iPhone SE (2nd generation)
Geekbench ML Score
1003
Core ML GPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| User | Skyforger |
| Upload Date | August 30 2025 04:34 AM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 16.3.1 |
| 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 | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
280
52.3 IPS |
|
|
Image Classification (F16)
|
100% |
341
63.8 IPS |
|
|
Image Classification (I8)
|
99% |
339
63.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
297
4.96 IPS |
|
|
Image Segmentation (F16)
|
100% |
322
5.38 IPS |
|
|
Image Segmentation (I8)
|
100% |
328
5.48 IPS |
|
|
Pose Estimation (F32)
|
100% |
2199
2.66 IPS |
|
|
Pose Estimation (F16)
|
100% |
3152
3.82 IPS |
|
|
Pose Estimation (I8)
|
100% |
3104
3.76 IPS |
|
|
Object Detection (F32)
|
100% |
565
42.1 IPS |
|
|
Object Detection (F16)
|
100% |
554
41.3 IPS |
|
|
Object Detection (I8)
|
97% |
518
38.7 IPS |
|
|
Face Detection (F32)
|
100% |
2504
29.8 IPS |
|
|
Face Detection (F16)
|
97% |
3095
36.8 IPS |
|
|
Face Detection (I8)
|
96% |
2935
34.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
2282
17.7 IPS |
|
|
Depth Estimation (F16)
|
100% |
3132
24.3 IPS |
|
|
Depth Estimation (I8)
|
99% |
3304
25.6 IPS |
|
|
Style Transfer (F32)
|
24% |
5421
7.13 IPS |
|
|
Style Transfer (F16)
|
30% |
7301
9.60 IPS |
|
|
Style Transfer (I8)
|
30% |
7328
9.64 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1191
42.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1499
53.5 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
1490
53.2 IPS |
|
|
Text Classification (F32)
|
100% |
249
357.9 IPS |
|
|
Text Classification (F16)
|
100% |
323
463.6 IPS |
|
|
Text Classification (I8)
|
96% |
323
463.6 IPS |
|
|
Machine Translation (F32)
|
100% |
312
5.73 IPS |
|
|
Machine Translation (F16)
|
100% |
301
5.53 IPS |
|
|
Machine Translation (I8)
|
99% |
313
5.77 IPS |
