iPhone SE (2nd generation)
Geekbench ML Score
941
Core ML GPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | January 18 2024 02:13 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.3 |
| 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% |
267
49.9 IPS |
|
|
Image Classification (F16)
|
100% |
332
62.2 IPS |
|
|
Image Classification (I8)
|
99% |
332
62.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
222
3.70 IPS |
|
|
Image Segmentation (F16)
|
100% |
244
4.08 IPS |
|
|
Image Segmentation (I8)
|
100% |
250
4.17 IPS |
|
|
Pose Estimation (F32)
|
100% |
2255
2.73 IPS |
|
|
Pose Estimation (F16)
|
100% |
3034
3.67 IPS |
|
|
Pose Estimation (I8)
|
100% |
3042
3.68 IPS |
|
|
Object Detection (F32)
|
100% |
541
40.4 IPS |
|
|
Object Detection (F16)
|
100% |
557
41.6 IPS |
|
|
Object Detection (I8)
|
97% |
481
35.9 IPS |
|
|
Face Detection (F32)
|
100% |
2432
28.9 IPS |
|
|
Face Detection (F16)
|
97% |
3099
36.8 IPS |
|
|
Face Detection (I8)
|
96% |
3165
37.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
2497
19.4 IPS |
|
|
Depth Estimation (F16)
|
100% |
3537
27.4 IPS |
|
|
Depth Estimation (I8)
|
99% |
3436
26.6 IPS |
|
|
Style Transfer (F32)
|
24% |
5904
7.77 IPS |
|
|
Style Transfer (F16)
|
30% |
8603
11.3 IPS |
|
|
Style Transfer (I8)
|
30% |
8580
11.3 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1084
38.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1391
49.7 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
1173
41.9 IPS |
|
|
Text Classification (F32)
|
100% |
241
346.6 IPS |
|
|
Text Classification (F16)
|
100% |
306
439.8 IPS |
|
|
Text Classification (I8)
|
96% |
312
448.1 IPS |
|
|
Machine Translation (F32)
|
100% |
222
4.08 IPS |
|
|
Machine Translation (F16)
|
100% |
207
3.82 IPS |
|
|
Machine Translation (I8)
|
99% |
229
4.22 IPS |
