iPhone SE (3rd generation)
Geekbench ML Score
2442
Core ML GPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | July 13 2024 03:56 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 | 3.79 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
590
110.4 IPS |
|
|
Image Classification (F16)
|
100% |
571
106.9 IPS |
|
|
Image Classification (I8)
|
99% |
743
139.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
1079
18.0 IPS |
|
|
Image Segmentation (F16)
|
100% |
1149
19.2 IPS |
|
|
Image Segmentation (I8)
|
100% |
1171
19.6 IPS |
|
|
Pose Estimation (F32)
|
100% |
8725
10.6 IPS |
|
|
Pose Estimation (F16)
|
100% |
9931
12.0 IPS |
|
|
Pose Estimation (I8)
|
100% |
9530
11.5 IPS |
|
|
Object Detection (F32)
|
100% |
1013
75.6 IPS |
|
|
Object Detection (F16)
|
100% |
1013
75.6 IPS |
|
|
Object Detection (I8)
|
97% |
829
61.9 IPS |
|
|
Face Detection (F32)
|
100% |
3730
44.4 IPS |
|
|
Face Detection (F16)
|
98% |
4367
51.9 IPS |
|
|
Face Detection (I8)
|
97% |
4825
57.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
6190
48.0 IPS |
|
|
Depth Estimation (F16)
|
100% |
6309
48.9 IPS |
|
|
Depth Estimation (I8)
|
99% |
5735
44.5 IPS |
|
|
Style Transfer (F32)
|
100% |
16749
22.0 IPS |
|
|
Style Transfer (F16)
|
100% |
19614
25.8 IPS |
|
|
Style Transfer (I8)
|
100% |
19506
25.7 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2966
105.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
3183
113.7 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
3237
115.6 IPS |
|
|
Text Classification (F32)
|
100% |
2106
3.03 KIPS |
|
|
Text Classification (F16)
|
100% |
3566
5.13 KIPS |
|
|
Text Classification (I8)
|
96% |
3593
5.16 KIPS |
|
|
Machine Translation (F32)
|
100% |
278
5.11 IPS |
|
|
Machine Translation (F16)
|
100% |
271
4.98 IPS |
|
|
Machine Translation (I8)
|
99% |
242
4.46 IPS |
