iPhone SE (2nd generation)
Geekbench ML Score
1624
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | May 22 2024 03:31 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% |
276
51.6 IPS |
|
|
Image Classification (F16)
|
100% |
2637
493.4 IPS |
|
|
Image Classification (I8)
|
99% |
2614
489.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
208
3.47 IPS |
|
|
Image Segmentation (F16)
|
100% |
247
4.12 IPS |
|
|
Image Segmentation (I8)
|
100% |
246
4.10 IPS |
|
|
Pose Estimation (F32)
|
100% |
2222
2.69 IPS |
|
|
Pose Estimation (F16)
|
100% |
22067
26.7 IPS |
|
|
Pose Estimation (I8)
|
100% |
21908
26.5 IPS |
|
|
Object Detection (F32)
|
100% |
397
29.7 IPS |
|
|
Object Detection (F16)
|
100% |
1025
76.5 IPS |
|
|
Object Detection (I8)
|
97% |
511
38.1 IPS |
|
|
Face Detection (F32)
|
100% |
2311
27.5 IPS |
|
|
Face Detection (F16)
|
98% |
4547
54.1 IPS |
|
|
Face Detection (I8)
|
97% |
4760
56.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
2455
19.0 IPS |
|
|
Depth Estimation (F16)
|
100% |
20776
161.1 IPS |
|
|
Depth Estimation (I8)
|
99% |
19457
150.9 IPS |
|
|
Style Transfer (F32)
|
100% |
5829
7.67 IPS |
|
|
Style Transfer (F16)
|
100% |
17403
22.9 IPS |
|
|
Style Transfer (I8)
|
100% |
17595
23.1 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
986
35.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
4685
167.3 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
5109
182.5 IPS |
|
|
Text Classification (F32)
|
100% |
222
319.1 IPS |
|
|
Text Classification (F16)
|
100% |
283
406.7 IPS |
|
|
Text Classification (I8)
|
96% |
300
431.8 IPS |
|
|
Machine Translation (F32)
|
100% |
221
4.06 IPS |
|
|
Machine Translation (F16)
|
100% |
208
3.83 IPS |
|
|
Machine Translation (I8)
|
99% |
216
3.97 IPS |
