iPhone SE (2nd generation)
Geekbench ML Score
1628
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | July 25 2024 09:12 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.5.1 |
| 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% |
277
51.8 IPS |
|
|
Image Classification (F16)
|
100% |
2631
492.2 IPS |
|
|
Image Classification (I8)
|
99% |
2644
494.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
194
3.24 IPS |
|
|
Image Segmentation (F16)
|
100% |
278
4.64 IPS |
|
|
Image Segmentation (I8)
|
100% |
275
4.59 IPS |
|
|
Pose Estimation (F32)
|
100% |
1858
2.25 IPS |
|
|
Pose Estimation (F16)
|
100% |
25471
30.8 IPS |
|
|
Pose Estimation (I8)
|
100% |
25428
30.8 IPS |
|
|
Object Detection (F32)
|
100% |
468
35.0 IPS |
|
|
Object Detection (F16)
|
100% |
1150
85.8 IPS |
|
|
Object Detection (I8)
|
97% |
395
29.5 IPS |
|
|
Face Detection (F32)
|
100% |
2280
27.1 IPS |
|
|
Face Detection (F16)
|
98% |
4807
57.2 IPS |
|
|
Face Detection (I8)
|
97% |
4707
56.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
2178
16.9 IPS |
|
|
Depth Estimation (F16)
|
100% |
18871
146.3 IPS |
|
|
Depth Estimation (I8)
|
99% |
20569
159.5 IPS |
|
|
Style Transfer (F32)
|
100% |
4937
6.49 IPS |
|
|
Style Transfer (F16)
|
100% |
18022
23.7 IPS |
|
|
Style Transfer (I8)
|
100% |
17334
22.8 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1019
36.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
4335
154.8 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
5143
183.7 IPS |
|
|
Text Classification (F32)
|
100% |
233
335.5 IPS |
|
|
Text Classification (F16)
|
100% |
293
421.2 IPS |
|
|
Text Classification (I8)
|
96% |
294
422.4 IPS |
|
|
Machine Translation (F32)
|
100% |
213
3.92 IPS |
|
|
Machine Translation (F16)
|
100% |
213
3.92 IPS |
|
|
Machine Translation (I8)
|
99% |
223
4.10 IPS |
