iPhone SE (3rd generation)
Geekbench ML Score
3302
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | May 09 2024 09:32 AM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.4.1 |
| 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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1403
262.6 IPS |
|
|
Image Classification (F16)
|
100% |
1751
327.7 IPS |
|
|
Image Classification (I8)
|
99% |
1750
327.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
814
13.6 IPS |
|
|
Image Segmentation (F16)
|
100% |
813
13.6 IPS |
|
|
Image Segmentation (I8)
|
100% |
813
13.6 IPS |
|
|
Pose Estimation (F32)
|
100% |
5738
6.95 IPS |
|
|
Pose Estimation (F16)
|
100% |
13466
16.3 IPS |
|
|
Pose Estimation (I8)
|
100% |
13530
16.4 IPS |
|
|
Object Detection (F32)
|
100% |
1378
102.9 IPS |
|
|
Object Detection (F16)
|
100% |
1870
139.6 IPS |
|
|
Object Detection (I8)
|
97% |
1372
102.4 IPS |
|
|
Face Detection (F32)
|
100% |
2431
28.9 IPS |
|
|
Face Detection (F16)
|
97% |
3900
46.4 IPS |
|
|
Face Detection (I8)
|
97% |
3880
46.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
4848
37.6 IPS |
|
|
Depth Estimation (F16)
|
100% |
8118
63.0 IPS |
|
|
Depth Estimation (I8)
|
99% |
8125
63.0 IPS |
|
|
Style Transfer (F32)
|
100% |
16252
21.4 IPS |
|
|
Style Transfer (F16)
|
100% |
25123
33.0 IPS |
|
|
Style Transfer (I8)
|
100% |
25131
33.1 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
3723
132.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
4891
174.7 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
4875
174.1 IPS |
|
|
Text Classification (F32)
|
100% |
2218
3.19 KIPS |
|
|
Text Classification (F16)
|
100% |
3282
4.72 KIPS |
|
|
Text Classification (I8)
|
96% |
3328
4.78 KIPS |
|
|
Machine Translation (F32)
|
100% |
1129
20.8 IPS |
|
|
Machine Translation (F16)
|
100% |
1360
25.0 IPS |
|
|
Machine Translation (I8)
|
99% |
1074
19.8 IPS |
