iPhone SE (2nd generation)
Geekbench ML Score
1248
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | September 14 2024 11:44 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
100.6 IPS |
|
|
Image Classification (F16)
|
100% |
648
121.3 IPS |
|
|
Image Classification (I8)
|
99% |
661
123.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
419
7.01 IPS |
|
|
Image Segmentation (F16)
|
100% |
420
7.01 IPS |
|
|
Image Segmentation (I8)
|
100% |
420
7.02 IPS |
|
|
Pose Estimation (F32)
|
100% |
3238
3.92 IPS |
|
|
Pose Estimation (F16)
|
100% |
5530
6.70 IPS |
|
|
Pose Estimation (I8)
|
100% |
5527
6.69 IPS |
|
|
Object Detection (F32)
|
100% |
566
42.2 IPS |
|
|
Object Detection (F16)
|
100% |
726
54.2 IPS |
|
|
Object Detection (I8)
|
97% |
567
42.3 IPS |
|
|
Face Detection (F32)
|
100% |
1105
13.1 IPS |
|
|
Face Detection (F16)
|
100% |
1157
13.8 IPS |
|
|
Face Detection (I8)
|
99% |
1150
13.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
1967
15.3 IPS |
|
|
Depth Estimation (F16)
|
99% |
2500
19.4 IPS |
|
|
Depth Estimation (I8)
|
99% |
2500
19.4 IPS |
|
|
Style Transfer (F32)
|
100% |
5521
7.26 IPS |
|
|
Style Transfer (F16)
|
100% |
7556
9.94 IPS |
|
|
Style Transfer (I8)
|
100% |
7559
9.94 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1615
57.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1673
59.8 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
1683
60.1 IPS |
|
|
Text Classification (F32)
|
100% |
648
930.7 IPS |
|
|
Text Classification (F16)
|
100% |
411
591.1 IPS |
|
|
Text Classification (I8)
|
96% |
399
573.3 IPS |
|
|
Machine Translation (F32)
|
100% |
799
14.7 IPS |
|
|
Machine Translation (F16)
|
99% |
1219
22.4 IPS |
|
|
Machine Translation (I8)
|
99% |
743
13.7 IPS |
