iPhone SE (3rd generation)
Geekbench ML Score
1756
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | September 15 2024 02:50 AM |
| Views | 2 |
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% |
569
106.4 IPS |
|
|
Image Classification (F16)
|
100% |
1052
196.9 IPS |
|
|
Image Classification (I8)
|
99% |
1027
192.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
514
8.59 IPS |
|
|
Image Segmentation (F16)
|
100% |
602
10.1 IPS |
|
|
Image Segmentation (I8)
|
100% |
598
9.99 IPS |
|
|
Pose Estimation (F32)
|
100% |
2878
3.49 IPS |
|
|
Pose Estimation (F16)
|
100% |
6155
7.45 IPS |
|
|
Pose Estimation (I8)
|
100% |
6060
7.34 IPS |
|
|
Object Detection (F32)
|
100% |
606
45.2 IPS |
|
|
Object Detection (F16)
|
100% |
1000
74.6 IPS |
|
|
Object Detection (I8)
|
97% |
602
45.0 IPS |
|
|
Face Detection (F32)
|
100% |
1588
18.9 IPS |
|
|
Face Detection (F16)
|
97% |
2539
30.2 IPS |
|
|
Face Detection (I8)
|
97% |
2539
30.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
2428
18.8 IPS |
|
|
Depth Estimation (F16)
|
100% |
4761
36.9 IPS |
|
|
Depth Estimation (I8)
|
99% |
4774
37.0 IPS |
|
|
Style Transfer (F32)
|
100% |
7708
10.1 IPS |
|
|
Style Transfer (F16)
|
100% |
11778
15.5 IPS |
|
|
Style Transfer (I8)
|
100% |
11866
15.6 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1859
66.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
2243
80.1 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
2285
81.6 IPS |
|
|
Text Classification (F32)
|
100% |
1062
1.53 KIPS |
|
|
Text Classification (F16)
|
100% |
1822
2.62 KIPS |
|
|
Text Classification (I8)
|
96% |
1828
2.63 KIPS |
|
|
Machine Translation (F32)
|
100% |
597
11.0 IPS |
|
|
Machine Translation (F16)
|
100% |
674
12.4 IPS |
|
|
Machine Translation (I8)
|
99% |
594
10.9 IPS |
