iPhone SE (3rd generation)
Geekbench ML Score
3698
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | October 17 2024 08:18 PM |
| Views | 1 |
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% |
1330
248.9 IPS |
|
|
Image Classification (F16)
|
100% |
2326
435.2 IPS |
|
|
Image Classification (I8)
|
99% |
2321
434.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
909
15.2 IPS |
|
|
Image Segmentation (F16)
|
100% |
1238
20.7 IPS |
|
|
Image Segmentation (I8)
|
100% |
1177
19.7 IPS |
|
|
Pose Estimation (F32)
|
100% |
5771
6.99 IPS |
|
|
Pose Estimation (F16)
|
100% |
13322
16.1 IPS |
|
|
Pose Estimation (I8)
|
100% |
13309
16.1 IPS |
|
|
Object Detection (F32)
|
100% |
1332
99.5 IPS |
|
|
Object Detection (F16)
|
100% |
2274
169.7 IPS |
|
|
Object Detection (I8)
|
97% |
1346
100.5 IPS |
|
|
Face Detection (F32)
|
100% |
2695
32.0 IPS |
|
|
Face Detection (F16)
|
97% |
5280
62.8 IPS |
|
|
Face Detection (I8)
|
97% |
5237
62.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
5301
41.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
11028
85.5 IPS |
|
|
Depth Estimation (I8)
|
99% |
11100
86.1 IPS |
|
|
Style Transfer (F32)
|
100% |
17194
22.6 IPS |
|
|
Style Transfer (F16)
|
100% |
26097
34.3 IPS |
|
|
Style Transfer (I8)
|
100% |
26248
34.5 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
4082
145.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
4923
175.8 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
4914
175.5 IPS |
|
|
Text Classification (F32)
|
100% |
2193
3.15 KIPS |
|
|
Text Classification (F16)
|
100% |
3642
5.23 KIPS |
|
|
Text Classification (I8)
|
96% |
3680
5.29 KIPS |
|
|
Machine Translation (F32)
|
100% |
1176
21.6 IPS |
|
|
Machine Translation (F16)
|
100% |
1315
24.2 IPS |
|
|
Machine Translation (I8)
|
99% |
1080
19.9 IPS |
