iPhone SE (3rd generation)
Geekbench ML Score
3736
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | July 13 2024 03:53 PM |
| 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 | 3.79 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1220
228.2 IPS |
|
|
Image Classification (F16)
|
100% |
2287
428.0 IPS |
|
|
Image Classification (I8)
|
99% |
2227
416.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
854
14.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
1185
19.8 IPS |
|
|
Image Segmentation (I8)
|
100% |
1162
19.4 IPS |
|
|
Pose Estimation (F32)
|
100% |
6186
7.49 IPS |
|
|
Pose Estimation (F16)
|
100% |
13843
16.8 IPS |
|
|
Pose Estimation (I8)
|
100% |
13927
16.9 IPS |
|
|
Object Detection (F32)
|
100% |
1369
102.2 IPS |
|
|
Object Detection (F16)
|
100% |
2291
171.0 IPS |
|
|
Object Detection (I8)
|
97% |
1372
102.5 IPS |
|
|
Face Detection (F32)
|
100% |
2684
31.9 IPS |
|
|
Face Detection (F16)
|
97% |
5483
65.2 IPS |
|
|
Face Detection (I8)
|
97% |
5466
65.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
5465
42.4 IPS |
|
|
Depth Estimation (F16)
|
100% |
11209
86.9 IPS |
|
|
Depth Estimation (I8)
|
99% |
11207
86.9 IPS |
|
|
Style Transfer (F32)
|
100% |
17405
22.9 IPS |
|
|
Style Transfer (F16)
|
100% |
26640
35.0 IPS |
|
|
Style Transfer (I8)
|
100% |
26309
34.6 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
4192
149.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
4889
174.6 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
4947
176.7 IPS |
|
|
Text Classification (F32)
|
100% |
2286
3.28 KIPS |
|
|
Text Classification (F16)
|
100% |
3754
5.40 KIPS |
|
|
Text Classification (I8)
|
96% |
3790
5.45 KIPS |
|
|
Machine Translation (F32)
|
100% |
1161
21.4 IPS |
|
|
Machine Translation (F16)
|
100% |
1352
24.9 IPS |
|
|
Machine Translation (I8)
|
99% |
1139
21.0 IPS |
