iPhone SE (3rd generation)
Geekbench ML Score
1735
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | May 08 2024 10:15 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.0 |
| 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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
942
176.2 IPS |
|
|
Image Classification (F16)
|
100% |
922
172.4 IPS |
|
|
Image Classification (I8)
|
99% |
912
170.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
490
8.19 IPS |
|
|
Image Segmentation (F16)
|
100% |
447
7.47 IPS |
|
|
Image Segmentation (I8)
|
100% |
442
7.38 IPS |
|
|
Pose Estimation (F32)
|
100% |
5171
6.26 IPS |
|
|
Pose Estimation (F16)
|
100% |
10119
12.3 IPS |
|
|
Pose Estimation (I8)
|
100% |
10114
12.2 IPS |
|
|
Object Detection (F32)
|
100% |
938
70.0 IPS |
|
|
Object Detection (F16)
|
100% |
1007
75.1 IPS |
|
|
Object Detection (I8)
|
97% |
952
71.1 IPS |
|
|
Face Detection (F32)
|
100% |
1605
19.1 IPS |
|
|
Face Detection (F16)
|
100% |
1493
17.8 IPS |
|
|
Face Detection (I8)
|
99% |
1414
16.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
3179
24.7 IPS |
|
|
Depth Estimation (F16)
|
99% |
3596
27.9 IPS |
|
|
Depth Estimation (I8)
|
99% |
3525
27.3 IPS |
|
|
Style Transfer (F32)
|
100% |
9835
12.9 IPS |
|
|
Style Transfer (F16)
|
100% |
11604
15.3 IPS |
|
|
Style Transfer (I8)
|
100% |
11661
15.3 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2859
102.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
2528
90.3 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
2517
89.9 IPS |
|
|
Text Classification (F32)
|
100% |
957
1.38 KIPS |
|
|
Text Classification (F16)
|
100% |
601
864.4 IPS |
|
|
Text Classification (I8)
|
96% |
591
849.1 IPS |
|
|
Machine Translation (F32)
|
100% |
729
13.4 IPS |
|
|
Machine Translation (F16)
|
99% |
776
14.3 IPS |
|
|
Machine Translation (I8)
|
99% |
652
12.0 IPS |
