iPhone SE (3rd generation)
Geekbench ML Score
1934
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | January 17 2025 08:51 AM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 16.6.1 |
| 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% |
959
179.5 IPS |
|
|
Image Classification (F16)
|
100% |
903
169.0 IPS |
|
|
Image Classification (I8)
|
99% |
909
170.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
635
10.6 IPS |
|
|
Image Segmentation (F16)
|
100% |
577
9.64 IPS |
|
|
Image Segmentation (I8)
|
100% |
571
9.53 IPS |
|
|
Pose Estimation (F32)
|
100% |
5795
7.02 IPS |
|
|
Pose Estimation (F16)
|
100% |
9381
11.4 IPS |
|
|
Pose Estimation (I8)
|
100% |
9232
11.2 IPS |
|
|
Object Detection (F32)
|
100% |
1011
75.5 IPS |
|
|
Object Detection (F16)
|
100% |
1044
77.9 IPS |
|
|
Object Detection (I8)
|
97% |
1012
75.6 IPS |
|
|
Face Detection (F32)
|
100% |
1760
20.9 IPS |
|
|
Face Detection (F16)
|
100% |
1619
19.3 IPS |
|
|
Face Detection (I8)
|
99% |
1616
19.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
3415
26.5 IPS |
|
|
Depth Estimation (F16)
|
99% |
3702
28.7 IPS |
|
|
Depth Estimation (I8)
|
99% |
3654
28.3 IPS |
|
|
Style Transfer (F32)
|
100% |
10324
13.6 IPS |
|
|
Style Transfer (F16)
|
100% |
11788
15.5 IPS |
|
|
Style Transfer (I8)
|
100% |
11797
15.5 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2520
90.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
2543
90.8 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
2535
90.5 IPS |
|
|
Text Classification (F32)
|
100% |
987
1.42 KIPS |
|
|
Text Classification (F16)
|
100% |
470
676.1 IPS |
|
|
Text Classification (I8)
|
96% |
613
880.3 IPS |
|
|
Machine Translation (F32)
|
100% |
1335
24.6 IPS |
|
|
Machine Translation (F16)
|
99% |
1796
33.1 IPS |
|
|
Machine Translation (I8)
|
99% |
1332
24.5 IPS |
