iPhone SE (2nd generation)
Geekbench ML Score
1992
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | November 08 2025 11:16 PM |
| Views | 8 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 26.1 |
| Model | iPhone SE (2nd generation) |
| Model ID | iPhone12,8 |
| Motherboard | D79AP |
| CPU Information | |
|---|---|
| Name | Apple A13 Bionic |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 2.66 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| L1 Instruction Cache | 96.0 KB x 1 |
| L1 Data Cache | 48.0 KB x 1 |
| L2 Cache | 4.00 MB x 1 |
| Memory Information | |
|---|---|
| Size | 2.89 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
792
148.2 IPS |
|
|
Image Classification (F16)
|
100% |
1324
247.8 IPS |
|
|
Image Classification (I8)
|
99% |
1321
247.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
419
7.00 IPS |
|
|
Image Segmentation (F16)
|
100% |
521
8.71 IPS |
|
|
Image Segmentation (I8)
|
100% |
518
8.65 IPS |
|
|
Pose Estimation (F32)
|
100% |
3476
4.21 IPS |
|
|
Pose Estimation (F16)
|
100% |
6439
7.80 IPS |
|
|
Pose Estimation (I8)
|
100% |
6218
7.53 IPS |
|
|
Object Detection (F32)
|
100% |
730
54.5 IPS |
|
|
Object Detection (F16)
|
100% |
1368
102.1 IPS |
|
|
Object Detection (I8)
|
97% |
752
56.2 IPS |
|
|
Face Detection (F32)
|
100% |
1541
18.3 IPS |
|
|
Face Detection (F16)
|
97% |
2950
35.1 IPS |
|
|
Face Detection (I8)
|
96% |
2991
35.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
3071
23.8 IPS |
|
|
Depth Estimation (F16)
|
100% |
5820
45.1 IPS |
|
|
Depth Estimation (I8)
|
99% |
5812
45.1 IPS |
|
|
Style Transfer (F32)
|
100% |
7421
9.76 IPS |
|
|
Style Transfer (F16)
|
100% |
14164
18.6 IPS |
|
|
Style Transfer (I8)
|
100% |
14021
18.4 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2011
71.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
2834
101.2 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
2857
102.0 IPS |
|
|
Text Classification (F32)
|
100% |
1282
1.84 KIPS |
|
|
Text Classification (F16)
|
100% |
2087
3.00 KIPS |
|
|
Text Classification (I8)
|
96% |
2032
2.92 KIPS |
|
|
Machine Translation (F32)
|
100% |
640
11.8 IPS |
|
|
Machine Translation (F16)
|
100% |
850
15.6 IPS |
|
|
Machine Translation (I8)
|
99% |
581
10.7 IPS |
