iPhone SE (2nd generation)
Geekbench ML Score
1774
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | January 21 2024 01:44 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.3 |
| 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% |
275
51.4 IPS |
|
|
Image Classification (F16)
|
100% |
2868
536.8 IPS |
|
|
Image Classification (I8)
|
99% |
2894
541.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
219
3.66 IPS |
|
|
Image Segmentation (F16)
|
100% |
333
5.57 IPS |
|
|
Image Segmentation (I8)
|
100% |
332
5.55 IPS |
|
|
Pose Estimation (F32)
|
100% |
2257
2.73 IPS |
|
|
Pose Estimation (F16)
|
100% |
26576
32.2 IPS |
|
|
Pose Estimation (I8)
|
100% |
26171
31.7 IPS |
|
|
Object Detection (F32)
|
100% |
512
38.3 IPS |
|
|
Object Detection (F16)
|
100% |
1202
89.7 IPS |
|
|
Object Detection (I8)
|
97% |
511
38.1 IPS |
|
|
Face Detection (F32)
|
100% |
2398
28.5 IPS |
|
|
Face Detection (F16)
|
97% |
4868
57.9 IPS |
|
|
Face Detection (I8)
|
96% |
5010
59.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
2445
19.0 IPS |
|
|
Depth Estimation (F16)
|
100% |
20661
160.2 IPS |
|
|
Depth Estimation (I8)
|
99% |
21076
163.4 IPS |
|
|
Style Transfer (F32)
|
24% |
5838
7.68 IPS |
|
|
Style Transfer (F16)
|
100% |
18991
25.0 IPS |
|
|
Style Transfer (I8)
|
100% |
18794
24.7 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1022
36.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
5094
181.9 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
5641
201.5 IPS |
|
|
Text Classification (F32)
|
100% |
238
341.5 IPS |
|
|
Text Classification (F16)
|
100% |
320
459.5 IPS |
|
|
Text Classification (I8)
|
96% |
334
479.7 IPS |
|
|
Machine Translation (F32)
|
100% |
227
4.17 IPS |
|
|
Machine Translation (F16)
|
100% |
215
3.96 IPS |
|
|
Machine Translation (I8)
|
99% |
228
4.20 IPS |
