iPhone SE (2nd generation)
Geekbench ML Score
1725
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | May 18 2024 08:53 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.4.1 |
| 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% |
278
52.0 IPS |
|
|
Image Classification (F16)
|
100% |
2775
519.3 IPS |
|
|
Image Classification (I8)
|
99% |
2811
526.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
231
3.85 IPS |
|
|
Image Segmentation (F16)
|
100% |
337
5.63 IPS |
|
|
Image Segmentation (I8)
|
100% |
334
5.58 IPS |
|
|
Pose Estimation (F32)
|
100% |
2259
2.74 IPS |
|
|
Pose Estimation (F16)
|
100% |
25218
30.5 IPS |
|
|
Pose Estimation (I8)
|
100% |
25514
30.9 IPS |
|
|
Object Detection (F32)
|
100% |
396
29.6 IPS |
|
|
Object Detection (F16)
|
100% |
1097
81.9 IPS |
|
|
Object Detection (I8)
|
97% |
482
36.0 IPS |
|
|
Face Detection (F32)
|
100% |
2395
28.5 IPS |
|
|
Face Detection (F16)
|
98% |
4402
52.3 IPS |
|
|
Face Detection (I8)
|
97% |
4719
56.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
2518
19.5 IPS |
|
|
Depth Estimation (F16)
|
100% |
21241
164.7 IPS |
|
|
Depth Estimation (I8)
|
99% |
23205
180.0 IPS |
|
|
Style Transfer (F32)
|
100% |
5913
7.78 IPS |
|
|
Style Transfer (F16)
|
100% |
17931
23.6 IPS |
|
|
Style Transfer (I8)
|
100% |
18622
24.5 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1221
43.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
5241
187.2 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
5151
183.9 IPS |
|
|
Text Classification (F32)
|
100% |
227
326.5 IPS |
|
|
Text Classification (F16)
|
100% |
284
407.8 IPS |
|
|
Text Classification (I8)
|
96% |
297
426.3 IPS |
|
|
Machine Translation (F32)
|
100% |
208
3.83 IPS |
|
|
Machine Translation (F16)
|
100% |
206
3.80 IPS |
|
|
Machine Translation (I8)
|
99% |
226
4.15 IPS |
