iPhone SE (3rd generation)
Geekbench ML Score
4099
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | October 03 2024 08:40 PM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 18.1 |
| Model | iPhone SE (3rd generation) |
| Model ID | iPhone14,6 |
| Motherboard | D49AP |
| CPU Information | |
|---|---|
| Name | Apple A15 Bionic |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 3.23 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| L1 Instruction Cache | 128 KB x 1 |
| L1 Data Cache | 64.0 KB x 1 |
| L2 Cache | 4.00 MB x 1 |
| Memory Information | |
|---|---|
| Size | 3.80 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
632
118.3 IPS |
|
|
Image Classification (F16)
|
100% |
4762
891.1 IPS |
|
|
Image Classification (I8)
|
99% |
5030
941.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
822
13.7 IPS |
|
|
Image Segmentation (F16)
|
100% |
1099
18.4 IPS |
|
|
Image Segmentation (I8)
|
100% |
1107
18.5 IPS |
|
|
Pose Estimation (F32)
|
100% |
6511
7.89 IPS |
|
|
Pose Estimation (F16)
|
100% |
35016
42.4 IPS |
|
|
Pose Estimation (I8)
|
100% |
35849
43.4 IPS |
|
|
Object Detection (F32)
|
100% |
862
64.4 IPS |
|
|
Object Detection (F16)
|
100% |
2693
201.0 IPS |
|
|
Object Detection (I8)
|
97% |
799
59.7 IPS |
|
|
Face Detection (F32)
|
100% |
3188
37.9 IPS |
|
|
Face Detection (F16)
|
97% |
8811
104.8 IPS |
|
|
Face Detection (I8)
|
96% |
8833
105.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
6710
52.0 IPS |
|
|
Depth Estimation (F16)
|
100% |
29684
230.2 IPS |
|
|
Depth Estimation (I8)
|
37% |
30714
238.2 IPS |
|
|
Style Transfer (F32)
|
100% |
14599
19.2 IPS |
|
|
Style Transfer (F16)
|
100% |
63344
83.3 IPS |
|
|
Style Transfer (I8)
|
100% |
65886
86.7 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2815
100.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
15053
537.6 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
15512
554.0 IPS |
|
|
Text Classification (F32)
|
100% |
1061
1.53 KIPS |
|
|
Text Classification (F16)
|
100% |
1727
2.48 KIPS |
|
|
Text Classification (I8)
|
96% |
1754
2.52 KIPS |
|
|
Machine Translation (F32)
|
100% |
242
4.45 IPS |
|
|
Machine Translation (F16)
|
100% |
984
18.1 IPS |
|
|
Machine Translation (I8)
|
99% |
225
4.15 IPS |
