iPhone SE (3rd generation)
Geekbench ML Score
2023
Core ML GPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | June 17 2025 01:16 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 16.5.1 |
| 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 | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1079
201.8 IPS |
|
|
Image Classification (F16)
|
100% |
530
99.2 IPS |
|
|
Image Classification (I8)
|
99% |
500
93.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
501
8.37 IPS |
|
|
Image Segmentation (F16)
|
100% |
511
8.53 IPS |
|
|
Image Segmentation (I8)
|
100% |
506
8.44 IPS |
|
|
Pose Estimation (F32)
|
100% |
9154
11.1 IPS |
|
|
Pose Estimation (F16)
|
100% |
8954
10.8 IPS |
|
|
Pose Estimation (I8)
|
100% |
9754
11.8 IPS |
|
|
Object Detection (F32)
|
100% |
1089
81.3 IPS |
|
|
Object Detection (F16)
|
100% |
774
57.8 IPS |
|
|
Object Detection (I8)
|
97% |
1180
88.1 IPS |
|
|
Face Detection (F32)
|
100% |
3708
44.1 IPS |
|
|
Face Detection (F16)
|
97% |
3760
44.7 IPS |
|
|
Face Detection (I8)
|
96% |
5087
60.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
5953
46.2 IPS |
|
|
Depth Estimation (F16)
|
100% |
7104
55.1 IPS |
|
|
Depth Estimation (I8)
|
99% |
8301
64.4 IPS |
|
|
Style Transfer (F32)
|
100% |
16722
22.0 IPS |
|
|
Style Transfer (F16)
|
100% |
19501
25.7 IPS |
|
|
Style Transfer (I8)
|
100% |
19433
25.6 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2561
91.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
2921
104.3 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
1664
59.4 IPS |
|
|
Text Classification (F32)
|
100% |
631
907.2 IPS |
|
|
Text Classification (F16)
|
100% |
387
556.6 IPS |
|
|
Text Classification (I8)
|
96% |
393
565.4 IPS |
|
|
Machine Translation (F32)
|
100% |
633
11.6 IPS |
|
|
Machine Translation (F16)
|
100% |
691
12.7 IPS |
|
|
Machine Translation (I8)
|
99% |
632
11.6 IPS |
