iPhone SE (3rd generation)
Geekbench ML Score
3314
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | August 15 2024 06:39 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.5.1 |
| Model | iPhone SE (3rd generation) |
| Model ID | iPhone14,6 |
| Motherboard | D49AP |
| CPU Information | |
|---|---|
| Name | Apple A15 Bionic |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 3.23 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| L1 Instruction Cache | 128 KB x 1 |
| L1 Data Cache | 64.0 KB x 1 |
| L2 Cache | 4.00 MB x 1 |
| Memory Information | |
|---|---|
| Size | 3.80 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1407
263.2 IPS |
|
|
Image Classification (F16)
|
100% |
1746
326.8 IPS |
|
|
Image Classification (I8)
|
99% |
1747
326.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
816
13.6 IPS |
|
|
Image Segmentation (F16)
|
100% |
816
13.6 IPS |
|
|
Image Segmentation (I8)
|
100% |
815
13.6 IPS |
|
|
Pose Estimation (F32)
|
100% |
5675
6.87 IPS |
|
|
Pose Estimation (F16)
|
100% |
13388
16.2 IPS |
|
|
Pose Estimation (I8)
|
100% |
13410
16.2 IPS |
|
|
Object Detection (F32)
|
100% |
1370
102.2 IPS |
|
|
Object Detection (F16)
|
100% |
1855
138.5 IPS |
|
|
Object Detection (I8)
|
97% |
1372
102.4 IPS |
|
|
Face Detection (F32)
|
100% |
2458
29.2 IPS |
|
|
Face Detection (F16)
|
97% |
3959
47.1 IPS |
|
|
Face Detection (I8)
|
97% |
3952
47.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
5036
39.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
8148
63.2 IPS |
|
|
Depth Estimation (I8)
|
99% |
8139
63.1 IPS |
|
|
Style Transfer (F32)
|
100% |
16190
21.3 IPS |
|
|
Style Transfer (F16)
|
100% |
25155
33.1 IPS |
|
|
Style Transfer (I8)
|
100% |
25105
33.0 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
3760
134.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
4878
174.2 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
4863
173.7 IPS |
|
|
Text Classification (F32)
|
100% |
2208
3.17 KIPS |
|
|
Text Classification (F16)
|
100% |
3480
5.00 KIPS |
|
|
Text Classification (I8)
|
96% |
3474
4.99 KIPS |
|
|
Machine Translation (F32)
|
100% |
1121
20.6 IPS |
|
|
Machine Translation (F16)
|
100% |
1336
24.6 IPS |
|
|
Machine Translation (I8)
|
99% |
1057
19.5 IPS |
