iPhone SE (3rd generation)
Geekbench ML Score
3661
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | October 08 2024 09:07 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 18.1 |
| 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% |
1310
245.2 IPS |
|
|
Image Classification (F16)
|
100% |
2324
434.9 IPS |
|
|
Image Classification (I8)
|
99% |
2309
432.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
869
14.5 IPS |
|
|
Image Segmentation (F16)
|
100% |
1170
19.5 IPS |
|
|
Image Segmentation (I8)
|
100% |
1135
19.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
5622
6.81 IPS |
|
|
Pose Estimation (F16)
|
100% |
13476
16.3 IPS |
|
|
Pose Estimation (I8)
|
100% |
13278
16.1 IPS |
|
|
Object Detection (F32)
|
100% |
1354
101.1 IPS |
|
|
Object Detection (F16)
|
100% |
2310
172.5 IPS |
|
|
Object Detection (I8)
|
97% |
1341
100.1 IPS |
|
|
Face Detection (F32)
|
100% |
2675
31.8 IPS |
|
|
Face Detection (F16)
|
97% |
5211
62.0 IPS |
|
|
Face Detection (I8)
|
97% |
5190
61.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
5340
41.4 IPS |
|
|
Depth Estimation (F16)
|
100% |
10543
81.8 IPS |
|
|
Depth Estimation (I8)
|
99% |
10595
82.2 IPS |
|
|
Style Transfer (F32)
|
100% |
16381
21.5 IPS |
|
|
Style Transfer (F16)
|
100% |
26333
34.6 IPS |
|
|
Style Transfer (I8)
|
100% |
26132
34.4 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
4140
147.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
4953
176.9 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
4942
176.5 IPS |
|
|
Text Classification (F32)
|
100% |
2241
3.22 KIPS |
|
|
Text Classification (F16)
|
100% |
3759
5.40 KIPS |
|
|
Text Classification (I8)
|
96% |
3782
5.44 KIPS |
|
|
Machine Translation (F32)
|
100% |
1136
20.9 IPS |
|
|
Machine Translation (F16)
|
100% |
1269
23.4 IPS |
|
|
Machine Translation (I8)
|
99% |
1047
19.3 IPS |
