iPhone SE (2nd generation)
Geekbench ML Score
1947
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | July 26 2024 10:15 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 18.0 |
| 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% |
750
140.4 IPS |
|
|
Image Classification (F16)
|
100% |
1380
258.3 IPS |
|
|
Image Classification (I8)
|
99% |
1375
257.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
429
7.17 IPS |
|
|
Image Segmentation (F16)
|
100% |
588
9.82 IPS |
|
|
Image Segmentation (I8)
|
100% |
587
9.80 IPS |
|
|
Pose Estimation (F32)
|
100% |
3287
3.98 IPS |
|
|
Pose Estimation (F16)
|
100% |
6295
7.62 IPS |
|
|
Pose Estimation (I8)
|
100% |
6421
7.78 IPS |
|
|
Object Detection (F32)
|
100% |
704
52.6 IPS |
|
|
Object Detection (F16)
|
100% |
1383
103.3 IPS |
|
|
Object Detection (I8)
|
97% |
713
53.2 IPS |
|
|
Face Detection (F32)
|
100% |
1548
18.4 IPS |
|
|
Face Detection (F16)
|
97% |
3102
36.9 IPS |
|
|
Face Detection (I8)
|
97% |
3113
37.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
3127
24.2 IPS |
|
|
Depth Estimation (F16)
|
100% |
5994
46.5 IPS |
|
|
Depth Estimation (I8)
|
99% |
5991
46.5 IPS |
|
|
Style Transfer (F32)
|
100% |
7605
10.0 IPS |
|
|
Style Transfer (F16)
|
100% |
14051
18.5 IPS |
|
|
Style Transfer (I8)
|
100% |
14205
18.7 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2178
77.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
2859
102.1 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
2837
101.3 IPS |
|
|
Text Classification (F32)
|
100% |
1216
1.75 KIPS |
|
|
Text Classification (F16)
|
100% |
2096
3.01 KIPS |
|
|
Text Classification (I8)
|
96% |
2096
3.01 KIPS |
|
|
Machine Translation (F32)
|
100% |
408
7.52 IPS |
|
|
Machine Translation (F16)
|
100% |
601
11.1 IPS |
|
|
Machine Translation (I8)
|
99% |
424
7.81 IPS |
