iPhone SE (3rd generation)
Geekbench ML Score
2077
Core ML GPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | May 08 2024 10:30 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.0 |
| 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 | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
471
88.2 IPS |
|
|
Image Classification (F16)
|
100% |
765
143.2 IPS |
|
|
Image Classification (I8)
|
99% |
718
134.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
1122
18.7 IPS |
|
|
Image Segmentation (F16)
|
100% |
1158
19.3 IPS |
|
|
Image Segmentation (I8)
|
100% |
1181
19.7 IPS |
|
|
Pose Estimation (F32)
|
100% |
8732
10.6 IPS |
|
|
Pose Estimation (F16)
|
100% |
9416
11.4 IPS |
|
|
Pose Estimation (I8)
|
100% |
9301
11.3 IPS |
|
|
Object Detection (F32)
|
100% |
1023
76.3 IPS |
|
|
Object Detection (F16)
|
100% |
898
67.0 IPS |
|
|
Object Detection (I8)
|
97% |
984
73.4 IPS |
|
|
Face Detection (F32)
|
100% |
3450
41.0 IPS |
|
|
Face Detection (F16)
|
97% |
4402
52.3 IPS |
|
|
Face Detection (I8)
|
96% |
4296
51.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
7076
54.9 IPS |
|
|
Depth Estimation (F16)
|
100% |
5636
43.7 IPS |
|
|
Depth Estimation (I8)
|
37% |
5434
42.1 IPS |
|
|
Style Transfer (F32)
|
100% |
16011
21.1 IPS |
|
|
Style Transfer (F16)
|
100% |
18634
24.5 IPS |
|
|
Style Transfer (I8)
|
100% |
18538
24.4 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2904
103.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
3040
108.6 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
2967
106.0 IPS |
|
|
Text Classification (F32)
|
100% |
375
538.9 IPS |
|
|
Text Classification (F16)
|
100% |
370
531.3 IPS |
|
|
Text Classification (I8)
|
96% |
377
542.2 IPS |
|
|
Machine Translation (F32)
|
100% |
503
9.25 IPS |
|
|
Machine Translation (F16)
|
100% |
476
8.76 IPS |
|
|
Machine Translation (I8)
|
99% |
475
8.74 IPS |
