iPhone SE (2nd generation)
Geekbench ML Score
1151
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | March 27 2024 07:42 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.3.1 |
| 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% |
644
120.6 IPS |
|
|
Image Classification (I8)
|
99% |
641
119.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
303
5.06 IPS |
|
|
Image Segmentation (F16)
|
100% |
300
5.01 IPS |
|
|
Image Segmentation (I8)
|
100% |
300
5.01 IPS |
|
|
Pose Estimation (F32)
|
100% |
3273
3.96 IPS |
|
|
Pose Estimation (F16)
|
100% |
5507
6.67 IPS |
|
|
Pose Estimation (I8)
|
100% |
5497
6.66 IPS |
|
|
Object Detection (F32)
|
100% |
554
41.3 IPS |
|
|
Object Detection (F16)
|
100% |
713
53.2 IPS |
|
|
Object Detection (I8)
|
97% |
563
42.0 IPS |
|
|
Face Detection (F32)
|
100% |
1141
13.6 IPS |
|
|
Face Detection (F16)
|
100% |
1148
13.7 IPS |
|
|
Face Detection (I8)
|
99% |
1146
13.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
2026
15.7 IPS |
|
|
Depth Estimation (F16)
|
99% |
2549
19.8 IPS |
|
|
Depth Estimation (I8)
|
99% |
2530
19.6 IPS |
|
|
Style Transfer (F32)
|
100% |
5611
7.38 IPS |
|
|
Style Transfer (F16)
|
100% |
7702
10.1 IPS |
|
|
Style Transfer (I8)
|
100% |
7714
10.1 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1762
62.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1758
62.8 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
1735
62.0 IPS |
|
|
Text Classification (F32)
|
100% |
650
934.1 IPS |
|
|
Text Classification (F16)
|
100% |
396
569.6 IPS |
|
|
Text Classification (I8)
|
96% |
396
569.8 IPS |
|
|
Machine Translation (F32)
|
100% |
508
9.35 IPS |
|
|
Machine Translation (F16)
|
99% |
611
11.2 IPS |
|
|
Machine Translation (I8)
|
99% |
465
8.56 IPS |
