iPhone 14
Geekbench ML Score
1936
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | April 28 2025 03:51 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 16.3.1 |
| Model | iPhone 14 |
| Model ID | iPhone14,7 |
| Motherboard | D27AP |
| 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 | 5.56 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
951
178.0 IPS |
|
|
Image Classification (F16)
|
100% |
914
171.1 IPS |
|
|
Image Classification (I8)
|
99% |
921
172.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
639
10.7 IPS |
|
|
Image Segmentation (F16)
|
100% |
579
9.67 IPS |
|
|
Image Segmentation (I8)
|
100% |
576
9.62 IPS |
|
|
Pose Estimation (F32)
|
100% |
5463
6.62 IPS |
|
|
Pose Estimation (F16)
|
100% |
9569
11.6 IPS |
|
|
Pose Estimation (I8)
|
100% |
9577
11.6 IPS |
|
|
Object Detection (F32)
|
100% |
1060
79.1 IPS |
|
|
Object Detection (F16)
|
100% |
1040
77.6 IPS |
|
|
Object Detection (I8)
|
97% |
1029
76.8 IPS |
|
|
Face Detection (F32)
|
100% |
1772
21.1 IPS |
|
|
Face Detection (F16)
|
100% |
1632
19.4 IPS |
|
|
Face Detection (I8)
|
99% |
1623
19.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
3282
25.4 IPS |
|
|
Depth Estimation (F16)
|
99% |
3677
28.5 IPS |
|
|
Depth Estimation (I8)
|
99% |
3637
28.2 IPS |
|
|
Style Transfer (F32)
|
100% |
9897
13.0 IPS |
|
|
Style Transfer (F16)
|
100% |
11807
15.5 IPS |
|
|
Style Transfer (I8)
|
100% |
11726
15.4 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2405
85.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
2543
90.8 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
2562
91.5 IPS |
|
|
Text Classification (F32)
|
100% |
1008
1.45 KIPS |
|
|
Text Classification (F16)
|
100% |
465
668.5 IPS |
|
|
Text Classification (I8)
|
96% |
617
887.2 IPS |
|
|
Machine Translation (F32)
|
100% |
1357
25.0 IPS |
|
|
Machine Translation (F16)
|
99% |
1794
33.0 IPS |
|
|
Machine Translation (I8)
|
99% |
1352
24.9 IPS |
