iPhone 14
Geekbench ML Score
1927
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | February 25 2025 05:46 PM |
| Views | 5 |
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% |
941
176.0 IPS |
|
|
Image Classification (F16)
|
100% |
909
170.1 IPS |
|
|
Image Classification (I8)
|
99% |
914
171.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
632
10.6 IPS |
|
|
Image Segmentation (F16)
|
100% |
574
9.58 IPS |
|
|
Image Segmentation (I8)
|
100% |
556
9.29 IPS |
|
|
Pose Estimation (F32)
|
100% |
5369
6.50 IPS |
|
|
Pose Estimation (F16)
|
100% |
9639
11.7 IPS |
|
|
Pose Estimation (I8)
|
100% |
9571
11.6 IPS |
|
|
Object Detection (F32)
|
100% |
1045
78.0 IPS |
|
|
Object Detection (F16)
|
100% |
1053
78.6 IPS |
|
|
Object Detection (I8)
|
97% |
1025
76.5 IPS |
|
|
Face Detection (F32)
|
100% |
1749
20.8 IPS |
|
|
Face Detection (F16)
|
100% |
1607
19.1 IPS |
|
|
Face Detection (I8)
|
99% |
1598
19.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
3256
25.3 IPS |
|
|
Depth Estimation (F16)
|
99% |
3644
28.3 IPS |
|
|
Depth Estimation (I8)
|
99% |
3576
27.7 IPS |
|
|
Style Transfer (F32)
|
100% |
9958
13.1 IPS |
|
|
Style Transfer (F16)
|
100% |
11736
15.4 IPS |
|
|
Style Transfer (I8)
|
100% |
11767
15.5 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2431
86.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
2547
91.0 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
2561
91.5 IPS |
|
|
Text Classification (F32)
|
100% |
998
1.43 KIPS |
|
|
Text Classification (F16)
|
100% |
475
682.7 IPS |
|
|
Text Classification (I8)
|
96% |
648
931.4 IPS |
|
|
Machine Translation (F32)
|
100% |
1353
24.9 IPS |
|
|
Machine Translation (F16)
|
99% |
1756
32.3 IPS |
|
|
Machine Translation (I8)
|
99% |
1336
24.6 IPS |
