iPhone SE (3rd generation)
Geekbench ML Score
1932
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | June 17 2025 01:13 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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
972
181.9 IPS |
|
|
Image Classification (F16)
|
100% |
917
171.6 IPS |
|
|
Image Classification (I8)
|
99% |
920
172.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
622
10.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
566
9.46 IPS |
|
|
Image Segmentation (I8)
|
100% |
549
9.17 IPS |
|
|
Pose Estimation (F32)
|
100% |
5777
7.00 IPS |
|
|
Pose Estimation (F16)
|
100% |
9643
11.7 IPS |
|
|
Pose Estimation (I8)
|
100% |
9623
11.7 IPS |
|
|
Object Detection (F32)
|
100% |
1029
76.9 IPS |
|
|
Object Detection (F16)
|
100% |
1054
78.7 IPS |
|
|
Object Detection (I8)
|
97% |
1040
77.6 IPS |
|
|
Face Detection (F32)
|
100% |
1738
20.7 IPS |
|
|
Face Detection (F16)
|
100% |
1500
17.8 IPS |
|
|
Face Detection (I8)
|
99% |
1564
18.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
3357
26.0 IPS |
|
|
Depth Estimation (F16)
|
99% |
3675
28.5 IPS |
|
|
Depth Estimation (I8)
|
99% |
3636
28.2 IPS |
|
|
Style Transfer (F32)
|
100% |
10190
13.4 IPS |
|
|
Style Transfer (F16)
|
100% |
11814
15.5 IPS |
|
|
Style Transfer (I8)
|
100% |
11748
15.5 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2544
90.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
2585
92.3 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
2574
91.9 IPS |
|
|
Text Classification (F32)
|
100% |
1013
1.46 KIPS |
|
|
Text Classification (F16)
|
100% |
471
677.4 IPS |
|
|
Text Classification (I8)
|
96% |
622
894.2 IPS |
|
|
Machine Translation (F32)
|
100% |
1344
24.7 IPS |
|
|
Machine Translation (F16)
|
99% |
1758
32.4 IPS |
|
|
Machine Translation (I8)
|
99% |
1310
24.1 IPS |
