iPhone SE (2nd generation)
Geekbench ML Score
1167
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | July 25 2024 08:36 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.5.1 |
| 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% |
700
130.9 IPS |
|
|
Image Classification (F16)
|
100% |
1090
204.0 IPS |
|
|
Image Classification (I8)
|
99% |
1085
203.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
311
5.20 IPS |
|
|
Image Segmentation (F16)
|
100% |
344
5.74 IPS |
|
|
Image Segmentation (I8)
|
100% |
324
5.42 IPS |
|
|
Pose Estimation (F32)
|
100% |
2965
3.59 IPS |
|
|
Pose Estimation (F16)
|
100% |
5884
7.13 IPS |
|
|
Pose Estimation (I8)
|
100% |
5513
6.68 IPS |
|
|
Object Detection (F32)
|
100% |
616
46.0 IPS |
|
|
Object Detection (F16)
|
100% |
1096
81.9 IPS |
|
|
Object Detection (I8)
|
97% |
608
45.4 IPS |
|
|
Face Detection (F32)
|
100% |
1080
12.8 IPS |
|
|
Face Detection (F16)
|
97% |
2095
24.9 IPS |
|
|
Face Detection (I8)
|
97% |
1885
22.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
2124
16.5 IPS |
|
|
Depth Estimation (F16)
|
100% |
3241
25.1 IPS |
|
|
Depth Estimation (I8)
|
99% |
3194
24.8 IPS |
|
|
Style Transfer (F32)
|
100% |
3477
4.57 IPS |
|
|
Style Transfer (F16)
|
100% |
4655
6.12 IPS |
|
|
Style Transfer (I8)
|
100% |
2757
3.63 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
344
12.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1033
36.9 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
1423
50.8 IPS |
|
|
Text Classification (F32)
|
100% |
840
1.21 KIPS |
|
|
Text Classification (F16)
|
100% |
1613
2.32 KIPS |
|
|
Text Classification (I8)
|
96% |
1763
2.53 KIPS |
|
|
Machine Translation (F32)
|
100% |
137
2.52 IPS |
|
|
Machine Translation (F16)
|
100% |
423
7.79 IPS |
|
|
Machine Translation (I8)
|
99% |
314
5.77 IPS |
