iPhone SE (3rd generation)
Geekbench ML Score
4460
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | August 24 2024 05:36 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.6.1 |
| 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% |
659
123.3 IPS |
|
|
Image Classification (F16)
|
100% |
4968
929.7 IPS |
|
|
Image Classification (I8)
|
99% |
5771
1.08 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1185
19.8 IPS |
|
|
Image Segmentation (F16)
|
100% |
1704
28.5 IPS |
|
|
Image Segmentation (I8)
|
100% |
1726
28.8 IPS |
|
|
Pose Estimation (F32)
|
100% |
9029
10.9 IPS |
|
|
Pose Estimation (F16)
|
100% |
70399
85.3 IPS |
|
|
Pose Estimation (I8)
|
100% |
76171
92.2 IPS |
|
|
Object Detection (F32)
|
100% |
1059
79.1 IPS |
|
|
Object Detection (F16)
|
100% |
3318
247.7 IPS |
|
|
Object Detection (I8)
|
97% |
948
70.8 IPS |
|
|
Face Detection (F32)
|
100% |
2845
33.8 IPS |
|
|
Face Detection (F16)
|
97% |
9734
115.7 IPS |
|
|
Face Detection (I8)
|
96% |
9914
117.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
5357
41.5 IPS |
|
|
Depth Estimation (F16)
|
100% |
32055
248.6 IPS |
|
|
Depth Estimation (I8)
|
37% |
31305
242.8 IPS |
|
|
Style Transfer (F32)
|
100% |
16705
22.0 IPS |
|
|
Style Transfer (F16)
|
100% |
98450
129.5 IPS |
|
|
Style Transfer (I8)
|
100% |
93341
122.8 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2552
91.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
13802
492.9 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
15096
539.1 IPS |
|
|
Text Classification (F32)
|
100% |
366
526.6 IPS |
|
|
Text Classification (F16)
|
100% |
830
1.19 KIPS |
|
|
Text Classification (I8)
|
96% |
335
481.9 IPS |
|
|
Machine Translation (F32)
|
100% |
448
8.24 IPS |
|
|
Machine Translation (F16)
|
100% |
1103
20.3 IPS |
|
|
Machine Translation (I8)
|
99% |
472
8.69 IPS |
