iPhone SE (2nd generation)
Geekbench ML Score
1827
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | August 30 2025 04:14 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 16.3.1 |
| 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 | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
290
54.2 IPS |
|
|
Image Classification (F16)
|
100% |
2746
513.9 IPS |
|
|
Image Classification (I8)
|
99% |
2796
523.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
298
4.97 IPS |
|
|
Image Segmentation (F16)
|
100% |
483
8.07 IPS |
|
|
Image Segmentation (I8)
|
100% |
475
7.94 IPS |
|
|
Pose Estimation (F32)
|
100% |
1957
2.37 IPS |
|
|
Pose Estimation (F16)
|
100% |
26400
32.0 IPS |
|
|
Pose Estimation (I8)
|
100% |
26458
32.0 IPS |
|
|
Object Detection (F32)
|
100% |
576
43.0 IPS |
|
|
Object Detection (F16)
|
100% |
1093
81.6 IPS |
|
|
Object Detection (I8)
|
97% |
512
38.2 IPS |
|
|
Face Detection (F32)
|
100% |
2361
28.1 IPS |
|
|
Face Detection (F16)
|
97% |
5109
60.8 IPS |
|
|
Face Detection (I8)
|
96% |
5088
60.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
2447
19.0 IPS |
|
|
Depth Estimation (F16)
|
100% |
19504
151.3 IPS |
|
|
Depth Estimation (I8)
|
99% |
18285
141.8 IPS |
|
|
Style Transfer (F32)
|
24% |
5690
7.48 IPS |
|
|
Style Transfer (F16)
|
100% |
16733
22.0 IPS |
|
|
Style Transfer (I8)
|
100% |
16596
21.8 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1015
36.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
4915
175.5 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
5053
180.5 IPS |
|
|
Text Classification (F32)
|
100% |
243
349.9 IPS |
|
|
Text Classification (F16)
|
100% |
302
434.1 IPS |
|
|
Text Classification (I8)
|
96% |
322
462.2 IPS |
|
|
Machine Translation (F32)
|
100% |
296
5.44 IPS |
|
|
Machine Translation (F16)
|
100% |
234
4.31 IPS |
|
|
Machine Translation (I8)
|
99% |
305
5.62 IPS |
