iPhone SE (3rd generation)
Geekbench ML Score
3176
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | September 12 2024 03:56 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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1398
261.6 IPS |
|
|
Image Classification (F16)
|
100% |
1745
326.5 IPS |
|
|
Image Classification (I8)
|
99% |
1741
325.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
799
13.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
782
13.1 IPS |
|
|
Image Segmentation (I8)
|
100% |
664
11.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
4979
6.03 IPS |
|
|
Pose Estimation (F16)
|
100% |
12940
15.7 IPS |
|
|
Pose Estimation (I8)
|
100% |
12690
15.4 IPS |
|
|
Object Detection (F32)
|
100% |
1321
98.6 IPS |
|
|
Object Detection (F16)
|
100% |
1820
135.8 IPS |
|
|
Object Detection (I8)
|
97% |
1337
99.8 IPS |
|
|
Face Detection (F32)
|
100% |
2329
27.7 IPS |
|
|
Face Detection (F16)
|
97% |
3745
44.5 IPS |
|
|
Face Detection (I8)
|
97% |
3696
43.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
4721
36.6 IPS |
|
|
Depth Estimation (F16)
|
100% |
8034
62.3 IPS |
|
|
Depth Estimation (I8)
|
99% |
7915
61.4 IPS |
|
|
Style Transfer (F32)
|
100% |
15875
20.9 IPS |
|
|
Style Transfer (F16)
|
100% |
24908
32.8 IPS |
|
|
Style Transfer (I8)
|
100% |
24805
32.6 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
3715
132.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
4833
172.6 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
4850
173.2 IPS |
|
|
Text Classification (F32)
|
100% |
2146
3.08 KIPS |
|
|
Text Classification (F16)
|
100% |
3087
4.44 KIPS |
|
|
Text Classification (I8)
|
96% |
3076
4.42 KIPS |
|
|
Machine Translation (F32)
|
100% |
1092
20.1 IPS |
|
|
Machine Translation (F16)
|
100% |
1295
23.8 IPS |
|
|
Machine Translation (I8)
|
99% |
1039
19.1 IPS |
