iPhone SE (3rd generation)
Geekbench ML Score
2111
Core ML GPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | September 15 2024 02:59 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 18.0 |
| 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 | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
823
154.0 IPS |
|
|
Image Classification (F16)
|
100% |
733
137.2 IPS |
|
|
Image Classification (I8)
|
99% |
568
106.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
810
13.5 IPS |
|
|
Image Segmentation (F16)
|
100% |
843
14.1 IPS |
|
|
Image Segmentation (I8)
|
100% |
834
13.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
8510
10.3 IPS |
|
|
Pose Estimation (F16)
|
100% |
8383
10.2 IPS |
|
|
Pose Estimation (I8)
|
100% |
9392
11.4 IPS |
|
|
Object Detection (F32)
|
100% |
833
62.2 IPS |
|
|
Object Detection (F16)
|
100% |
828
61.8 IPS |
|
|
Object Detection (I8)
|
97% |
803
60.0 IPS |
|
|
Face Detection (F32)
|
100% |
3218
38.3 IPS |
|
|
Face Detection (F16)
|
98% |
3801
45.2 IPS |
|
|
Face Detection (I8)
|
97% |
3822
45.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
6228
48.3 IPS |
|
|
Depth Estimation (F16)
|
100% |
5985
46.4 IPS |
|
|
Depth Estimation (I8)
|
99% |
6021
46.7 IPS |
|
|
Style Transfer (F32)
|
100% |
16099
21.2 IPS |
|
|
Style Transfer (F16)
|
100% |
17833
23.5 IPS |
|
|
Style Transfer (I8)
|
100% |
18877
24.8 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2761
98.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
2961
105.8 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
3030
108.2 IPS |
|
|
Text Classification (F32)
|
100% |
1066
1.53 KIPS |
|
|
Text Classification (F16)
|
100% |
1827
2.63 KIPS |
|
|
Text Classification (I8)
|
96% |
1829
2.63 KIPS |
|
|
Machine Translation (F32)
|
100% |
253
4.65 IPS |
|
|
Machine Translation (F16)
|
100% |
244
4.49 IPS |
|
|
Machine Translation (I8)
|
99% |
243
4.47 IPS |
