iPhone SE (3rd generation)
Geekbench ML Score
1742
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | September 17 2024 01:25 PM |
| 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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
571
106.8 IPS |
|
|
Image Classification (F16)
|
100% |
1015
189.9 IPS |
|
|
Image Classification (I8)
|
99% |
1006
188.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
505
8.44 IPS |
|
|
Image Segmentation (F16)
|
100% |
593
9.90 IPS |
|
|
Image Segmentation (I8)
|
100% |
592
9.89 IPS |
|
|
Pose Estimation (F32)
|
100% |
2865
3.47 IPS |
|
|
Pose Estimation (F16)
|
100% |
6199
7.51 IPS |
|
|
Pose Estimation (I8)
|
100% |
6184
7.49 IPS |
|
|
Object Detection (F32)
|
100% |
580
43.3 IPS |
|
|
Object Detection (F16)
|
100% |
1002
74.8 IPS |
|
|
Object Detection (I8)
|
97% |
596
44.5 IPS |
|
|
Face Detection (F32)
|
100% |
1548
18.4 IPS |
|
|
Face Detection (F16)
|
97% |
2553
30.4 IPS |
|
|
Face Detection (I8)
|
97% |
2551
30.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
2448
19.0 IPS |
|
|
Depth Estimation (F16)
|
100% |
4929
38.2 IPS |
|
|
Depth Estimation (I8)
|
99% |
4915
38.1 IPS |
|
|
Style Transfer (F32)
|
100% |
7811
10.3 IPS |
|
|
Style Transfer (F16)
|
100% |
11828
15.6 IPS |
|
|
Style Transfer (I8)
|
100% |
10055
13.2 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1825
65.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
2253
80.5 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
2296
82.0 IPS |
|
|
Text Classification (F32)
|
100% |
1045
1.50 KIPS |
|
|
Text Classification (F16)
|
100% |
1828
2.63 KIPS |
|
|
Text Classification (I8)
|
96% |
1835
2.64 KIPS |
|
|
Machine Translation (F32)
|
100% |
595
11.0 IPS |
|
|
Machine Translation (F16)
|
100% |
669
12.3 IPS |
|
|
Machine Translation (I8)
|
99% |
595
11.0 IPS |
