 IPS |
|
|
Depth Estimation (I8)
|
99% |
2459
19.1 IPS |
|
|
Style Transfer (F32)
|
100% |
5410
7.12 IPS |
|
|
Style Transfer (F16)
|
100% |
7525
9.90 IPS |
|
|
Style Transfer (I8)
|
100% |
7538
9.92 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1623
57.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1687
60.3 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
1667
59.5 IPS |
|
|
Text Classification (F32)
|
100% |
646
928.9 IPS |
|
|
Text Classification (F16)
|
100% |
400
575.4 IPS |
|
|
Text Classification (I8)
|
96% |
413
593.8 IPS |
|
|
Machine Translation (F32)
|
100% |
760
14.0 IPS |
|
|
Machine Translation (F16)
|
99% |
1163
21.4 IPS |
|
|
Machine Translation (I8)
|
99% |
702
12.9 IPS |
