iPhone SE (3rd generation)
Geekbench ML Score
3643
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | September 08 2024 08:39 AM |
| Views | 2 |
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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1356
253.8 IPS |
|
|
Image Classification (F16)
|
100% |
2334
436.8 IPS |
|
|
Image Classification (I8)
|
99% |
2352
440.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
904
15.1 IPS |
|
|
Image Segmentation (F16)
|
100% |
1196
20.0 IPS |
|
|
Image Segmentation (I8)
|
100% |
1205
20.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
6010
7.28 IPS |
|
|
Pose Estimation (F16)
|
100% |
13974
16.9 IPS |
|
|
Pose Estimation (I8)
|
100% |
13980
16.9 IPS |
|
|
Object Detection (F32)
|
100% |
1381
103.1 IPS |
|
|
Object Detection (F16)
|
100% |
2295
171.3 IPS |
|
|
Object Detection (I8)
|
97% |
1394
104.1 IPS |
|
|
Face Detection (F32)
|
100% |
2682
31.9 IPS |
|
|
Face Detection (F16)
|
97% |
5211
62.0 IPS |
|
|
Face Detection (I8)
|
97% |
4819
57.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
5182
40.2 IPS |
|
|
Depth Estimation (F16)
|
100% |
10321
80.0 IPS |
|
|
Depth Estimation (I8)
|
99% |
10686
82.9 IPS |
|
|
Style Transfer (F32)
|
100% |
16211
21.3 IPS |
|
|
Style Transfer (F16)
|
100% |
25900
34.1 IPS |
|
|
Style Transfer (I8)
|
100% |
26108
34.3 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
3992
142.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
4979
177.8 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
5005
178.8 IPS |
|
|
Text Classification (F32)
|
100% |
2276
3.27 KIPS |
|
|
Text Classification (F16)
|
100% |
3929
5.65 KIPS |
|
|
Text Classification (I8)
|
96% |
3450
4.96 KIPS |
|
|
Machine Translation (F32)
|
100% |
996
18.3 IPS |
|
|
Machine Translation (F16)
|
100% |
1072
19.7 IPS |
|
|
Machine Translation (I8)
|
99% |
1011
18.6 IPS |
