iPhone SE (2nd generation)
Geekbench ML Score
1710
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | July 26 2024 12:11 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.0 |
| 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% |
274
51.3 IPS |
|
|
Image Classification (F16)
|
100% |
2662
498.1 IPS |
|
|
Image Classification (I8)
|
99% |
2683
502.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
226
3.78 IPS |
|
|
Image Segmentation (F16)
|
100% |
330
5.52 IPS |
|
|
Image Segmentation (I8)
|
100% |
328
5.48 IPS |
|
|
Pose Estimation (F32)
|
100% |
2281
2.76 IPS |
|
|
Pose Estimation (F16)
|
100% |
26656
32.3 IPS |
|
|
Pose Estimation (I8)
|
100% |
26256
31.8 IPS |
|
|
Object Detection (F32)
|
100% |
490
36.6 IPS |
|
|
Object Detection (F16)
|
100% |
1177
87.9 IPS |
|
|
Object Detection (I8)
|
97% |
504
37.6 IPS |
|
|
Face Detection (F32)
|
100% |
2339
27.8 IPS |
|
|
Face Detection (F16)
|
97% |
4738
56.3 IPS |
|
|
Face Detection (I8)
|
96% |
5002
59.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
2238
17.4 IPS |
|
|
Depth Estimation (F16)
|
100% |
19031
147.6 IPS |
|
|
Depth Estimation (I8)
|
99% |
18055
140.0 IPS |
|
|
Style Transfer (F32)
|
24% |
5665
7.45 IPS |
|
|
Style Transfer (F16)
|
100% |
17652
23.2 IPS |
|
|
Style Transfer (I8)
|
100% |
17576
23.1 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1263
45.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
4437
158.5 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
4409
157.5 IPS |
|
|
Text Classification (F32)
|
100% |
233
334.5 IPS |
|
|
Text Classification (F16)
|
100% |
298
427.6 IPS |
|
|
Text Classification (I8)
|
96% |
329
473.1 IPS |
|
|
Machine Translation (F32)
|
100% |
221
4.07 IPS |
|
|
Machine Translation (F16)
|
100% |
216
3.98 IPS |
|
|
Machine Translation (I8)
|
99% |
221
4.06 IPS |
