iPhone SE (2nd generation)
Geekbench ML Score
1738
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | October 03 2024 01:59 AM |
| Views | 1 |
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% |
742
138.8 IPS |
|
|
Image Classification (F16)
|
100% |
1122
209.9 IPS |
|
|
Image Classification (I8)
|
99% |
1127
210.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
370
6.17 IPS |
|
|
Image Segmentation (F16)
|
100% |
393
6.56 IPS |
|
|
Image Segmentation (I8)
|
100% |
385
6.43 IPS |
|
|
Pose Estimation (F32)
|
100% |
3285
3.98 IPS |
|
|
Pose Estimation (F16)
|
100% |
6393
7.74 IPS |
|
|
Pose Estimation (I8)
|
100% |
6489
7.86 IPS |
|
|
Object Detection (F32)
|
100% |
666
49.7 IPS |
|
|
Object Detection (F16)
|
100% |
1186
88.5 IPS |
|
|
Object Detection (I8)
|
97% |
668
49.9 IPS |
|
|
Face Detection (F32)
|
100% |
1179
14.0 IPS |
|
|
Face Detection (F16)
|
97% |
2355
28.0 IPS |
|
|
Face Detection (I8)
|
97% |
2372
28.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
2389
18.5 IPS |
|
|
Depth Estimation (F16)
|
100% |
4843
37.6 IPS |
|
|
Depth Estimation (I8)
|
99% |
4867
37.7 IPS |
|
|
Style Transfer (F32)
|
100% |
6768
8.90 IPS |
|
|
Style Transfer (F16)
|
100% |
12545
16.5 IPS |
|
|
Style Transfer (I8)
|
100% |
12492
16.4 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1911
68.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
2641
94.3 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
2608
93.2 IPS |
|
|
Text Classification (F32)
|
100% |
1304
1.87 KIPS |
|
|
Text Classification (F16)
|
100% |
1866
2.68 KIPS |
|
|
Text Classification (I8)
|
96% |
1840
2.64 KIPS |
|
|
Machine Translation (F32)
|
100% |
439
8.08 IPS |
|
|
Machine Translation (F16)
|
100% |
723
13.3 IPS |
|
|
Machine Translation (I8)
|
99% |
575
10.6 IPS |
