iPhone SE (3rd generation)
Geekbench ML Score
3221
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | August 01 2024 08:22 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.6 |
| 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% |
1391
260.2 IPS |
|
|
Image Classification (F16)
|
100% |
1741
325.8 IPS |
|
|
Image Classification (I8)
|
99% |
1741
325.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
801
13.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
793
13.2 IPS |
|
|
Image Segmentation (I8)
|
100% |
798
13.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
5446
6.60 IPS |
|
|
Pose Estimation (F16)
|
100% |
12869
15.6 IPS |
|
|
Pose Estimation (I8)
|
100% |
13294
16.1 IPS |
|
|
Object Detection (F32)
|
100% |
1356
101.2 IPS |
|
|
Object Detection (F16)
|
100% |
1849
138.0 IPS |
|
|
Object Detection (I8)
|
97% |
1353
101.0 IPS |
|
|
Face Detection (F32)
|
100% |
2365
28.1 IPS |
|
|
Face Detection (F16)
|
97% |
3738
44.4 IPS |
|
|
Face Detection (I8)
|
97% |
3698
44.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
4785
37.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
7957
61.7 IPS |
|
|
Depth Estimation (I8)
|
99% |
7932
61.5 IPS |
|
|
Style Transfer (F32)
|
100% |
15884
20.9 IPS |
|
|
Style Transfer (F16)
|
100% |
24997
32.9 IPS |
|
|
Style Transfer (I8)
|
100% |
24809
32.6 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
3720
132.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
5033
179.7 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
4987
178.1 IPS |
|
|
Text Classification (F32)
|
100% |
2188
3.14 KIPS |
|
|
Text Classification (F16)
|
100% |
3106
4.46 KIPS |
|
|
Text Classification (I8)
|
96% |
3094
4.45 KIPS |
|
|
Machine Translation (F32)
|
100% |
1100
20.2 IPS |
|
|
Machine Translation (F16)
|
100% |
1229
22.6 IPS |
|
|
Machine Translation (I8)
|
99% |
1001
18.4 IPS |
