iPhone SE (2nd generation)
Geekbench ML Score
765
Core ML GPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | July 25 2024 09:08 PM |
| 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 | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
268
50.1 IPS |
|
|
Image Classification (F16)
|
100% |
339
63.4 IPS |
|
|
Image Classification (I8)
|
99% |
337
63.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
176
2.94 IPS |
|
|
Image Segmentation (F16)
|
100% |
173
2.89 IPS |
|
|
Image Segmentation (I8)
|
100% |
181
3.03 IPS |
|
|
Pose Estimation (F32)
|
100% |
1322
1.60 IPS |
|
|
Pose Estimation (F16)
|
100% |
2030
2.46 IPS |
|
|
Pose Estimation (I8)
|
100% |
2018
2.44 IPS |
|
|
Object Detection (F32)
|
100% |
476
35.6 IPS |
|
|
Object Detection (F16)
|
100% |
449
33.5 IPS |
|
|
Object Detection (I8)
|
97% |
547
40.8 IPS |
|
|
Face Detection (F32)
|
100% |
1726
20.5 IPS |
|
|
Face Detection (F16)
|
98% |
2230
26.5 IPS |
|
|
Face Detection (I8)
|
97% |
2264
26.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
1740
13.5 IPS |
|
|
Depth Estimation (F16)
|
100% |
2532
19.6 IPS |
|
|
Depth Estimation (I8)
|
99% |
2516
19.5 IPS |
|
|
Style Transfer (F32)
|
100% |
3809
5.01 IPS |
|
|
Style Transfer (F16)
|
100% |
5946
7.82 IPS |
|
|
Style Transfer (I8)
|
100% |
5985
7.87 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1051
37.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1201
42.9 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
1350
48.2 IPS |
|
|
Text Classification (F32)
|
100% |
220
316.9 IPS |
|
|
Text Classification (F16)
|
100% |
280
402.5 IPS |
|
|
Text Classification (I8)
|
96% |
243
349.0 IPS |
|
|
Machine Translation (F32)
|
100% |
213
3.92 IPS |
|
|
Machine Translation (F16)
|
100% |
196
3.61 IPS |
|
|
Machine Translation (I8)
|
99% |
225
4.13 IPS |
