iPhone SE (3rd generation)
Geekbench ML Score
2074
Core ML GPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | August 28 2024 10:41 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 18.0 |
| 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 | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
743
139.1 IPS |
|
|
Image Classification (F16)
|
100% |
629
117.7 IPS |
|
|
Image Classification (I8)
|
99% |
554
103.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
822
13.7 IPS |
|
|
Image Segmentation (F16)
|
100% |
863
14.4 IPS |
|
|
Image Segmentation (I8)
|
100% |
848
14.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
8472
10.3 IPS |
|
|
Pose Estimation (F16)
|
100% |
8446
10.2 IPS |
|
|
Pose Estimation (I8)
|
100% |
9518
11.5 IPS |
|
|
Object Detection (F32)
|
100% |
829
61.9 IPS |
|
|
Object Detection (F16)
|
100% |
883
65.9 IPS |
|
|
Object Detection (I8)
|
97% |
836
62.4 IPS |
|
|
Face Detection (F32)
|
100% |
3282
39.0 IPS |
|
|
Face Detection (F16)
|
98% |
3443
40.9 IPS |
|
|
Face Detection (I8)
|
97% |
4156
49.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
5883
45.6 IPS |
|
|
Depth Estimation (F16)
|
100% |
5805
45.0 IPS |
|
|
Depth Estimation (I8)
|
99% |
5581
43.3 IPS |
|
|
Style Transfer (F32)
|
100% |
14775
19.4 IPS |
|
|
Style Transfer (F16)
|
100% |
17358
22.8 IPS |
|
|
Style Transfer (I8)
|
100% |
18666
24.6 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2734
97.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
2991
106.8 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
2834
101.2 IPS |
|
|
Text Classification (F32)
|
100% |
1045
1.50 KIPS |
|
|
Text Classification (F16)
|
100% |
1827
2.63 KIPS |
|
|
Text Classification (I8)
|
96% |
1823
2.62 KIPS |
|
|
Machine Translation (F32)
|
100% |
245
4.51 IPS |
|
|
Machine Translation (F16)
|
100% |
244
4.48 IPS |
|
|
Machine Translation (I8)
|
99% |
241
4.43 IPS |
