iPhone SE (2nd generation)
Geekbench ML Score
1196
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | September 07 2024 02:58 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 16.2 |
| 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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
538
100.7 IPS |
|
|
Image Classification (F16)
|
100% |
644
120.5 IPS |
|
|
Image Classification (I8)
|
99% |
646
120.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
426
7.11 IPS |
|
|
Image Segmentation (F16)
|
100% |
420
7.01 IPS |
|
|
Image Segmentation (I8)
|
100% |
419
6.99 IPS |
|
|
Pose Estimation (F32)
|
100% |
3209
3.89 IPS |
|
|
Pose Estimation (F16)
|
100% |
5545
6.72 IPS |
|
|
Pose Estimation (I8)
|
100% |
5551
6.72 IPS |
|
|
Object Detection (F32)
|
100% |
566
42.2 IPS |
|
|
Object Detection (F16)
|
100% |
725
54.1 IPS |
|
|
Object Detection (I8)
|
97% |
575
43.0 IPS |
|
|
Face Detection (F32)
|
100% |
1112
13.2 IPS |
|
|
Face Detection (F16)
|
100% |
1161
13.8 IPS |
|
|
Face Detection (I8)
|
99% |
1151
13.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
1946
15.1 IPS |
|
|
Depth Estimation (F16)
|
99% |
2497
19.4 IPS |
|
|
Depth Estimation (I8)
|
99% |
2494
19.3 IPS |
|
|
Style Transfer (F32)
|
100% |
5543
7.29 IPS |
|
|
Style Transfer (F16)
|
100% |
7544
9.92 IPS |
|
|
Style Transfer (I8)
|
100% |
7531
9.91 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1612
57.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1684
60.1 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
1669
59.6 IPS |
|
|
Text Classification (F32)
|
100% |
707
1.02 KIPS |
|
|
Text Classification (F16)
|
100% |
404
581.0 IPS |
|
|
Text Classification (I8)
|
96% |
398
572.0 IPS |
|
|
Machine Translation (F32)
|
100% |
462
8.51 IPS |
|
|
Machine Translation (F16)
|
99% |
848
15.6 IPS |
|
|
Machine Translation (I8)
|
99% |
487
8.97 IPS |
